hana_dev_en

SAP HANA Appliance Software SPS 05 

Document Version: 1.0 - 2012-11-29 

SAP HANA Developer Guide 

PUBLIC

Table of Contents 

1 Overview. ....................................................................8 

2 SAP HANA. ...................................................................9 

2.1 The SAP HANA In-Memory Database. ................................................ 9 

2.1.1 Columnar Data Storage. ...................................................9 

2.1.2 Parallel Processing. ......................................................10 

2.1.3 Simplifying Applications. ..................................................10 

2.2 SAP HANA Database Architecture. ..................................................11 

2.3 SAP HANA Extended Application Services. ............................................12 

2.4 Refactoring SAP HANA Based Applications. ........................................... 15 

3 SAP HANA as a Development Platform. ............................................16 

3.1 Developer Scenarios. ........................................................... 16 

3.1.1 Scenario: Developing Native SAP HANA Applications. ............................. 17 

3.1.2 Scenario: Using Database Client Interfaces. .................................... 18 

3.2 Development Objects. ...........................................................19 

3.3 Repository. ...................................................................21 

3.4 SAP HANA Studio. .............................................................23 

3.4.1 Modeler Perspective. .................................................... 23 

3.4.2 SAP HANA Development Perspective. ........................................25 

3.4.3 Debug Perspective. ..................................................... 30 

3.4.4 Administration Console Perspective. ......................................... 31 

3.5 Getting Started. ...............................................................32 

3.5.1 Adding a System. .......................................................33 

4 Setting up Your Application. .................................................... 34 

4.1 Setting up Delivery Units. ........................................................ 35 

4.1.1 Maintaining the Delivery-Unit Vendor ID. .......................................35 

4.1.2 SAP HANA Delivery Unit Naming Conventions. ..................................36 

4.1.3 Creating a Delivery Unit. ..................................................36 

4.2 Using SAP HANA Projects. ....................................................... 37 

4.2.1 SAP HANA Repository: Workspaces. .........................................38 

4.2.2 Creating a Repository Workspace. ...........................................39 

4.2.3 SAP HANA Studio Projects. ................................................39 

4.2.4 Creating a Project for SAP HANA XS. .........................................40 

4.2.5 Sharing a Project for SAP HANA XS. ......................................... 40 

4.2.6 Importing a Project in SAP HANA XS. .........................................41 

4.3 Maintaining Repository Packages. ..................................................42 

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Table of Contents

4.3.1 SAP HANA Repository Packages and Namespaces. ...............................43 

4.3.2 Defining Repository Package Privileges. .......................................46 

4.3.3 Creating a Package. .....................................................46 

4.3.4 Defining a Package Hierarchy. ..............................................47 

4.4 Creating the Application Descriptors. ................................................49 

4.4.1 The SAP HANA XS Application Descriptor. .....................................49 

4.4.2 Create an Application Descriptor File. .........................................50 

4.4.3 The Application-Access File. ...............................................50 

4.4.4 Application-Access File Keyword Options. ..................................... 53 

4.4.5 Application-Access URL Rewrite Rules. ....................................... 56 

4.4.6 Enabling Access to SAP HANA XS Application Packages. ...........................57 

4.4.7 The Application-Privileges File. ............................................. 59 

4.4.8 Create an SAP HANA XS Application Privileges File. .............................. 60 

4.5 Tutorial: My First SAP HANA Application. .............................................62 

4.5.1 Open the Development Perspective. ......................................... 62 

4.5.2 Add a System. .........................................................63 

4.5.3 Add a Workspace. ...................................................... 66 

4.5.4 Add a Project. ......................................................... 67 

4.5.5 Share Your Project. ..................................................... 68 

4.5.6 Write Server-Side JavaScript. ..............................................70 

4.5.7 Retrieve Data. ......................................................... 72 

5 Setting up the Persistence Model. ................................................74 

5.1 Schema. .................................................................... 75 

5.2 Creating Schemas. .............................................................76 

5.3 Tables. ..................................................................... 76 

5.4 Creating Tables. ...............................................................77 

5.5 Sequences. ..................................................................78 

5.6 Creating Sequences. ............................................................79 

5.7 SQL Views. .................................................................. 80 

5.8 Creating SQL Views. ............................................................81 

5.9 Data Provisioning Using Table Import. ...............................................82 

5.9.1 Table-Import Model. .....................................................83 

5.9.2 Table-Import Data. ......................................................83 

5.9.3 Table-Import Extensions. ................................................. 84 

5.9.4 Table-Import Configuration-File Syntax. .......................................84 

5.10 Importing Data Using Table Import. .................................................85 

5.11 Using Imported Table Data in SAP HANA. .............................................87 

5.12 Using Imported Table Data in an SAP HANA XS Application. ................................88 

5.13 Extending a Table Import. ........................................................89 



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6 Setting Up the Analytic Model. ...................................................92 

6.1 Setting Up the Modeling Environment. ...............................................94 

6.1.1 Setting Modeler Preferences. .............................................. 94 

6.1.2 Configuring the Import Server. ............................................. 95 

6.1.3 Importing Table Definitions. ............................................... 95 

6.1.4 Loading Data into Tables. ................................................. 97 

6.1.5 Copying Content Delivered by SAP. ..........................................99 

6.1.6 Mapping the Authoring Schema to the Physical Schema. ..........................100 

6.1.7 Generating Time Data. ...................................................102 

6.2 Creating Views. ...............................................................103 

6.2.1 Attributes and Measures. ................................................ 103 

6.2.2 Attribute Views. .......................................................104 

6.2.3 Creating Attribute Views. .................................................105 

6.2.4 Analytic Views. ........................................................109 

6.2.5 Creating Analytic Views. ..................................................110 

6.2.6 Calculation Views. ......................................................115 

6.2.7 Creating Calculation Views . ...............................................116 

6.2.8 Assigning Variables. .................................................... 123 

6.2.9 Creating Input Parameters. ...............................................125 

6.2.10 Creating Hierarchies. ....................................................127 

6.2.11 Using Currency and Unit of Measure. ........................................130 

6.2.12 Activating Objects. .....................................................132 

6.3 Creating Decision Tables. ....................................................... 133 

6.3.1 Changing the Layout of a Decision Table. ..................................... 139 

6.3.2 Using Parameters in a Decision Table. ........................................139 

6.4 Managing Object Versions. ...................................................... 140 

6.4.1 Switching Ownership of Inactive Objects. .....................................140 

6.4.2 Toggling Versions of Content Objects. ........................................141 

6.4.3 Viewing Version History of Content Objects. ...................................142 

6.5 Working with Objects. ..........................................................142 

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6.5.1 Managing Layout. ......................................................142 

6.5.2 Filtering Packages and Objects. ............................................142 

6.5.3 Refactoring Objects. ....................................................143 

6.5.4 Validating Models . .....................................................144 

6.5.5 Generating Object Documentation. ..........................................144 

6.5.6 Enabling Multilanguage Support for Objects. ...................................145 

6.5.7 Checking Model References. .............................................. 145 

6.5.8 Viewing the Job Log. ....................................................146 

6.5.9 Maintaining Search Attributes. .............................................146 

6.5.10 Previewing Data of Content Objects. .........................................146 

6.5.11 Functions used in Expressions. .............................................147 

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6.5.12 Searching Tables, Models and Column Views. ..................................152 

6.5.13 Setting Keyboard Shortcuts. .............................................. 153 

6.5.14 Copying an Object. .....................................................154 

6.6 Importing BW Objects. ......................................................... 154 

7 Developing Procedures. ....................................................... 158 

7.1 Editing SQLScript. .............................................................159 

7.2 Debugging SQLScript. ..........................................................161 

7.3 Developing Procedures in the Modeler Editor. .........................................162 

8 Defining Web-based Data Access. ............................................... 164 

8.1 Data Access with OData in SAP HANA XS. ............................................164 

8.1.1 OData in SAP HANA XS. ................................................. 164 

8.1.2 OData Service Definitions. ................................................165 

8.1.3 OData URI Parameters, Query Options, and Features. ............................ 167 

8.1.4 OData Security Considerations. ............................................183 

8.1.5 Defining the Data an OData Service Exposes. ...................................183 

8.1.6 Creating an OData Service Definition. ........................................183 

8.1.7 OData Service Definition Language Syntax. ....................................184 

8.1.8 OData Service Definition: SQL-EDM Type Mapping. ..............................186 

8.1.9 OData Service-Definition Examples. .........................................188 

8.2 Data Access with XMLA in SAP HANA XS. ............................................201 

8.2.1 XML for Analysis (XMLA). ................................................201 

8.2.2 XMLA Service Definition. .................................................202 

8.2.3 XMLA Security Considerations. ............................................203 

8.2.4 Multidimensional Expressions (MDX). ....................................... 203 

8.2.5 MDX Functions. .......................................................204 

8.2.6 MDX Extensions. ...................................................... 207 

8.2.7 Defining the Data an XMLA Service Exposes. ...................................210 

8.2.8 Creating an XMLA Service Definition. ........................................210 

9 Writing Server-Side JavaScript Applications. .......................................212 

9.1 Data Access with JavaScript in SAP HANA XS. .........................................212 

9.2 Writing JavaScript Code. ........................................................212 

9.2.1 Server-Side JavaScript in SAP HANA XS. ..................................... 212 

9.2.2 JavaScript Editor. ......................................................213 

9.2.3 Writing Server-Side JavaScript Applications. ...................................214 

9.3 Writing JavaScript Libraries. ..................................................... 215 

9.3.1 Server-Side JavaScript Libraries. ...........................................215 

9.3.2 Writing Server-Side JavaScript Libraries. ..................................... 215 

9.3.3 Importing Server-Side JavaScript Libraries. ....................................216 

9.4 Server-Side JavaScript APIs. .....................................................217 



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9.5 The SQL Connection Configuration File. ............................................. 218 

9.6 Tracing JavaScript. ............................................................220 

9.6.1 Server-Side JavaScript Tracing. ............................................220 

9.6.2 Tracing Server-Side JavaScript Applications. ..................................220 

9.6.3 Viewing Server-Side JavaScript Application Trace Files. ...........................221 

9.7 Debugging JavaScript. ..........................................................221 

9.7.1 Opening a Port for JavaScript Debugging. .....................................223 

10 Building UIs With SAPUI5. ..................................................... 225 

10.1 Installing SAPUI5 Application Development Tools. ......................................226 

10.2 Creating an SAPUI5 Application. .................................................. 226 

10.2.1 Local Testing of a SAPUI5 Application. .......................................228 

10.2.2 SAPUI5 Runtime Version Comparison. .......................................229 

10.3 Supporting Translation. ........................................................ 230 

11 Enabling Search. .............................................................231 

11.1 Creating Full Text Indexes. .......................................................231 

11.1.1 Full Text Index Types. ...................................................233 

11.1.2 Synchronization. ...................................................... 236 

11.1.3 Text Analysis. .........................................................238 

11.1.4 Dropping Full Text Indexes. ...............................................242 

11.1.5 Altering Full Text Index Parameters. .........................................242 

11.1.6 Full Text Index Parameters. ...............................................243 

11.2 Building SQL Search Queries. .................................................... 248 

11.2.1 Search Queries with CONTAINS. ...........................................248 

11.2.2 EXACT Search. ........................................................251 

11.2.3 LINGUISTIC Search. ....................................................252 

11.2.4 FUZZY Search. ........................................................252 

11.3 Building Search Apps. ..........................................................304 

11.3.1 Introduction to the UI Toolkit for Info Access. ..................................304 

11.3.2 Installing the Service and the Toolkit. ........................................305 

11.3.3 Getting to Know the Demo App. ............................................306 

11.3.4 Getting to Know the Demo HTML. .......................................... 307 

11.3.5 Preparing Your Source Data. ..............................................308 

11.3.6 Connecting Your Source Data. .............................................310 

11.3.7 Defining the Page Layout. .................................................311 

11.3.8 Configuring the Widgets. .................................................311 

11.3.9 Defining the Layout of Result Lists and Details. ................................. 315 

12 Setting Up Roles and Authorizations. .............................................316 

12.1 The Authorization Model. ........................................................316 

12.2 Authentication Overview. ........................................................317 

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12.3 Roles. ......................................................................317 

12.3.1 Roles. .............................................................. 318 

12.3.2 Roles as Repository Objects. ..............................................319 

12.3.3 Creating Roles in the Repository. ...........................................320 

12.4 Privileges. .................................................................. 325 

12.4.1 System Privileges. ..................................................... 325 

12.4.2 Object Privileges. ......................................................325 

12.4.3 Package Privileges. .....................................................326 

12.4.4 Analytic Privileges. .....................................................328 

12.4.5 Creating Analytic Privileges. .............................................. 337 

12.4.6 Granting Privileges to Users. .............................................. 341 

12.5 Application Access. ........................................................... 342 

13 Implementing Lifecycle Management . ............................................344 

13.1 SAP HANA Delivery Units. .......................................................344 

13.2 The SAP HANA Delivery-Unit Lifecycle. ............................................. 344 

13.3 Exporting Delivery Units. ........................................................345 

13.4 Importing Delivery Units. ........................................................347 

13.5 Translating Delivery Units. .......................................................348 

13.5.1 SAP HANA Delivery-Unit Translation Details. .................................. 349 

13.5.2 Maintaining Translation Details. ............................................349 

14 Using Database Client Interfaces. ................................................351 

14.1 Connecting via ODBC. ..........................................................351 

14.1.1 Using the User Store. ...................................................352 

14.1.2 Testing the ODBC Installation. .............................................353 

14.2 Connecting via JDBC. ..........................................................354 

14.2.1 Tracing JDBC Connections. ...............................................355 

14.2.2 Valid Java-to-SQL Conversions. ............................................357 

14.3 Connecting via ODBO. ..........................................................358 

14.3.1 Connecting with Microsoft Excel. ...........................................358 

14.3.2 Multidimensional Expressions (MDX). ........................................361 

14.3.3 MDX Functions. .......................................................362 

14.3.4 MDX Extensions. ...................................................... 366 

15 SAP HANA Developer References. ...............................................369 



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1 Overview 

This guide presents a developer’s view of SAP HANA ® . It explains how to use the SAP HANA development tools to 

create comprehensive analytical models and to build applications with SAP HANA's programmatic interfaces and 

integrated development environment, including to develop native code that runs inside SAP HANA. 

The guide is organized as follows: 

● SAP HANA [page 9] describes the capabilities of SAP HANA. 

● SAP HANA as a Development Platform [page 16] describes the main developer scenarios, the development 

process and the development environment. 

● Setting up Your Application [page 34] describes how to get started developing SAP HANA applications. 

Most of the remaining chapters explain how to develop various SAP HANA development objects. 

Audience 

Note: Application development with SAP HANA Extended Application Services (SAP HANA XS) is 

currently only available as an SAP-led project solution, for pre-approved customers and partners. This 

applies to server-side JavaScript programming, support for ODATA and XMLA, Web server features and 

the Web application development environment. For more information, see SAP Note 1779803. 

This guide is aimed at two developer roles: 

● Modeler: This person, often a business/data analyst or database expert, is concerned with the definition of 

the model and schemas that will be used in SAP HANA, the specification and definition of tables, views, 

primary keys, indexes, partitions and other aspects of the layout and inter-relationship of the data in SAP 

HANA. 

The data modeler is also concerned with designing and defining authorization and access control, through the 

specification of privileges, roles and users. 

The modeler generally uses the Administration Console and Modeler perspectives and tools of the SAP HANA 

studio. 

● Application Programmer: The programmer is concerned with building SAP HANA applications, which could 

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take many forms but are designed based on the model-view-controller architecture. Programmers develop 

the code for: 

○ View, which could run inside a browser or on a mobile device 

○ Controller, which typically runs in the context of an application server 

○ Model, which interacts closely with the data model, performs efficient queries, and may be developed to 

run within the SAP HANA data engine, using embedded procedures or libraries 

The programmer generally uses the SAP HANA Development perspective and tools of the SAP HANA studio. 

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Overview

2 SAP HANA 

SAP HANA is an in-memory data platform that is deployable as an appliance or in the cloud. At its core, it is an 

innovative in-memory relational database management system that makes full use of the capabilities of current 

hardware to increase application performance, to reduce cost of ownership, and to enable new scenarios and 

applications that were not possible before. 

With SAP HANA, you have the opportunity to build applications that integrate the business control logic and the 

database layer with unprecedented performance. As a developer, one of the key questions is how you can 

minimize data movements. The more you can do directly on the data in memory next to the CPUs, the better the 

application will perform. 

2.1 The SAP HANA In-Memory Database 

SAP HANA was designed to run on modern, distributed computers built out of multi-core CPUs (multiple CPUs on 

one chip) with fast communication between processor cores, and containing terabytes of main memory. With 

SAP HANA, all data is available in main memory, which completely avoids the performance penalty of disk I/O. 

Either disk or solid-state drives are still required for permanent persistency in the event of a power failure or some 

other catastrophe. This does not slow down performance, however, because the required backup operations to 

disk can take place asynchronously as a background task. 

2.1.1 Columnar Data Storage 

A database table is conceptually a two-dimensional data structure organized in rows and columns. Computer 

memory, in contrast, is organized as a linear structure. A table can be represented in row-order or column-order. 

A row-oriented organization stores a table as a sequence of records. Conversely, in column storage the entries of 

a column are stored in contiguous memory locations. SAP HANA supports both, but is particularly optimized for 

column-order storage. 

Columnar data storage allows highly efficient compression. Especially if a column is sorted, there will normally be 

repeated adjacent values. SAP HANA employs highly efficient compression methods, such as run-length 

encoding, cluster coding and dictionary coding. With dictionary encoding, columns are stored as sequences of bitcoded 

integers. That means that a check for equality can be executed on the integers (for example during scans 

or join operations). This is much faster than comparing, for example, string values. 


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Columnar storage, in many cases, eliminates the need for additional index structures. Storing data in columns is 

functionally similar to having a built-in index for each column. The column scanning speed of the in-memory 

column store and the compression mechanisms – especially dictionary compression – allow read operations with 

very high performance. In many cases it will not be required to have additional indexes. Eliminating additional 

indexes reduces complexity and eliminates effort for defining and maintaining metadata. 

2.1.2 Parallel Processing 

SAP HANA was designed from the ground up to perform its basic calculations (such as analytic joins, scans and 

aggregations) in parallel, often using hundreds of cores at the same time, fully utilizing the available computing 

resources of distributed systems. 

With columnar data, operations on single columns, such as searching or aggregations, can be implemented as 

loops over an array stored in contiguous memory locations. Such an operation has high spatial locality and can 

efficiently be executed in the CPU cache. With row-oriented storage, the same operation would be much slower 

because data of the same column is distributed across memory and the CPU is slowed down by cache misses. 

Compressed data can be loaded into the CPU cache faster. This is because the limiting factor is the data transport 

between memory and CPU cache, and so the performance gain will exceed the additional computing time needed 

for decompression. 

Column-based storage also allows execution of operations in parallel using multiple processor cores. In a column 

store, data is already vertically partitioned. This means that operations on different columns can easily be 

processed in parallel. If multiple columns need to be searched or aggregated, each of these operations can be 

assigned to a different processor core. In addition, operations on one column can be parallelized by partitioning 

the column into multiple sections that can be processed by different processor cores. 

2.1.3 Simplifying Applications 

Traditional business applications often use materialized aggregates to increase performance. These aggregates 

are computed and stored either after each write operation on the aggregated data, or at scheduled times. Read 

operations read the materialized aggregates instead of computing them each time they are required. 

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With a scanning speed of several gigabytes per millisecond, SAP HANA makes it possible to calculate aggregates 

on large amounts of data on-the-fly with high performance. This eliminates the need for materialized aggregates 

in many cases, simplifying data models, and correspondingly the application logic. Furthermore, with on-the fly 

aggregation, the aggregate values are always up-to-date unlike materialized aggregates that may be updated only 

at scheduled times. 

2.2 SAP HANA Database Architecture 

A running SAP HANA system consists of multiple communicating processes (services). The following shows the 

main SAP HANA database services in a classical application context. 

Such traditional database applications use well-defined interfaces (for example, ODBC and JDBC) to 

communicate with the database management system functioning as a data source, usually over a network 

connection. Often running in the context of an application server, these traditional applications use Structured 

Query Language (SQL) to manage and query the data stored in the database. 

The main SAP HANA database management component is known as the index server. The index server contains 

the actual data stores and the engines for processing the data. The index server processes incoming SQL or MDX 

statements in the context of authenticated sessions and transactions. 


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The SAP HANA database has its own scripting language named SQLScript. The motivation for SQLScript is to 

embed data-intensive application logic into the database. Classical applications tend to offload only very limited 

functionality into the database using SQL. This results in extensive copying of data from and to the database, and 

in programs that slowly iterate over huge data loops and are hard to optimize and parallelize. SQLScript is based 

on side-effect free functions that operate on tables using SQL queries for set processing, and is therefore 

parallelizable over multiple processors. 

In addition to SQLScript, SAP HANA supports a framework for the installation of specialized and optimized 

functional libraries, which are tightly integrated with different data engines of the index server. Two of these 

functional libraries are the SAP HANA Business Function Library (BFL) and the SAP HANA Predictive Analytics 

Library (PAL). BFL and PAL functions can be called directly from within SQLScript. 

SAP HANA also supports the development of programs written in the popular statistics language R. 

SQL and SQLScript are implemented using a common infrastructure of built-in data engine functions that have 

access to various meta definitions, such as definitions of relational tables, columns, views, and indexes, and 

definitions of SQLScript procedures. This metadata is stored in one common catalog. 

The database persistence layer is responsible for durability and atomicity of transactions. It ensures that the 

database can be restored to the most recent committed state after a restart and that transactions are either 

completely executed or completely undone. 

The index server uses the preprocessor server for analyzing text data and extracting the information on which the 

text search capabilities are based. The name server owns the information about the topology of a SAP HANA 

system. In a distributed system, the name server knows where the components are running and which data is 

located on which server. The statistics server collects information about status, performance and resource 

consumption from the other servers in the system. Monitoring clients, such as the SAP HANA studio, access the 

statistics server to get the status of various alert monitors. The statistics server also provides a history of 

measurement data for further analysis. 

Related Links 

SAP HANA SQLScript Reference 

SAP HANA Business Function Library (BFL) Reference 

SAP HANA Predictive Analysis Library (PAL) Reference 

SAP HANA R Integration Guide 

2.3 SAP HANA Extended Application Services 

Traditional database applications use interfaces such as ODBC and JDBC with SQL to manage and query their 

data. The following illustrates such applications using the common Model-View-Controller (MVC) development 

architecture. 

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SAP HANA greatly extends the traditional database server role. SAP HANA functions as a comprehensive 

platform for the development and execution of native data-intensive applications that run efficiently in SAP HANA, 

taking advantage of its in-memory architecture and parallel execution capabilities. 

By restructuring your application in this way, not only do you gain from the increased performance due to the 

integration with the data source, you can effectively eliminate the overhead of the middle-tier between the userinterface 

(the view) and the data-intensive control logic, as shown in the following figure. 

In support of this data-integrated application paradigm, SAP HANA Extended Application Services provides a 

comprehensive set of embedded services that provide end-to-end support for Web-based applications. This 

includes a lightweight web server, configurable OData support, server-side JS execution and, of course, full 

access to SQL and SQLScript. 

These SAP HANA Extended Application Services are provided by the SAP HANA XS server, which provides 

lightweight application services that are fully integrated into SAP HANA. It allows clients to access the SAP HANA 

system via HTTP. Controller applications can run completely natively on SAP HANA, without the need for an 

additional external application server.The following shows the SAP HANA XS server as part of the SAP HANA 

system. 


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The application services can be used to expose the database data model, with its tables, views and database 

procedures, to clients. This can be done in a declarative way using OData services or by writing native applicationspecific 

code that runs in the SAP HANA context . Also, you can use SAP HANA XS to build dynamic HTML5 UI 

applications. 

In addition to exposing the data model, SAP HANA XS also hosts system services that are part of the SAP HANA 

system. The search service is an example of such a system application. No data is stored in the SAP HANA XS 

server itself. To read tables or views, to modify data or to execute SQLScript database procedures and 

calculations, it connects to the index server (or servers, in case of a distributed system). 

Related Links 





Building UIs With SAPUI5 [page 225] 

This section provides introductory information about UI development toolkit for HTML5. 

Enabling Search [page 231] 

With a SAP HANA database, your users will want to search tables and views much like they would when 

searching for information on the Internet. In SAP HANA, you can either directly query data using SQL queries 

or you can build search apps using a UI toolkit. 

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2.4 Refactoring SAP HANA Based Applications 

The possibility to run application-specific code in SAP HANA raises the question: What kind of logic should run 

where? Clearly, data-intensive and model-based calculations must be close to the data and, therefore, need to be 

executed in the index server, for instance, using SQLScript or the code of the specialized functional libraries. 

The presentation (view) logic runs on the client – for example, as an HTML5 application in a Web browser or on a 

mobile device. 

Native application-specific code, supported by SAP HANA Extended Application Services, can be used to provide 

a thin layer between the clients on one side, and the views, tables and procedures in the index server on the other 

side. Typical applications contain, for example, control flow logic based on request parameters, invoke views and 

stored procedures in the index server, and transform the results to the response format expected by the client. 

Such applications can also send emails and consume external HTTP-based services. 

The communication between the SAP HANA XS server and index server is optimized for high performance. 

However, performance is not the only reason why the SAP HANA XS server was integrated into SAP HANA. It also 

leads to simplified administration and a better development experience. 

The SAP HANA XS server completes SAP HANA to make it a comprehensive development platform. With the SAP 

HANA XS server, developers can write SAP HANA-based applications that cover all server-side aspects, such as 

tables and database views, database procedures, server-side control logic, integration with external systems, and 

provisioning of HTTP-based services. The integration of the SAP HANA XS server into the SAP HANA system also 

helps to reduce cost of ownership, as all servers are installed, operated and updated as one system. 


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3 SAP HANA as a Development 

Platform 

To simplify and support the development of HANA Based applications, SAP HANA serves as the integrated 

development environment (IDE) for developing and delivering these SAP HANA applications. 

Built around the Eclipse-based SAP HANA studio the SAP HANA IDE supports integrated and collaborative 

development, debugging and deployment of applications that use native database procedures for data 

processing, server-side JavaScript for control and an HTML5 SDK for the development of user interface 

representation. 

The design-time environment's central component is the SAP HANA repository, which stores and manages all 

design-time objects. The following figure illustrates the principle of co-development with SAP HANA. 

Using the HANA studio on your workstation, you design and create development objects such as data models or 

server-side code files, and then store, manage and share them with other developers, by interacting with the SAP 

HANA repository. The repository enables teams to work together on a set of development objects, and ultimately 

turn them into runtime objects which can be used by clients or other applications. The repository provides the 

basis for concepts like namespaces (through packages), transport and delivery support. 

3.1 Developer Scenarios 

The possibility to run application specific code in SAP HANA creates several possibilities for developing SAP 

HANA based applications, representing various integration scenarios, and corresponding development 

processes. 

Broadly, we distinguish SAP HANA based applications into two broad categories: 

● Web-based scenarios that take full advantage of the SAP HANA Extended Application Services. In these 

scenarios, clients access SAP HANA data using standard OData or XMLA interfaces, or directly use a Webbased 

GUI that was developed using the SAPGUI5 toolkit, and that uses custom-developed server-side 

JavaScript, as well as native SQLScript procedures. 

● Traditional client-based scenarios, where an external application accesses the SAP HANA data model (tables, 

analytic views, etc.) via client interfaces such as ODBC, ODBO and JDBC, and only uses SQL and native 

SQLScript procedures. 

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SAP HANA as a Development Platform

In either case, as a developer you need to understand the SAP HANA development environment, which enables 

you to design and develop your data and analytical models, and your other HANA-based development objects in 

the form of portable and deployable delivery units. 

Common activities include: 

Table 1: Common Activities 

Activity More Information 

Setting up your development environment. Setting up Your Application [page 34] 

Setting up your schema and tables. Setting up the Persistence Model [page 74] 

Setting up views of your data. Setting Up the Analytic Model [page 92] 

Developing procedures for data-intensive logic. Developing Procedures [page 158] 

Setting up roles and authorizations. i031349596025517.ditamap 

Managing the delivery of your application. SAP HANA Delivery Units [page 344] 

For these activites, you will want to keep handy the following references: 

● SAP HANA SQL Reference, to help you writing SQL statements within procedures and from your server-side 

JavaScript. 

● SAP HANA SQLScript Reference, to help you if you are writing procedures. 

The next two sections describes the main scenarios and what activities you may need to perform for them. 

3.1.1 Scenario: Developing Native SAP HANA Applications 

Here, you want to create a Web-based scenario that takes full advantage of SAP HANA Extended Application 

Services. In this scenario, clients access SAP HANA data using standard OData or XMLA interfaces, or directly use 

a Web-based GUI that was developed using the SAPGUI5 toolkit, and that uses custom-developed server-side 

JavaScript, as well as native SQLScript procedures. 


SAP HANA as a Development Platform 

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For this scenario, you may need to perform the following activities: 

Table 2: Developing Native SAP HANA Applications 


Develop server-side JavaScript for control logic. Writing Server-Side JavaScript Applications [page 

Define OData data interfaces. Data Access with OData in SAP HANA XS [page 164] 

Define XMLA data interfaces Data Access with XMLA in SAP HANA XS [page 201] 

How to build HTML pages with SAPUI5. Building UIs With SAPUI5 [page 225] 

You will also want to keep handy the following references: 

● SAP HANA SQL Reference, to help you write SQL statements within procedures and from your server-side 

JavaScript. 

● SAP HANA XS JavaScript Reference, to help you use the SAP HANA XS JavaScript API. 

212] 

For a list of all references, see SAP HANA Developer References [page 369]. 

3.1.2 Scenario: Using Database Client Interfaces 

Here, you want to build an application outside of SAP HANA, for example, within SAP NetWeaver, that accesses 

the SAP HANA data model (for example, tables and analytic views) via client interfaces such as ODBC, ODBO and 

JDBC, and only uses SQL and native SQLScript procedures. 

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For this scenario, you may need to perform the following activities: 

Table 3: Using Database Client Interfaces 


Installing and using the SAP HANA client interfaces Using Database Client Interfaces [page 351] 

Developing procedures for data-intensive logic. Developing Procedures [page 158] 

You will also want to keep handy several references: 

● SAP HANA SQL Reference, to help you write SQL statements. 

For information on MDX in SAP HANA, see MDX Functions [page 204]. 

● SAP HANA SQLScript Reference, to help you if you are writing procedures. 

For a list of all references, see SAP HANA Developer References [page 369]. 

3.2 Development Objects 

The design-time building blocks of your SAP HANA applications are called development objects. Some of these 

development objects, such as projects and packages, are concepts that help you structure your application. 

Others, like schemas, table definitions, analytical and attribute views, help you organize the structure of your data. 

Procedures and server-side JavaScript code are the backbone of the SAP HANA application. Other types of 

development objects help you control the access to runtime objects. 

Understanding the different development objects and their use is one of the main objectives of this guide. 

The following are the building blocks for an SAP HANA application, showing the file extension and where to get 

information for building it: 



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Table 4: Application Building Blocks 

Object Description File Extension More Information 

Structure 

Project An Eclipse project for developing your 

application or part of an application. 

The .project file can be stored in the SAP 

HANA repository. 

Package A container in the repository for 

development objects. 

Modeling Data 

Schema A database schema for organizing database 

objects. 

.project SAP HANA Studio Projects 

Packages are 

represented by 

folders. 

[page 39] 

Maintaining Repository 

Packages [page 42] 

.hdbschema Schema [page 75] 

Table A database table. .hdbtable Tables [page 76] 

SQL View A virtual table based on a SQL query. .hdbview SQL Views [page 80] 

Attribute, 

Analytic and 

Calculation 

View 

A view created with modeling tools and 

designed to model a business use case. 

Decision Table A database table used to define business 

rules, for example, for validating data. 

Analytic 

Privilege 

A set of rules that restricts users to seeing 

only a subset of data in a table or view. 

Sequence A set of unique numbers, for example, for 

use as primary keys for a specific table. 

Procedure A database function for performing 

complex and data-intensive business logic 

that cannot be performed with standard 

SQL. 

Web Access 

Application 

Descriptor 

Application 

Access File 

Application 

Privilege 

20 

A file in a repository package that defines a 

root folder of a native SAP HANA 

application. All files in that package are 

available to be called via URL. 

A file that defines permissions for a native 

SAP HANA application, that is, permissions 

for accessing and running objects in the 

package. 

A file that defines a privilege related to an 

SAP HANA Extended Application Services 

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Created with the 

Navigator view. 

Setting Up the Analytic 

Model [page 92] 

Creating Decision Tables 

[page 133] 

Creating Analytic Privileges 

[page 337] 

.hdbsequence Sequences [page 78] 

.procedure Developing Procedures 

[page 158] 

.xsapp Creating the Application 

Descriptors [page 49] 

.xsaccess Enabling Access to SAP 

HANA XS Application 

Packages [page 57] 

.xsprivileges The Application-Privileges 

File [page 59] 



Object Description File Extension More Information 

Server-Side 

JavaScript 

Code 

Server-Side 

JavaScript 

Library 

OData 

Descriptor 

XMLA 

Descriptor 

SQL Connection 

Configuration 

Other 

application, for example, the right to start or 

administer the application. 

JavaScript code that can run in SAP HANA 

Extended Application Services and that can 

be accessed via URL. 

JavaScript code that can run in SAP HANA 

Extended Application Services but cannot 

be accessed via URL. The code can be 

imported into an .xsjs code file. 

A file that defines an OData service that 

exposes SAP HANA data. 

A file that defines an XMLA service that 

exposes SAP HANA data 

A file that enables execution of SQL 

statements from inside server-side 

JavaScript code with credentials that are 

different than those of the requesting user. 

.xsjs Writing Server-Side 

JavaScript Applications 

[page 214] 

.xsjslib 

.xsodata Data Access with OData in 

SAP HANA XS [page 164] 

.xsxmla Data Access with XMLA in 

SAP HANA XS [page 201] 

.xssqlcc The SQL Connection 

Configuration File [page 

218] 

Role A file that defines an SAP HANA role. .hdbrole Creating Roles in the 

Repository [page 320] 

Search Rule Set A file that defines a set of rules for use with 

fuzzy searches. The rules help decide what 

is a valid match in a search. 

Resource 

Bundle 

3.3 Repository 

A file for defining translatable UI texts for an 

application. 

.searchruleset Search Rules [page 297] 

.hdbtextbundle Creating an SAPUI5 

Application [page 226] 

The SAP HANA repository is the design-time storage system for development objects and is built into SAP HANA. 

The repository is the source control for all your development work on SAP HANA. You can add objects to the 

repository, update the objects, publish the objects, and compile these design-time objects into runtime objects. 

The repository supports the following: 

● Version Control 

● Sharing of objects between multiple developers 

● Transport 

The repository manages all development objects. You can browse the repository for a specific system with the 

SAP HANA Repositories view. 



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Packages 

Within the repository, development objects are managed as files within packages. Packages enable you to: 

● Create namespaces, so you can uniquely identify development objects. 

● Group objects that logically belong together. 

● Provide containers for your objects so you can easily insert relevant objects into delivery units and transport 

them. 

● Assign permissions at the package level. 

You might create a top-level package for your company, and then a subpackage for each project, and then 

subpackages for parts of your project, for example, a subpackage for your HTML files, another for server-side 

JavaScript files, and so forth. 

Workspaces 

When working with development objects, you need to retrieve them from the repository, work on them on your 

workstation, and then return them to the repository. To make this simpler, the SAP HANA studio enables you to 

create a repository workspace, which establishes a link between two locations: 

● The repository of the SAP HANA system where you wish to maintain the development object files of your 

projects (in the form of a package hierarchy). 

● A directory/folder on your workstation where you checkout these project files while you are working on them. 

Working with Objects 

When creating development objects, the following is the workflow: 

1. Create a project. 

2. Share the project to associate it with a workspace, and thus a specific SAP HANA system. Shared projects, 

once they are activated, are available for import by other members of the application-development team. 

3. Create a new object file within the project, and save it to your workstation. Depending on the extension of the 

file you create, you may use a dedicated editor for that type of object, for example, a JavaScript editor 

for .xsjs files. 

4. Commit the file. 

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Committing the file saves it in the repository, but the object is inactive and cannot be run, and only you can 

see it. 

5. Activate the file. 

Activating a file does the following: 

○ Publishes the file so others can see it. 

○ Adds the previously active version of the file to the history. The repository maintains a history of changes 

to the file. 

○ Validates the file and compiles it or exposes it as a runtime object. 

The design-time object is now active. 

Related Links 

Setting up Your Application [page 34] 

In SAP HANA Extended Application Services (SAP HANA XS), the design-time artifacts that make up your 

application are stored in the repository like files in a file system. You first choose a root folder for your 

application-development activities, and within this folder you create additional subfolders to organize the 

applications and the application content according to your own requirements. 

3.4 SAP HANA Studio 

The SAP HANA studio is an Eclipse-based development and administration tool for working with SAP HANA, 

including creating projects, creating development objects, and deploying them to SAP HANA. As a developer, you 

may want to also perform some administrative tasks, such as configuring and monitoring the system. 

There are several key Eclipse perspectives that you will use while developing: 

● Modeler: Used for creating various types of views and analytical privileges. 

● SAP HANA Development: Used for programming applications, that is, creating development objects that 

access or update the data models, such as server-side JavaScript or HTML files. 

● Debug: Used to debug code, such as server-side JavaScript or SQLScript. 

● Administration: Used to monitor the system and change settings. 

To open a perspective, go to Window Open Perspective , or select on the toolbar. 

3.4.1 Modeler Perspective 

The Modeler perspective is used to define your analytic model by creating various types of views. 



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The perspective contains the following main areas: 

● Navigator View: A view of the database objects, that is, those objects you create from the Modeler 

perspective. 

● Quick Launch Area: A collection of shortcuts for performing the most common modeling tasks. If you close 

the Quick Launch tab, you can reopen it by selecting Help Quick Launch . 

Navigator View 

The Navigator view shows a view of the database objects in SAP HANA, both those that have been activated and 

those objects you created and have not activated yet. 

The view is divided into the following main sections: 

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● Security: Contains the roles and users defined for this system. 

● Catalog: Contains the database objects that have been activated. The objects are divided into schemas, which 

is a way to organize activated database objects. 

● Content: Contains design-time database objects, both those that have been activated and those not activated. 

If you want to see other development objects, use the SAP HANA Repositories view. 

Related Links 

SAP HANA Repositories View [page 26] 

3.4.2 SAP HANA Development Perspective 

The SAP HANA Development perspective is where you will do most of your programming work, creating projects, 

associating them to SAP HANA systems, creating development objects, and deploying them. 



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The perspective contains the following main areas: 

● Development Objects: Several views for browsing your development objects: the objects on your workstation, 

and the objects in the repository of the SAP HANA system you are working with. 

● Editors: Specialized editors for working with different types of development objects. 

SAP HANA Repositories View 

The SAP HANA Repositories view enables you to browse the repository of a specific SAP HANA system, viewing 

the package hierarchy and to download files to your workstation. 

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The view essentially is a list of repository workspaces that you have created for developing on various systems. 

Generally, you create a workspace, check out files from the repository, and then do most of your development 

work in the Project Explorer. 

If you are creating a project from scratch, you do not need anything from this view, except to see the hierarchy of 

the repository. You create the project in the Project Explorer. 

Project Explorer View 

The Project Explorer is the standard Project Explorer view in Eclipse, which shows you the development files 

located on your workstation. 

Here you can create files, edit files, and deploy them to the repository. 

Working with the Repository 

To work with the repository, you need to either: 

● Share your project with the repository via a workspace. Sharing a project associates it with a SAP HANA 

system, so that files within the project can be added to the repository on that system. 

● Check out an existing package in the repository from a workspace. This creates copies on your workstation of 

the package, its subpackages and their objects. 

Team Menu 

You can interact with the repository by right-clicking on a file or project (in the Project Explorer view) or package 

(in the SAP HANA Repositories view), and selecting an option from the Team menu. 



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You can perform the following on a file, folder or project in the Project Explorer view, that is, development objects 

that you are working on and located on your workstation: 

Table 5: Repository Actions in Project Explorer (project, folder, or file) 

Action Description 

Commit 

Saves the object to the repository. 

The object (or changes to the object) are only visible to you. There is no versioning of 

committed objects; the repository stores only the latest committed changes. 

Activate Makes the development object active, and does the following: 

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● Publishes the object so it is visible to others. 

● Compiles the object into runtime objects. 

● Deploys the runtime object. 




● Creates a new version of the design-time object. 

Check Simulates activation of the object in order to check if the object is valid and can be 

activated. 

Checkout Retrieves the latest version of the object from the repository. 

Revert Removes all your committed changes (inactive object) with the latest version of the object 

Share/Unshare 

(project only) 

that was activated. 

Associates a project with a specific SAP HANA system, so that files within the project can 

be added and updated on the repository on that system. For more information, see Using 

SAP HANA Projects [page 37]. 

The following options are available for files only. 

Show Local History Shows a history of all versions of your object saved on your workstation. This is the Eclipse 

Show History 

local history feature. 

Shows a history of all the versions of the object that were activated in the repository. 

Currently, you can only view a list of versions. 

You can perform the following on a package and file in the SAP HANA Repositories view: 

Table 6: Repository Actions in SAP HANA Repositories (package or file) 


Checkout (package 

only) 

Checkout and 

Import Projects 

(package only) 

Retrieves the latest version of the objects from the repository in this package and its 

subpackages. 

Retrieves the latest version of the objects from the repository in this package, and imports 

a project into the SAP HANA studio. For more information, see Using SAP HANA Projects 

[page 37]. 



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Show History (file 

only) 

Status of Development Objects 

Shows a history of all the versions of the object that were activated in the repository. 

Each object displayed in your project within the Project Explorer view is shown with an icon that indicates its 

status. 

Table 7: Status of Development Objects 

Icon Description 

The file is not committed. You made a change to the file and saved it to your workstation, but have 

not yet committed the changes to the repository. 

The file is committed. 

The file is activated. 

3.4.3 Debug Perspective 

The Debug perspective in the SAP HANA studio is the standard Eclipse Debug perspective, enabling you to start 

debug sessions, create breakpoints and watch variables. 

In the SAP HANA studio, the debug tools have been enhanced to let you also debug SAP HANA code, both serverside 

JavaScript (.xsjs files) and SQLScript code (.procedure files). The following shows the tools available in 

the Debug perspective and how it is organized: 

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● Debug Session: The debug sessions that have been started 

● Watch: Breakpoints and variables to watch 

● Code: Code files that you have opened 

Related Links 

Debugging JavaScript [page 221] 

SAP HANA studio enables you to debug XS JavaScript files, including setting breakpoints and inspecting 

variables. 

Debugging SQLScript [page 161] 

The SAP HANA SQLScript debugger allows you to debug and analyze procedures. In a debug session, your 

procedures will be executed in a serial mode, not in parallel (not-optimized). This allows you to test the 

correctness of the procedure logic and is not for evaluating the performance. 

3.4.4 Administration Console Perspective 

The Administration Console perspective enables you to configure the SAP HANA server so that you can do your 

development work. For example, when debugging, the debug port must be opened and debugging enabled, which 

is done by setting configuration parameters within the administration console. 

The Administration Console perspective displays the Navigator view, for adding or selecting systems, and the 

administration console, where you can monitor and configure the system. Configuration parameters can viewed 

and changed from the Configuration tab. 

Note: You may need additional permissions to work with the administration console. 



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If the console is closed, you can open it by clicking the Administration icon in the Navigator view. 

3.5 Getting Started 

Before starting development work in the SAP HANA studio, make sure to have the following: 

● An installation of the SAP HANA studio on your workstation. 

● A live SAP HANA system to which to connect. 

● A user on the SAP HANA server that has at least the following roles or their equivalent: 

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○ MODELING 

○ CONTENT_ADMIN 

3.5.1 Adding a System 

To develop applications, you must first make a connection from your SAP HANA studio to an SAP HANA system. 

1. In the Navigator view, right-click anywhere in the view and select Add System. 

2. In the System window, enter the host name, instance number, and a description for the SAP HANA system 

you want to add. 

3. Select Next. 

4. Enter a user name and password, and select Finish. 

The Navigator view includes a new top-level node for the system. You can now create a repository workspace for 

this system so you can start to develop objects to run in it. 

Related Links 








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4 Setting up Your Application 


application are stored in the repository like files in a file system. You first choose a root folder for your applicationdevelopment 

activities, and within this folder you create additional subfolders to organize the applications and the 

application content according to your own requirements. 





As part of the application-development process, you typically need to perform the tasks described in the following 

list. Each of the tasks in more detail is described in its own section: 

1. Set up delivery units. 

To create and manage delivery units, you must set the identity of the vendor with whom the delivery units are 

associated. To avoid conflicts with applications from SAP or other providers, we recommend that you name 

the root application-development folder for your company using the DNS name of your company. For 

example, you could use the name acme.com.hr.newHires for the root folder for a new application 

managing new hires in a company called acme. 

2. Set up SAP HANA projects. 

In SAP HANA, projects enable you to group together all the artifacts you need for a specific part of the 

application-development environment. To start the application-development work flow, you first create a local 

workspace in the SAP HANA Development perspective, which creates a directory structure to store files on 

your PC; the workspace you create enables you to synchronize changes in local files with changes in the 

repository. Then you can use the SAP HANA studio to create a project to manage the development activities 

for the new application. 

3. Maintain repository packages. 

To perform the high-level tasks that typically occur during the process of maintaining repository packages, 

you need to be familiar with the concepts of packages and package hierarchies, which you use to manage the 

artifacts in your applications. 

4. Maintain application descriptors. 

34 

The framework defined by the application descriptors includes the root point in the package hierarchy where 

content is to be served to client requests. The framework also defines if the application is permitted to expose 

data to client requests, what kind of access to the data is allowed, and what if any privileges are required to 

perform actions on packages and package content. 

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Setting up Your Application

4.1 Setting up Delivery Units 

A delivery unit is a collection of packages that are to be transported together. You assign all the packages 

belonging to your application to the same delivery unit to ensure that they are transported consistently together 

within your system landscape. Each delivery unit has a unique identity. 

The identity of a delivery unit consists of two parts: a vendor name and a delivery-unit name. The combined ID 

ensures that delivery units from different vendors are easy to distinguish and follows a pattern that SAP uses for 

all kinds of software components. 

To create and manage delivery units you first need to maintain the identity of the vendor, with whom the delivery 

units are associated, and in whose namespace the packages that make up the delivery unit are stored. As part of 

the vendor ID maintenance process, you must perform the following tasks: 

1. Understand delivery units 

You must be familiar with the conventions that exist for delivery-unit names and understand the phases of the 

delivery-unit lifecycle. 

2. Maintain details of the vendor ID associated with a delivery unit. 

Delivery units are located in the namespace associated with the vendor who creates them and who manages 

the delivery-unit's lifecycle. 

3. Create a delivery unit. 

Related Links 

Maintaining the Delivery-Unit Vendor ID [page 35] 

In SAP HANA, the vendor ID is used primarily to define the identity of the company developing a software 

component that they plan to ship for use with SAP HANA. If you want to create a delivery unit, it is a 

prerequisite to maintain a vendor ID in your system. 

Creating a Delivery Unit [page 36] 

A delivery unit is a group of transportable objects used for content delivery. You can use a delivery unit to 

transport the design-time objects that are stored in the SAP HANA repository between two systems, for 

example, from a development system to a consolidation system. 

4.1.1 Maintaining the Delivery-Unit Vendor ID 


component that they plan to ship for use with SAP HANA. If you want to create a delivery unit, it is a prerequisite 

to maintain a vendor ID in your system. 

Before creating your first own delivery unit you must set the identity of the vendor in the development system's 

configuration. To maintain details of the delivery-unit vendor ID, perform the following steps: 

1. Start the SAP HANA studio. 

2. Switch to the Administration Console perspective. 

In the SAP HANA studio Navigator view choose Administration . Alternatively, use the menu path: Window > 

Open Perspective > Administration Console . 

3. Display configuration details for the SAP HANA instance; choose the Configuration tab page. 

4. Maintain details of the vendor ID. 

In the Configuration tab page, perform the following steps: 


Setting up Your Application 

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a) Locate indexserver.ini in the list of configuration files displayed in the Name column. 

b) Expand the indexserver.ini entry. 

c) Expand the repository entry. 

d) Edit the content_vendor parameter. 

e) Double-click content_vendor and enter the name of your vendor. Note that guidelines and conventions 

exist for vendor names. 

f) Save your changes. 

Note: We recommend that you use your DNS name to set the vendor ID, for example, acme.com. 

4.1.2 SAP HANA Delivery Unit Naming Conventions 

In SAP HANA, conventions and guidelines exist for the naming of delivery units (DU). The delivery unit is the 

vehicle that lifecycle management (LCM) uses to ship one or more software components from SAP (or a partner) 

to a customer. The DU is also the container you use to transport application content in your system landscape. 

If you are creating a delivery unit, you must adhere to the following naming conventions 

● The name of a delivery unit must contain only capital letters (A-Z), digits (0-9), and underscores (_) 

● You cannot use an underscore (_) as the first character of a delivery-unit name. 

Note: The naming conventions for packages in a delivery unit differ from the naming conventions that 

apply to the delivery unit itself. For example, the maximum length of a package name is not restricted to 

30 characters; it must be less than 190 characters (including the namespace hierarchy). 

4.1.3 Creating a Delivery Unit 

A delivery unit is a group of transportable objects used for content delivery. You can use a delivery unit to 

transport the design-time objects that are stored in the SAP HANA repository between two systems, for example, 

from a development system to a consolidation system. 

In the SAP HANA studio, you can create a delivery unit in the Quick Launch view of the Modeler perspective : 

Note: You cannot create a delivery unit unless you have already defined the delivery unit's vendor ID; the 

vendor ID defines the namespace in which the new delivery unit resides. 

To create a new delivery unit, perform the following steps: 

1. In the SAP HANA studio, start the Modeler perspective. 

2. In the Setup screen area of the Quick Launch tab, choose Delivery Units.... 

3. Create a new delivery unit. 

In the Delivery Units dialog, choose Create... 

4. Maintain delivery unit details. 

36 

a) Enter a name for the new delivery unit. 

The delivery unit Name is mandatory. 

b) Fill in the other information as required: 

Note the following points when entering information: 

○ The name of the Vendor is set to the vendor ID that is specified in the system configuration, for 

example, acme.com. 

○ The Responsible text box enables you to specify the name of the person responsible for managing the 

delivery unit. 

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Related Links 

○ In the text boxes Version, Support Package Version, and Patch Version enter integer values only; the 

combined values define the version of the delivery unit that is currently being developed. For 

example, enter Version = 1, Support Package Version = 3, and Patch Version = 17 to specify that the 

current version of your delivery unit is 1.3.17. The version number is transported to other systems 

with every DU transport. 

Note: The numbers you enter here refer to the application component that you are 

developing; the numbers do not refer to the patch or service-pack level deployed on the SAP 

HANA server. 

○ The PPMS ID is the product ID used by the SAP Product and Production Management System 

(PPMS). 

Note: Customers and partners should leave the PPMS ID text box empty. 

Maintaining the Delivery-Unit Vendor ID [page 35] 


component that they plan to ship for use with SAP HANA. If you want to create a delivery unit, it is a 

prerequisite to maintain a vendor ID in your system. 

SAP HANA Delivery Unit Naming Conventions [page 36] 


vehicle that lifecycle management (LCM) uses to ship one or more software components from SAP (or a 

partner) to a customer. The DU is also the container you use to transport application content in your system 

landscape. 

4.2 Using SAP HANA Projects 

Projects group together all the artifacts you need for a specific part of the application-development environment. 

Before you can start the application-development workflow, you must create a project, which you use to group 

together all your application-related artifacts. However, before you create a project, you must create a repository 

workspace, which enables you to synchronize changes in local files with changes in the repository. As part of the 

project-creation process, you perform the following tasks: 

1. Create a development workspace. 

The workspace is the link between the SAP HANA repository and your local filesystem, where you work on 

project-related objects. 

2. Create a project. 

Create a new project for a particular application or package; you can use the project to collect in a convenient 

place all your application-related artifacts. 

3. Share a project. 

Sharing a project enables you to ensure that changes you make to project-related files are visible to other 

team members and applications. Shared projects are available for import by other members of the 

application-development team. 



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4. Import a project. 

Import a project (and its associated artifacts) that has been shared by another member of the applicationdevelopment 

team. 

Related Links 

Create a Development Workspace [page 39] 

A workspace is a local directory that you map to all (or part) of a package hierarchy in the SAP HANA 

repository. When you check out a package from the repository, SAP HANA copies the contents of the package 

hierarchy to your workspace, where you can work on the files.. 

Create a New Project [page 40] 

Before you can start the application-development workflow, you must create a project, which you use to group 

all your application-related artifacts. 

Share a Project [page 40] 

Before you can start working on files associated with a new project, you must share the project; sharing a 

project enables you to track and synchronize local changes with the repository. 

Import a Project [page 41] 

Before you can start the application-development workflow, you must either create a new project and share it 

(with the repository), or import a shared project from the repository into your workspace. Importing a project 

enables you to track and synchronize local changes with the colleagues working on the objects in the imported 

project. 

4.2.1 SAP HANA Repository: Workspaces 

The place where you work on project-related objects is called a repository workspace. A workspace is an 

environment that maps a local directory to all (or part) of a package hierarchy in the SAP HANA repository. 

In SAP HANA studio, the repository tools enable you to view and browse the entire hierarchy of design-time 

objects stored in the repository. However, when you checkout a package from the repository, SAP HANA copies 

the contents of the package hierarchy to your workspace, where you can work on the files in your local file system. 

Note: Before you can create a workspace you must maintain connection information in the SAP HANA 

database user store. 

To start development work with SAP HANA studio, for example, to checkout the contents of a package, you must 

create a repository workspace. The workspace contains a system folder with metadata and package folders for 

the repository content. The file-system folders and their subfolders reflect the package hierarchy in the 

repository; the repository client ensures that changes are synchronized. You can use SAP HANA studio to 

perform the following workspace-related actions in the repository: 

● Checkout folders and files from the repository 

● Commit changes to the repository 

● Activate the committed changes 

● Revert inactive changes to the previously saved version 

The commit operation detects all changes in packages that you configure SAP HANA studio tool to track and 

writes the detected changes back to the repository. The repository client tools also support synchronization with 

changes on the server, including conflict detection and merging of change. All workspace-related repository 

actions are available as context-sensitive menu options in SAP HANA studio. For example, if you right click a 

repository object at the top of the package hierarchy in the Project Explorer in SAP HANA studio, you can commit 

and activate all changed objects within the selected hierarchy. 

38 

Note: If you create a new project using SAP HANA studio, you can assign the new project to an existing 

workspace. 

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4.2.2 Creating a Repository Workspace 

A workspace is a local directory that you map to all (or part) of a package hierarchy in the SAP HANA repository. 

When you check out a package from the repository, SAP HANA copies the contents of the package hierarchy to 

your workspace, where you can work on the files.. 

Before you can start work on the development of the application, you need to set up a workspace, where you store 

checked-out copies of your application’s source-code files. 

To create a new workspace in the SAP HANA studio, perform the following steps: 

1. Open the SAP HANA studio. 

2. Open the SAP HANA Development perspective. 

3. Choose the SAP HANA Repositories view. 

4. Choose Create Workspace… 

The Create Workspace… button is located in the top right-hand corner of the SAP HANA Repositories view. 

5. Specify the workspace details. In the Create New Repository Workspace dialog, enter the following 

information and choose Finish: 

a) Specify the SAP HANA system, for which you want to create a new workspace. 

b) Enter a workspace name, for example the name of the SAP HANA system where the repository is located. 

To avoid the potential for confusion, it is recommended to associate one workspace with one repository. 

c) Specify where the workspace root directory should be located on your local file system, for example: C: 

\users\username\workspaces 

The new workspace is displayed in the SAP HANA Repositories view. 

Note: Although the packages and objects in the chosen repository are visible in the SAP HANA 

Repositories view, you cannot open or work on the objects here. To work on objects, you must create 

a project and use the Project Explorer view. 

4.2.3 SAP HANA Studio Projects 

Before you can start the application-development workflow, you must create a project, which you use to group all 

your application-related artifacts. 

Projects group together all the artifacts you need for a specific part of the application-development environment. 

A basic project contains folders and files. More advanced projects are used for builds, version management, 

sharing, and the organization and maintenance of resources. 

Projects enable multiple people to work on the same files at the same time. By committing project-related files to 

the repository and activating them, you enable team members to see the latest changes. 

You can share and unshare projects. Sharing a project associates it with a particular package in the repository 

linked to a particular workspace. The act of sharing the project sets up a link between the workspace and the 

repository and enables you to track and synchronize local changes with the versions of the objects stored in the 

repository. When a project is shared, it becomes available to other people with authorization to access to the 

repository, for example, colleagues in an application-development team. Team members can import a shared 

project and see and work on the same files as the creator of the project. 

Note: Always unshare a project before deleting it. 



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In the SAP HANA studio you can create a project at any package level, which enables a fine level of control of the 

artifacts that may (or may not) be exposed by sharing the project. 

4.2.4 Creating a Project for SAP HANA XS 

Before you can start the application-development workflow, you must create a project, which you use to group all 

your application-related artifacts. 

Projects group together all the artifacts you need for a specific part of your application-development environment. 

Depending on the type of project you are working on, the project can include build tools, too. A basic project 

contains folders and files. More advanced projects are used for builds, version management, sharing, and the 

organization and maintenance of resources. 

To create a new project in the SAP HANA studio, perform the following steps: 



3. Choose the Project Explorer view. 

4. Right-click the white space in the Project Explorer view and choose New > Project… in the popup menu. 

The type of project you create determines the details you have to provide in the New Project dialog that 

appears. 

a) Enter a project name that describes what the project is about, for example: XS_JavaScript, XS_OData 

or XS_SAPUI5. 

b) Click Finish to create the new project. 

The new project is displayed in the Project Explorer view. 

Note: The contents of the project depend on the type of project you create. For example, a general 

project is empty immediately after creation; a JavaScript project contains all the resource files 

associated with a JavaScript project, such as libraries and build-environment artifacts. 

4.2.5 Sharing a Project for SAP HANA XS 

Before you can start working on files associated with a new project, you must share the project; sharing a project 

enables you to track and synchronize local changes with the repository. 

When you share a project, you set up a connection to the SAP HANA repository associated with a particular SAP 

HANA instance. Sharing the project enables you to ensure that changes you make to project-related files are 

visible to other team members and applications. Other developers can import a shared project and work on the 

same files. 

Note: Use the Project Explorer view in the SAP HANA studio to check if a project is shared. In addition to 

the project name, a shared project displays the SAP HANA system ID of the repository where the shared 

artifacts are located, a SAP HANA user name, and the path to the repository package to which the shared 

project is assigned, for example. "XSJS_myproject [SID (dbusername, 

'sap.hana.xs.app1')]. 

To share a project in the SAP HANA studio, perform the following steps: 

1. Open the SAP HANA studio 


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3. Open the Project Explorer view. 

4. Share the project 

Right-click the project you want to share and choose Team > Share Project… in the pop-up menu. 

5. Select the repository type. 

The Share Project dialog displays a list of all available repository types; choose SAP HANA Repository and 

choose Next. 

6. Select the repository workspace where the project should be located. 

7. Specify the package that you want to associate the shared project with. 

The Share Project dialog displays the suggested location for the shared project in the New Project location 

screen area. The default location is the name of the workspace with the name of the project you want to 

share. Choose Browse... to locate the package you want to associate the shared project with. The selected 

package is displayed in the Path to package text box. 

Note: The Keep project folder option appends the name of the project you are sharing to the name of 

the workspace in which you are sharing the project and creates a new package with the name of the 

shared project under the workspace location displayed. Use this option only if you want to create 

multiple projects for a selected package, for example, if you are creating a root project in your root 

application package. 

8. Click Finish to complete the project-sharing procedure. 

9. Add new files as required 

At this point you can start adding project-specific files to the shared project. These artifacts can then be 

committed to the repository, where they reside as inactive objects until they are activated, for example, using 

the Team Activate option in the context-sensitive menus available in the Project Navigator view. 

Note: The Project Explorer view decorates the file icons to indicate the current state of the repository 

files, for example: local (not yet committed), committed (inactive), and active (available for use by 

others). 

10. Make the project available for import, for example, so that others can join it and make changes to project 

content. 

The project-sharing procedure creates some artifacts (for example, the .project file) that must be 

committed to the repository and activated so that other team members can import the project more easily 

into their workspace. The .project file is used in several dialogs to populate the list of available projects. 

Related Links 

Note: Use the SAP HANA Repositories view to import projects (and checkout project content). 

Importing a Project in SAP HANA XS [page 41] 




project. 

4.2.6 Importing a Project in SAP HANA XS 





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project. 

To import an existing project from the repository into your workspace, perform the following steps. 

1. Open the SAP HANA studio 


3. Choose the HANA Repositories view. 

4. Right-click the package where the project you want to import is located and choose Checkout and Import 

Projects... in the popup menu. 

Projects can be assigned to a package at any level of the package hierarchy. If you know where the project is 

located, browse to the package first before choosing the Checkout and Import Projects... option. This reduces 

the amount of files to checkout and download to your local file system. 

Note: The existence of a .project file in a package identifies the package as being associated with a 

project. 

The SAP HANA studio checks out the content of the selected package and displays any projects it finds in the 

Projects screen area. 

5. Select the projects to import. 

If multiple projects are available for import, select the projects you want to import. 

6. Choose Finish to import the selected projects. 

You can add the imported project to your Working Sets. 

Note: A working set is a concept similar to favorites in a Web browser, which contain the objects you 

work on most frequently. 

4.3 Maintaining Repository Packages 

All content delivered as part of the application you develop for SAP HANA is stored in packages in the SAP HANA 

repository. The packages are arranged in a hierarchy that you define to help make the process of maintaining the 

packages transparent and logical. 

To perform the high-level tasks that typically occur during the process of maintaining repository packages, you 

need to be familiar with the concepts of packages and package hierarchy that create and maintain the artifacts for 

your applications. You also need to know about the privileges the application developers will need to have access 

to (and perform operations on) the packages. 

Note: You can also create and delete packages in the Project Explorer, for example, by creating or deleting 

folders in shared projects and committing and activating these changes. However, to maintain advanced 

package properties (for example, privileges, component, the package maintainer, and so on) you must 

use the Modeling perspective in the SAP HANA studio.. 

As part of the process of maintaining your application packages, you typically perform the following tasks: 

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1. Create a package 

Packages are necessary to group logically distinct artifacts together in one object location that is easy to 

transport. 

2. Define the package hierarchy 

The package hierarchy is essential for ease of maintenance as well as the configuration of access to packages 

and the privileges that are required to perform actions on the packages. 

3. Define package privileges 

You can set package authorizations for a specific user or for a role. Authorizations that are assigned to a 

repository package are implicitly assigned to all sub-packages, too. 

Related Links 

Creating a package [page 46] 

In SAP HANA, a package contains a selection of repository objects. You assemble a collection of packages into 

a delivery unit, which you can use to transport the repository objects between SAP HANA systems. 

Defining the package hierarchy [page 47] 

Packages belonging to an application-development delivery unit (DU) should be organized in a clear 

hierarchical structure under a single root package representing the vendor, for example, acme. 

Defining package privileges [page 46] 

In the SAP HANA repository, you can set package authorizations for a specific user or for a role. 

Authorizations that are assigned to a repository package are implicitly assigned to all sub-packages, too. You 

can also specify if the assigned user authorizations can be passed on to other users. 

4.3.1 SAP HANA Repository Packages and Namespaces 

In SAP HANA, a package typically consists of a collection of repository objects, which can be transported between 

systems. Multiple packages can be combined in a delivery unit (DU). 

A SAP HANA package specifies a namespace in which the repository objects exist. Every repository object is 

assigned to a package, and each package must be assigned to a specific delivery unit. In the repository, each 

object is uniquely identified by a combination of the following information: 

● Package name 

● Object name 

● Object type 

Note: Multiple objects of the same type can have the same object name if they belong to different 

packages. 

Before you start the package development process, consider the following important points: 

● Package hierarchy 

Each vendor uses a dedicated namespace, and the package hierarchy you create enables you to store the 

various elements of an application in a logical order that is easy to navigate. 

● Package type 

Packages can be structural or non-structural; some packages contain content; other packages contain only 

other (sub)packages. 

● Package naming conventions 

There are recommendations and restrictions regarding package names, for example, the name's maximum 

length and what if any characters must not be used. 



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Package Hierarchy 

You can create a package hierarchy, for example, by establishing a parent-child type relationship between 

packages. The assignment of packages to delivery units is independent of the package hierarchy; packages in a 

parent-child relationship can belong to different delivery units. SAP recommends that you assign to one specific 

delivery unit all packages that are part of a particular project or project area. 

The package hierarchy for a new project typically includes sub-packages, for example, to isolate the data model 

from the business logic. Although there are no package interfaces to enforce visibility of objects across packages, 

this separation of logical layers of development is still a recommended best practice. 

Note: You can only assign one project per package; this is important to remember if you have a mixture of 

design-time objects that need to be used in multiple projects, for example: server-side JavaScript (XSJS), 

SAPUI5, and a general project (for procedures). 

The following simple example shows a package structure containing tutorials for the use of a new application: 

sap 

\ 

hana 

\ 

app1 

\ 

code 

demos 

docs 

\ 

tutorials 

manuals 

help 

All content delivered by SAP should be in a sub-package of "sap". Partners and customers should choose their 

own root package to reflect their own name (for example, the domain name associated with the company) and 

must not create packages or objects under the "sap" root structural package. This rules ensures that customer or 

partner created content will not be overwritten by an SAP update or patch. 

Note: SAP reserves the right to deliver without notification changes in packages and models below the 

"sap" root structural package. 

There are no system mechanisms for enforcing the package hierarchy. The "sap" root structural package is not 

automatically protected. However, by default you cannot change the content of packages that did not originate in 

the system. In addition, an authorization concept exists, which enables you to control who can change what inside 

packages. 

Package Types 

SAP HANA Application Services provide or allow the following package types: 

● Structural 

44 

Package only contains sub-packages; it cannot contain repository objects. 

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● Non-Structural 

Package contains both repository objects and subpackages. 

The following packages are delivered by default with the repository: 

● sap 

Transportable package reserved for content delivered by SAP. Partners and customers must not use the sap 

package; they must create and use their own root package to avoid conflicts with software delivered by SAP, 

for example when SAP updates or overwrites the sap package structure during an update or patch process. 

● system-local 

Non-transportable, structural packages (and subpackages). Content in this package (and any subpackages) 

is considered system local and cannot be transported. This is similar to the concept of the $tmp development 

class in SAP NetWeaver ABAP. 

● system-local.generated 

Transportable, structural packages for generated content, that is; content not created by manual user 

interaction 

● system-local.private 

Transportable, structural sub-packages containing objects that belong to individual users and are named 

after these users (and are exclusively reserved for these users). For example, system- 

local.private. 

Package Naming Conventions 

The following rules apply to package names: 

● Permitted characters 

Lower/upper case letters (aA-zZ), digits (0-9), hyphens (-), and dots (.) are permitted in package names. 

Dots in a package name define a logical hierarchy. For example, "a.b.c" specifies a package "a" that contains 

sub-package "b", which in turn contains sub-package "c". 

● Forbidden characters 

A package name must not start with either a dot (.) or a hyphen (-) and cannot contain two or more 

consecutive dots (..). 

● Package name length 

The maximum permitted length of a package name is 190 characters. To avoid problems, we recommend you 

restrict the length of package names to well under the 190-character limit. 

● Package namespace length 



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The name of the complete package namespace hierarchy (for example, "aa.bb.cc.zz" including dots) must not 

be more than 190 characters long. To avoid problems, we recommend you restrict the length of the package 

namespace to well under the 190-character limit. 

4.3.2 Defining Repository Package Privileges 

In the SAP HANA repository, you can set package authorizations for a specific user or for a role. Authorizations 

that are assigned to a repository package are implicitly assigned to all sub-packages, too. You can also specify if 

the assigned user authorizations can be passed on to other users. 

To set user (or role) authorizations for repository packages, perform the following steps: 

1. In the SAP HANA studio, open the Navigator view of the Modeler perspective. 

2. In the Navigator view, expand the Security Roles/Users node for the system hosting the repository that 

contains the packages you want to grant access to. 

You can also define roles via source files; roles defined in this way can be assigned to a delivery unit and 

transported to other systems. 

3. Double click the user (or role) to whom you want to assign authorizations. 

4. Open the Package Privileges tab page. 

5. Choose [+] to add one or more packages. Press and hold the Ctrl key to select multiple packages. 

6. In the Select Repository Package dialog, use all or part of the package name to locate the repository package 

that you want to authorize access to. 

7. Select one or more repository packages that you want to authorize access to; the selected packages appear 

in the Package Privileges tab page. 

8. Select the packages to which you want authorize access and, in the Privileges for screen page, check the 

required privileges, for example: 

a) REPO.READ 

Read access to the selected package and design-time objects (both native and imported) 

b) REPO.EDIT_NATIVE_OBJECTS 

Authorization to modify design-time objects in packages originating in the system the user is working in 

c) REPO.ACTIVATE_NATIVE_OBJECTS 

Authorization to activate/reactivate design-time objects in packages originating in the system the user is 

working in 

d) REPO.MAINTAIN_NATIVE_PACKAGES 

Authorization to update or delete native packages, or create sub-packages of packages originating in the 

system in which the user is working 

4.3.3 Creating a Package 

In SAP HANA, a package contains a selection of repository objects. You assemble a collection of packages into a 

delivery unit, which you can use to transport the repository objects between SAP HANA systems. 

You can use packages to manage the various elements of your application development project. To create a 

project, perform the following steps: 


2. In the New screen area of the Quick Launch tab page, choose Package and choose Create.... 

3. Maintain the package details. 

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In the New Package dialog, enter information in the following fields: 

a) Enter a name for the new package. 

The package Name is mandatory. 

b) Fill in the other optional information as required: 

Related Links 

Use the Delivery Unit drop-down list to assign the new package to a delivery unit. 

Choose Translation if you intend to have the package content localized. You must maintain the translation 

details. 

SAP HANA Delivery-Unit Translation Details [page 349] 

The SAP HANA repository includes features for translating package-related metadata texts. If you plan to 

translate the contents of the new delivery unit you create, you must maintain translation details. 

4.3.4 Defining a Package Hierarchy 

Packages belonging to an application-development delivery unit (DU) should be organized in a clear hierarchical 

structure under a single root package representing the vendor, for example, acme. 

The package hierarchy for a new project might include sub-packages, for example, to isolate the data model from 

the business logic. Although there are no package interfaces to enforce visibility of objects across packages, this 

separation of logical layers of development is still a recommended best practice. 

Note: You can only assign one project per package; this is important to remember if you have a mixture of 

design-time objects that need to be used in multiple projects, for example: server-side JavaScript (XSJS), 

SAPUI5, and a general project (for procedures). 

The following simple example shows a package structure containing tutorials for the use of a new application: 

acme 

\ 

hana 

\ 

app1 

\ 

docs 

\ 

tutorials 

● Package hierarchy 

Each vendor uses a dedicated namespace, for example, acme. 

● Package type 

Note: Do not use the namespace sap to build your application hierarchy. The namespace sap is 

reserved for use by SAP; packages created in the sap namespace are overwritten by system updates. 

Some packages contain content; other packages contain only other (sub)packages. Packages can also 

contain both objects and (sub)packages. 

● Package naming conventions 

There are recommendations and restrictions regarding package names. 



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To set up a package hierarchy in the SAP HANA repository, perform the following steps: 

1. Create a new root package. 

Open the Modeler perspective and perform the following steps: 

a) Choose New > Package . 

b) Choose Create... 

2. Maintain the package details. 

In the Create Package dialog, perform the following steps: 

a) Enter the name of the package (mandatory). 

Guidelines and conventions apply to package names. 

b) Enter a package description (optional). 

c) Specify the delivery unit that the package is assigned to. 

You can add additional packages to a delivery unit at a later point in time, too. 

d) Specify a language for the package content. 

e) Assign responsibility of the package to a specific user (optional). 

By default, the responsible user for a new package is the database user connected to the SAP HANA 

repository in the current SAP HANA studio session. 

f) Maintain translation details. 

If you plan to have the content translated, you need to maintain the translation details; this is covered in 

another topic. 

3. Create a new subpackage. 

In the Navigator view of the Modeler perspective, perform the following steps: 

a) Right-click the package to which you want to add a new subpackage. 

b) In the pop-up menu, choose New > Package... 

4. Maintain the subpackage details. 

In the Create Package dialog, perform the following steps: 

a) Enter the name of the subpackage (mandatory). 

Guidelines and conventions apply to package names. 

b) Enter a description for the new subpackage (optional). 

c) Specify the delivery unit that the subpackage is assigned to. 

You can add additional packages to a delivery unit at a later point in time, too. 

d) Specify a language for the subpackage content. 

e) Assign responsibility of the subpackage to a specific user (optional). 

By default, the responsible user for a new package is the database user connected to the SAP HANA 

repository in the current SAP HANA studio session. 

f) Maintain translation details. 

Related Links 

If you plan to have the content translated, you need to maintain the translation details; this is covered in 

another topic. 

SAP HANA Delivery Unit Naming Conventions [page 36] 


vehicle that lifecycle management (LCM) uses to ship one or more software components from SAP (or a 

partner) to a customer. The DU is also the container you use to transport application content in your system 

landscape. 

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Maintaining Translation Details [page 349] 

Translation details provide a brief overview of the type and current status of the text objects to be translated, 

for example, by specifying the technical area of the new delivery unit and indicating the current status of 

translation texts. 

4.4 Creating the Application Descriptors 

When you develop and deploy applications in the context of SAP HANA Extended Application Services (SAP 

HANA XS), you must define the application descriptors, which describe the framework in which the application 

runs. The framework defined by the application descriptors includes the root point in the package hierarchy where 

content is to be served to client requests, whether the application is permitted to expose data to client requests, 

what kind of access to the data is allowed, and what if any privileges are required to perform actions on packages 

and package content. 

To perform the high-level tasks that make up the process of defining the application descriptors, you must be 

familiar with the concept of the application descriptor, the application-access file, and if required, the application- 

privileges file. Maintaining the application descriptors involves the following tasks: 

1. Creating the application descriptor file. 

The package that contains the application descriptor file becomes the root path of the resources exposed to 

client requests by the application you develop. 

2. Creating the application-access file. 

The application-access file enables you to specify who or what is authorized to access the content exposed by 

the application package and what content they are allowed to see. 

3. Creating the application-privileges file. (Optional) 

The application-privileges file can be used to define the authorization privileges required for access to an 

application, for example, to start the application or to perform administrative actions on an application. 

Related Links 

Create an application descriptor [page 50] 

Each application that you want to develop and deploy on SAP HANA Extended Application Services (SAP 

HANA XS) must have an application-descriptor file. The application descriptor is the core file that you use to 

describe an application's framework within SAP HANA XS. 

Create an application-access file [page 57] 


the application package and what content they are allowed to see. 

Create an application-privileges file [page 60] 

The application-privileges (.xssprivileges) file can be used to grant authorization levels for an application, 

for example, to start the application or perform administrative actions on an application. 

4.4.1 The SAP HANA XS Application Descriptor 

Each application that you want to develop and deploy on SAP HANA Extended Application Services (SAP HANA 

XS) must have an application descriptor file. The application descriptor is the core file that you use to describe an 

application's framework within SAP HANA XS. 

The package that contains the application descriptor file becomes the root path of the resources exposed to client 

requests by the application you develop. 



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Note: The application-descriptor file has no contents and no name; it only has the file extension “xsapp”, 

for example, .xsapp. For backward compatibility, content is allowed in the .xsapp file but ignored. 

The application descriptor file performs the following operations: 

● Determines the called application 

The application root is determined by the package containing the .xsapp file. If the package sap.test 

contains the file .xsapp, the application will be available under the URL http://:/ 

sap.test/. 

4.4.2 Create an Application Descriptor File 

Each application that you want to develop and deploy on SAP HANA Extended Application Services (SAP HANA 

XS) must have an application-descriptor file. The application descriptor is the core file that you use to describe an 

application's framework within SAP HANA XS. 

The package that contains the application-descriptor file becomes the root path of the resources exposed by the 

application you develop. 

1. Create a root package for your application, for example, helloxsjs. 

2. Create an application descriptor for your application and place it in the root package you created in the 

previous step. 

The application descriptor is the core file that you use to describe an application's availability within SAP 

HANA Extended Application Services. The application-descriptor file has no contents and no name; it only has 

the file extension .xsapp.. 

Note: For backward compatibility, content is allowed in the .xsapp file but ignored. 

3. Save and activate your changes and additions. 

4.4.3 The Application-Access File 

SAP HANA XS enables you to define access to each individual application package that you want to develop and 

deploy. 

The application-access file enables you to specify who or what is authorized to access the content exposed by a 

SAP HANA XS application package and what content they are allowed to see. For example, you use the 

application-access file to specify if authentication is to be used to check access to package content and whether if 

rules are in place for the exposure of target and source URLs. 

The application-access file does not have a name; it only has the file extension .xsaccess. The content of 

the .xsaccess file is formatted according to JSON rules and is associated with the package it belongs to as well 

as any subpackages lower in the package hierarchy. Multiple .xsaccess files are allowed, but only at different 

levels in the package hierarchy. This enables you to specify different application-access rules for individual 

packages and subpackages in the package hierarchy. 

Note: You cannot place two .xsaccess files in the same package. Furthermore, the rules specified in 

a .xsaccess file that is associated with a subpackage take precedence over any rules specified in 

a .xsaccess file associated with any parent package higher up the package hierarchy. 

The application-access file performs the following operations: 

● Data exposure 

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Use the exposed keyword to specify if package content is to be exposed to client requests via HTTP. 

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Note: Exposed package content can include design-time objects, for example, tables and views. 

● Authentication rules 

Use the authentication keyword to enable authorization for the requests in URLs either at the application level 

or for single packages in an application. The following authentication methods are supported: 

○ SAP logon tickets 

SAP logon tickets enable single sign-on across SAP boundaries; SAP logon tickets can also be used as 

authentication for access to third-party applications. 

○ Form-based authentication 

Redirect the logon request to a form to fill in, for example, on a Web page. 

○ Basic (user name and password) 

Log on with a recognized user name and password 

The authentication methods can also be written as an array, for example, to allow applications to support 

multiple authentication methods. The order of the authentication methods in the array should proceed from 

strongest to weakest, for example: 

1. SAP logon ticket 

2. Form-based 

3. Basic authentication 

● Application authorization 

Use the authorization keyword in the .xsaccess file to specify which authorization level is required by a user 

for access to a particular application package. The authorization levels you can choose from are defined in 

the .xsprivileges file, for example, "execute" for basic privileges, or "admin" for administrative privileges 

on the specified package. 

● URL rewrite rules 

Use the rewrite_rules keyword in the .xsaccess file to hide internal URL path details from external users, 

clients, and search engines. It is not possible to define global rewrite rules; the rules you define apply to the 

specified local application only. Rules are specified as a source-target pair where the source is written in the 

JavaScript regex syntax, and the target is a simple string where references to the groups found can be 

inserted using $groupnumber. 

● Connection security 

Use the force_ssl keyword in the .xsaccess file to enforce the use of secure HTTP (SSL/HTTPS) for client 

connections. Browser requests that do not use SSL/HTTPS are refused and the 403 Forbidden page is 

displayed. Note that if you set the force_ssl option, then you must ensure that the SAP Web Dispatcher is 

configured to accept and manage HTTPS requests. For more information about configuring the SAP Web 

Dispatcher to use HTTPS/SSL see the SAP HANA Administration Guide. 

Note: 

● Entity Tags 



If the SAP Webdispatcher sends the header “x-sap-webdisp-ap” with the HTTPS port, the request is 

redirected to a HTTPS page, for example: http://..:80/test -> https://..:433/test. 

Otherwise, a 403 error is displayed. 

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You can allow or prevent the generation of entity tags (etags) for static Web content using the enable_etags 

keyword in the .xsaccess file. Etags are used to improve caching performance, for example, so that the 

same data is not resent if no change has occurred since the last request. 

● MIME Mapping 

MIME means Multipurpose Internet Mail Extensions. You can use the mime_mapping keyword in 

the .xsaccess file to define the way in which to map certain file suffixes to required MIME types: 

"mime_mapping": [ {"extension":"jpg", "mimetype":"image/jpeg"} ] 

The Application-Access (.xsaccess) File 

The following example, shows the composition and structure of the SAP HANA XS application access 

(.xsaccess) file. In this file, data is available to client requests. The authentication methods specified are 

SAP logon ticket and then, as a fall-back option if the logon with the SAP logon ticket fails, a logon with a 

user name and password. Allowing a fall-back log-on mechanism is useful if the requesting client has 

problems handling the SAP logon ticket mechanism. 

{ 

$3" 

} 

Related Links 

"exposed" : true, // Expose data via http 

"authentication" : // Authentication method 

[ 

{ 

"method": "LogonTicket", 

}, 

{ 

"method" : "Basic" 

}, 

], 

"authorization": // Grant package privileges 

[ 

"sap.xse.test::Execute", 

"sap.xse.test::Admin" 

] 

"rewrite_rules" : // URL rewriting rules 

[ 

{ 

"source": "/entries/(\\d+)/(\\d+)/(\\d+)/", 

"target": "/logic/entries.xsjs?year=$1&month=$2&day= 

} 

], 

"mime_mapping" : // Map file-suffix to MIME type 

[ 

{ 

"extension":"jpg", "mimetype":"image/jpeg" 

} 

], 

"force_ssl" : true, // Refuse request if not SSL 

"enable_etags":false // Prevent etag generation 

http://help.sap.com/hana/hana_admin_en.pdf 

52 

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Application-Access File Keyword Options [page 53] 

The application-access (.xsaccess) file enables you to specify whether or not to expose package content, 

which authentication method is used to grant access, and what content is visible. 

4.4.4 Application-Access File Keyword Options 

The application-access (.xsaccess) file enables you to specify whether or not to expose package content, which 

authentication method is used to grant access, and what content is visible. 

The Application Access (.xsaccess) File 

The following example shows all possible keyword combinations in the SAP HANA XS application-access 

(.xsaccess) file. 

} 

{ 

exposed 

{ 

Note: In the form shown below, the .xsaccess file is not a working model; it is used to illustrate all 

possible options. 

"exposed" : true, 

"authentication" : // null = no auth required, 

[ 

{ 


}, 

{ 

"method" : "Basic" 

}, 

{ 

"method": "Form", 

} 

], 

"authorization": 

[ 



] 

"rewrite_rules" : 

[{ 

"source" : "...", 

"target" : "..." 

}], 

"mime_mapping" : 

[ 

{ 


} 

], 

"force_ssl" : true, 

"enable_etags":false 




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} 

The exposed keyword enables you define if content in a package (and its subpackages) is to be made available by 

HTTP to client requests. Values are Boolean true or false. If no value is set for exposed, the default setting (false) 

applies. 

authentication 

} 

{ 

"authentication" : 

[ 

{ 


}, 

{ 

"method" : "Basic", 

}, 

{ 

"method": "Form", 

} 

], 

The authentication keyword enables you to define the authentication method to use for Browser requests either 

at the application level or for single packages in an application. SAP HANA Extended Application Services support 

the following logon authentication mechanisms: 

Note: You can specify multiple authentication methods in the application-access file. 

● Basic authentication 

Logon with a recognized database user name and password. 

● SAP logon ticket 

SAP logon tickets enable single sign-on across SAP boundaries; SAP logon tickets can be also be used as 

authentication for access to third-party applications. 

● Form-based authentication 

Redirect the logon request to a form to fill in, for example, a Web page. 

If you use the authentication in the .xsaccess file, you must specify the authentication method to apply, for 

example, basic or SAP logon ticket. If you use the authentication keyword in the application-access file, but do not 

set an authentication method, your .xsaccess file is a valid JSON file but is not a semantically valid .xsaccess 

file and will return a parsing validation error . If you do not set the authentication keyword, your application applies 

the default basic authentication method (user name and password) to enable access to data. 

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Note: You can disable authentication checks with the null options, as follows: {"authentication" : 

null}. 

authorization 

{ 

} 


[ 



] 

The authorization keyword in the .xsaccess file enables you to specify which authorization level is required for 

access to a particular application package, for example, execute or admin on the package sap.xse.text. 

Note: The authorization levels you can choose from are defined in the .xsprivileges file for the 

package, for example, "execute" for basic privileges, or "admin" for administrative privileges on the 

specified package. If you use the authorization keyword in the .xsaccess file, for example, to require 

“execute” privileges for a specific application package, you must create a .xsprivileges file for the 

same application package (or a parent package higher up the hierarchy, in which you define the “execute” 

privilege level declared in the .xsaccess file. 

rewrite_rules 

} 

{ 


[{ 

"source" : "...", 

"target" : "..." 

}] 

The rewrite_rules keyword enables you hide the details of internal URL paths from external users, clients, and 

search engines. Any rules specified affect the local application where the .xsaccess file resides (and any 

subpackage, assuming the subpackages do not have their own .xsaccess files); it is not possible to define global 

rewrite rules. URL rewrite rules are specified as a source-target pair where the source is written in the JavaScript 

regex syntax and the target is a simple string where references to found groups can be inserted using 

$groupnumber. 

mime_mapping 

{ 




[ 

{ 


} 

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} 

] 

The mime_mapping keyword enables you to define how to map certain file suffixes to required MIME types. For 

example, you can map files with the .jpg file extension to the MIME type image/jpeg. 

force_ssl 

} 

{ 

"force_ssl" : true, 

The force_ssl keyword enables you to refuse Browser requests that do not use secure HTTP (SSL/HTTPS) for 

client connections. If no value is set for exposed, the default setting (false) applies and non-secured connections 

(HTTP) are allowed. 

enable_etags 

} 

{ 

"enable_etags" : true, 

You can allow or prevent the generation of entity tags (etags) for static Web content using the enable_etags 

keyword. If no value is set, the default setting (true) applies, in which case etags are generated. Etags are used to 

improve caching performance, for example, so that the same data is not resent from the server if no change has 

occurred since the last time a request for the same data was made. 

4.4.5 Application-Access URL Rewrite Rules 

Rewriting URLs enables you to hide internal URL path details from external users, clients, and search engines. You 

define URL rewrite rules in the application-access file (.xsaccess) for each application or for an application 

hierarchy (an application package and its subpackages). 

The rewrite rules you define in the .xsaccess file apply only to the local application to which the .xsaccess file 

belongs; it is not possible to define global rules to rewrite URLs. Rules are specified as a source-target pair where 

the source is written in the JavaScript regex syntax, and the target is a simple string where references to found 

groups can be inserted using $groupnumber. 

The following examples show how to use a simple set of rewrite rules to hide internal URLs from requesting clients 

and users. 

The first example illustrates the package structure that exists in the repository for a given application; the 

structure includes the base package apptest, the subpackages subpackage1 and subpackage2, and several 

other subpackages: 

56 

sap---apptest 

|---logic 

| |---users.xsjs 

| |---posts.xsjs 

|---posts 

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| |---2011... 

|---subpackage1 

| |---image.jpg 


| |---subsubpackage 

| | |---secret.txt 

| |---script.xsjs 


| |---internal.file 

|---users 

| |---123... 

|---.xsapp 

|---.xsaccess 

|---index.html 

The application-access file for the package apptest (and its subpackages) includes the following rules for 

rewriting URLs used in client requests: 

{ 

} 

"rewrite_rules": [ 

{ 

"source": "/users/(\\d+)/", 

"target": "/logic/users.xsjs?id=$1" 

}, 

{ 

"source": "/posts/(\\d+)/(\\d+)/(\\d+)/", 

"target": "/logic/posts.xsjs?year=$1&month=$2&day=$3" 

} 

] 

Assuming we have the package structure and URL rewrite rules illustrated in the previous examples, the following 

valid URLs would be exposed; bold URLs require authentication: 

/sap/apptest/ 

/sap/apptest/index.html 

/sap/apptest/logic/users.xsjs 

/sap/apptest/logic/posts.xsjs 

The rewriting of the following URLs would be allowed: 

/sap/apptest/users/123/ ==> /sap/appTest/logic/users.xsjs?id=123 

/sap/apptest/posts/2011/10/12/ ==> /sap/appTest/logic/posts.xsjs? 

year=2011&month=10&day=12 

4.4.6 Enabling Access to SAP HANA XS Application 

Packages 

The application-access file enables you to specify who or what is authorized to access the content exposed by the 

application package and what content they are allowed to see. 

You can use a set of keywords in the application-access file .xsaccess to specify if authentication is required to 

enable access to package content, which data is exposed, and if rewrite rules are in place to hide target and 

source URLs, for example, from users and search engines. You can also specify what, if any, level of authorization 

is required for the package and whether SSL is mandatory for client connections. 



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1. Create the application access file. 

The application-access file must be a JSON-compliant file with the file suffix .xsaccess. Note that the 

application-access file does not have a name before the dot (.); it only has the suffix .xsaccess. 

Create a file called .xsaccess and place it in the package containing the application to which you want to 

enable accesss. A basic .xsaccess file must, as the very least, contain a set of curly brackets, for example, 

{}. Note that the .xsaccess file uses keyword-value pairs to set access rules; if a mandatory keyword-value 

pair is not set, then the default value is assumed. 

2. Enable application access to data. 

You use the expose keyword to enable or disable access to content at a package or subpackage level. 

{ 

} 

"exposed" : true 

3. Define the application authentication method. 

You use the authentication keyword to define how to manage the authentication process for requests to 

access package content, for example, SAP logon ticket, form-based logon, or a basic user name and 

password . 

{ 

} 


[ 

{ "method" : "Basic" } 

] 

4. Specify the application privileges. 

Use the authorization keyword in the .xsaccess file to specify which authorization level is required by a user 

for access to a particular application package. The authorization levels you can choose from are defined in 

the .xsprivileges file, for example, "execute" for basic privileges or "admin" for administrative privileges 

on the specified package. 

{ 

} 


[ 



] 

5. Specify the client connection security. 

You use the force_ssl keyword to enforce the use of secure HTTP (SSL/HTTPS) for client connections. 

Browser requests that do not use SSL/HTTPS are refused and the 403 Forbidden page is displayed. 

{ 

} 

Note: You need to ensure the SAP Web Dispatcher is configured to accept and process HTTPS 

requests. 

"force_ssl" : true 

6. Define the MIME mapping to be used for specific file extensions. (Optional) 

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You use the mime_mapping keyword to map specific file extensions (for example, .jpg or .png) to a 

particular Multipurpose Internet Mail Extensions (MIME) type. 

{ 

} 


[ 

{ 

"extension":"jpg", 

"mimetype":"image/jpeg" 

} 

] 

7. Prevent the generation of entity tags. (Optional) 

You use the enable_etags keyword to prevent the generation of entity tags (etags) for static Web content. 

{ 

} 

"enable_etags":false 

8. Specify which, if any, URLs must be rewritten. (Optional) 

You use the rewrite_rules keyword to hide details of internal URL paths from external users, clients, and 

search engines. 

{ 

} 


[ 

{ 

"source" : "...", 

"target" : "..." 

} 

] 

9. Save the .xsaccess file and place it in the package with which you want to associate the rules you have 

defined. 

10. Commit the file to the repository and activate it. 

In the Project Navigator view, right click the object you want to activate and choose Team > Activate in 

the popup menu. 

Related Links 

Application-Access File Keyword Options [page 53] 

The application-access (.xsaccess) file enables you to specify whether or not to expose package content, 

which authentication method is used to grant access, and what content is visible. 

4.4.7 The Application-Privileges File 

In SAP HANA Extended Application Services (SAP HANA XS), the application-privileges (.xssprivileges) file 

can be used to create or define the authorization privileges required for access to an SAP HANA XS application, 

for example, to start the application or to perform administrative actions on an application. These privileges can 

be checked by an application at runtime. 

The application-privileges file has only the file extension .xsprivileges; it does not have a name and is 

formatted according to JSON rules. Multiple .xsprivileges files are allowed, but only at different levels in the 

package hierarchy; you cannot place two .xsprivileges files in the same application package. The package 



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privileges defined in a .xsprivileges file are bound to the package to which the .xsprivileges file belongs 

and can only be used in this package and its subpackages. 

Inside the .xsprivileges file, a privilege is defined by specifying an entry name with an optional description. 

This entry name is then automatically prefixed with the package name to form the unique privilege name, for 

example, sap.hana::Execute. 

As an application privilege is created during activation of an .xsprivileges file, the only user who has the 

privilege by default is the _SYS_REPO user. To grant or revoke the privilege to (or from) other users you must use 

the GRANT_APPLICATION_PRIVILEGE or REVOKE_APPLICATION_PRIVILEGE procedure in the _SYS_REPO 

schema. 

Note: The .xsprivileges file lists the authorization levels that are available for access to an application 

package; the .xsaccess file defines which authorization level is assigned to which application package. 

The SAP HANA XS Application-Privileges File 

The following example shows the composition and structure of a basic SAP HANA XS application- 

privileges file. 

{ 

"privileges" : 

[ 

{ "name" : "Execute", "description" : "Basic execution 

privilege" }, 

{ "name" : "Admin", "description" : "Administration 

privilege" }, 

] 

} 

In the example above, if the application-privileges file is located in the application package 

sap.hana.xse, then the following privileges are created: 

● sap.hana.xse::Execute 

● sap.hana.xse::Admin 

Note: The privileges defined apply to the package where the .xsprivileges file is located as well 

as any packages further down the package hierarchy unless an additional .xsprivileges file is 

present, for example, in a subpackage. The privileges do not apply to packages that are not in the 

specified package path, for example, sap.hana.app1. 

For the example above, the following Grant procedure would be used: 

call 

"_SYS_REPO"."GRANT_APPLICATION_PRIVILEGE"('"sap.hana.xse::Execute"', 

'') 

4.4.8 Create an SAP HANA XS Application Privileges File 

The application-privileges (.xssprivileges) file can be used to grant authorization levels for an application, for 

example, to start the application or perform administrative actions on an application. 

60 

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1. If you have not already done so, create a root package for your new application, for example, 

MyApplication. 

2. If you have not already done so, create an application descriptor for your new application and place it in the 

root package you created in the previous step. 



the file extension .xsapp. 


3. If you have not already done so, create an application-access file for your new application and place it in the 

package to which you want to grant access. 

The application-access file does not have a name; it only has the file extension .xsaccess. The contents of 

the .xsaccess file must be formatted according to JavaScript Object Notation (JSON) rules and associated 

with the package it belongs to. The rules defined in the .xsaccess file apply to the package it resides in as 

well as any subpackages lower in the package hierarchy. 

Note: 

Use the authorization keyword in the .xsaccess file to specify which authorization level is to be 

granted to a particular application package. The authorization levels you can choose from are defined 

in the application-privileges file (.xsprivileges), for example, "execute" for basic privileges, or 

"admin" for administrative privileges on the specified package. 

4. Create the application-privileges file. 

The application-privileges file does not have a name; it only has the file extension .xsprivileges. The 

contents of the .xsprivileges file must be formatted according to JavaScript Object Notation (JSON) 

rules. Multiple .xsprivileges files are allowed, but only at different levels in the package hierarchy; you 

cannot place two .privileges files in the same application package. The privileges defined in 

a .xsprivileges file are bound to the package to which the file belongs and can only be applied to this 

package and its subpackages. 

5. Define the application privileges. 

Inside the .xsprivileges file, a privilege is defined for an application package by specifying an entry name 

with an optional description. This entry name is then automatically prefixed with the package name to form 

the unique privilege name, for example, sap.hana::Execute. The unique privilege name can be used in 

multiple .xsprivileges files in different packages, since they are all different privileges. 

Note: The .xsprivileges file lists the authorization levels available for granting to an application 

package; the .xsaccess file defines which authorization level is assigned to which application 

package. 

{ 

"privileges" : 

[ 

{ "name" : "Execute", "description" : "Basic execution 

privilege" }, 

{ "name" : "Admin", "description" : "Adminstration 

privilege" }, 



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} 

] 


4.5 Tutorial: My First SAP HANA Application 

This tutorial shows you how SAP HANA development is done in the SAP HANA studio, including setting up a 

project, and developing a simple JavaScript file to extract data from the database. 

Though extremely simple, the tutorial shows the development process for programming all types of applications. 

The project creates server-side JavaScript code that retrieves data by executing SQL in the database, and then 

returns the data to the client, which in this case is a browser. The project can be viewed as adhering to the model- 

view-controller architecture: 

● Model: You have (dummy) data in the database, which we can extract via SQL. 

● Controller: You have JavaScript code that controls the extraction of the data and delivers it to the view. 

● View: You have a simple browser that calls the JavaScript code and simply displays the data. 

4.5.1 Open the Development Perspective 

Before you do anything, you have to start the SAP HANA studio and open the SAP HANA Development 

perspective. 

1. Open the SAP HANA studio. The first screen you see is the Welcome screen, with quick links to the main SAP 

HANA perspectives and to the documentation. 

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2. Select Open Development. 

The default SAP HANA Development perspective contains three views on the left for navigating SAP HANA 

and the repository, which holds the objects that you will create. In addition, the editor area is on the right, 

where you will build your objects. 

Related Links 

SAP HANA Development Perspective [page 25] 

4.5.2 Add a System 

You need to add a connection to the development SAP HANA system you will be working with. 

1. In the Navigator view, right-click anywhere in the view and select Add System. 



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2. Enter the following fields for the SAP HANA system: 

64 

○ Server name 

○ Instance number on that server 

○ A display name for this system. When you start working with a lot of systems, you will want to have a way 

to label the systems in the SAP HANA studio. Enter Development System. 

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3. Select Next. 

4. Enter a user name and password for the connection, and select Finish. 

After adding the system, you will see the system in the Navigator view. 



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4.5.3 Add a Workspace 

After you add a system, you need to specify where on your workstation you will be saving development files while 

working with this system. 

1. In the SAP HANA Repositories view, click in the upper-right of the view. 

2. Provide the following: 

○ SAP HANA system, which is the same system you just created. 

○ Workspace name, which can be anything you like. For this tutorial, enter DevWS. 

A folder with this name is created below the workspace root. 

○ Workspace root, which can be anywhere on your workstation. For this tutorial, create a folder at C: 

3. Click Finish. 

66 

\SAPHANAworkspaces and make this the root. 

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In the SAP HANA Repositories view, you will see your workspace, which enables you to browse the repository of 

the system tied to this workspace. You will see the repository's packages, displayed as folders. 

At the same time, a folder will be added to your file system to hold all your development files. 

4.5.4 Add a Project 

Now that you've set up your development environment for your SAP HANA system, you can add an Eclipse 

project to contain all the development objects you want to create. 

There are a variety of project types for different types of development objects. Generally, these projects types 

import necessary libraries for working with specific types of development objects. Here, you will create an XS 

Project. 

1. From the menu, select File New Project . 

2. Under SAP HANA Development, select XS Project, and select Next. 

3. Enter the following for the project: 

○ Name: Enter mycompany.myorg.testing. 

Since Eclipse project names must be unique within the same Eclipse workspace, a good convention is to 

use the fully qualified package name as the project name. 

○ Project Location: You can keep this as the default Eclipse workspace. 



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4. Select Finish. 

Now, in the Project Explorer view, you have a project that is ready to be shared, that is, associated with your 

workspace. 

4.5.5 Share Your Project 

After creating a project, you must associate it with a workspace, which enables the project files to be saved to the 

repository of your development SAP HANA system. 

1. In the Project Explorer view, right-click on the project, and select Team Share Project . 

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Since you only have one workspace, the wizard selects it for you. If you had several workspaces, you would 

choose with which one you wanted to share your project. 

The dialog also shows the Current project location (the current location of your project, in the Eclipse 

workspace), and the New project location (where your project will be copied so it can be associated with the 

repository workspace). 

Also, since Add project folder as subpackage is checked, subpackages will be created based on the name of 

your project. 

2. Click Finish. 

Now your project appears in the Project Explorer view associated with your workspace. 

The .project file is shown with an asterisk , which indicates that the file has changed but has yet to be 

committed, or saved, to the repository. 

3. Right-click on the project, and select Team Commit . This adds your project and its files to the 

repository, though only you can see them. The .project file is now displayed with a diamond, , indicating 

that the latest version on your workstation has been committed. 



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In addition, the SAP HANA Repositories view shows that a new hierarchy of packages has been created based 

on the name of your project, mycompany.myorg.testing. 

4.5.6 Write Server-Side JavaScript 

Now let's write some code. As a first step, to make sure everything is working OK, you will simply output Hello, 

World!. 

You will have to create three files: 

● .xsjs: This contains your code. 

● .xsapp: This indicates that everything in your package can be exposed via HTTP. You still need to explicitly 

expose the content and assign access controls. 

● .xsaccess: Exposes your content, meaning it can be accessed via HTTP, and assigned access controls. 

1. Right-click your project, and select New Other . 

2. Select SAP HANA Development XS JavaScript Source File . 

3. In File name, call your JavaScript file MyFirstSourceFile.xsjs, and select Finish. 

The file, which is blank, opens in the JavaScript editor. 

4. In the MyFirstSourceFile.xsjs file, enter the following code: 

$.response.contentType = "text/html"; 

$.response.setBody( "Hello, World !"); 

This uses the SAP HANA XS JavaScript API's response object to write out HTML. By typing $. you have 

access to the API's objects. 

5. Add a blank file called .xsapp (no name, just a file extension) by right-clicking to the root of your project. 

70 

More on this later. 

To add a file, right-click the project and select New File , enter a file name, and select Finish. 

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6. Add a file called .xsaccess (no name, just a file extension), and copy the following code: 

{ 

} 



[ 

{ "method" : "Basic" } 

] 

This code exposes the contents via HTTP, and requires you to log in with your SAP HANA credentials to 

access the file. 

7. Right-click on the project, and select Team Commit . This adds your four new files 

(.xsjs, .xsapp, .xsaccess and .project) to the repository, though only you can see the files and no one 

can run them. 

8. Right-click on the project, and select Team Activate . This publishes your work and you can now test it. 

To access your JavaScript code, open a browser and enter the URL: 

http://myServer:8000/mycompany/myorg/testing/MyFirstSourceFile.xsjs 

Note: 

● Change the server name to your server. 

● The port is 80 plus two digits for your instance. If your instance is 00, then the port is 8000. 

You should get the following: 



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After logging in with your SAP HANA user name and password, you should get the following: 

4.5.7 Retrieve Data 

To make things more interesting, let's make a call to the database via the JavaScript and then display the results. 

You will be using the SQL statement: 

select * from DUMMY 

This is test SQL to check connectivity, and returns one row with one field called DUMMY, whose value is X. 

1. In MyFirstSourceFile.xsjs, delete or comment out all your existing code. 

2. Add the following code: 

$.response.contentType = "text/html"; 

var output = "Hello, World !"; 

var conn = $.db.getConnection(); 

var pstmt = conn.prepareStatement( "select * from DUMMY" ); 

var rs = pstmt.executeQuery(); 

if (!rs.next()) { 

$.response.setBody( "Failed to retrieve data" ); 

$.response.status = $.net.http.INTERNAL_SERVER_ERROR; 

} else { 

output = output + "This is the response from my SQL: " + 

rs.getString(1); 

} 

rs.close(); 

pstmt.close(); 

conn.close(); 

$.response.setBody(output); 

3. Save the file. 

4. Commit the file by right-clicking the file and selecting Team Commit . 

5. Activate the file by right-clicking the file and selecting Team Activate . 

In your browser, refresh the page. You should get the following: 

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5 Setting up the Persistence Model 

In SAP HANA Extended Application Services (SAP HANA XS), the persistence model defines the schema, tables, 

and views that specify what data to make accessible and how. The persistence model is mapped to the 

consumption model that is exposed to client applications and users, so that data can be analyzed and displayed. 

SAP HANA XS enables you to create database schema, tables, views, and sequences as design-time files in the 

repository. Repository files can be read by applications that you develop. 

Note: All repository files including your view definition can be transported (along with tables, schema, and 

sequences) to other SAP HANA systems, for example, in a delivery unit. A delivery unit is the medium SAP 

HANA provides to enable you to assemble all your application-related repository artifacts together into an 

archive that can be easily exported to other systems. 

You can also set up data-provisioning rules and save them as design-time objects so that they can be included in 

the delivery unit that you transport between systems. 

As part of the process of setting up the basic persistence model for SAP HANA XS, you perform the following 

tasks: 

● Create a schema. 

Define a design-time schema and maintain the schema definition in the repository. The transportable schema 

has the file extension .hdbschema, for example, MYSCHEMA.hdbschema 

● Create a table. 

Define a design-time table and maintain the table definition in the repository. The transportable table has the 

file extension .hdbtable, for example, MYTABLE.hdbtable 

● Create a view. 

Define a design-time view and maintain the view definition in the repository. The transportable view has the 

file extension .hdbview, for example, MYVIEW.hdbview 

● Create a sequence. 

Define a design-time sequence and maintain the sequence definition in the repository. The transportable 

sequence has the file extension .hdbsequence, for example, MYSEQUENCE.hdbsequence 

● Import table content 

74 

Define data-provisioning rules that enable you to import data from comma-separated values (CSV) files into 

SAP HANA tables using the SAP HANA XS table-import feature. The complete configuration can be included 

in a delivery unit and transported between SAP HANA systems. 

Note: On activation of a repository file, the file suffix, for example, .hdbview, .hdbschema, 

or .hdbtable, is used to determine which runtime plugin to call during the activation process. The plugin 

reads the repository file selected for activation, for example, a table, sees the object descriptions in the 

file, and creates the appropriate runtime object. 

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Setting up the Persistence Model

5.1 Schema 

Relational databases contain a catalog that describes the various elements in the system. The catalog divides the 

database into sub-databases known as schema. A database schema enables you to logically group together 

objects such as tables, views, and stored procedures. Without a defined schema, you cannot write to the catalog. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database schema as a 

transportable design-time file in the repository. Repository files can be read by applications that you develop. 

If your application refers to the repository (design-time) version of a schema rather than the runtime version in 

the catalog, for example, by using the explicit path to the repository file (with suffix), any changes to the 

repository version of the file are visible as soon as they are committed to the repository. There is no need to wait 

for the repository to activate a runtime version of the schema. 

If you want to define a transportable schema using the design-time hdbschema specifications, use the 

configuration schema illustrated in the following example: 

string schema_name 

The following example shows the contents of a valid transportable schema-definition file for a schema called 

MYSCHEMA: 

schema_name=”MYSCHEMA”; 

The schema is stored in the repository with the schema name MYSCHEMA as the file name and the 

suffix .hdbschema, for example, MYSCHEMA.hdbschema. 

Schema Activation 

If you want to create a schema definition as a design-time object, you must create the schema as a flat file. You 

save the file containing the schema definition with the suffix .hdbschema in the appropriate package for your 

application in the SAP HANA repository. You can activate the design-time objects at any point in time. 

Note: On activation of a repository file, the file suffix, for example, .hdbschema, is used to determine 

which runtime plugin to call during the activation process. The plug-in reads the repository file selected for 

activation, parses the object descriptions in the file, and creates the appropriate runtime objects. 

If you activate a schema-definition object in SAP HANA, the activation process checks if a schema with the same 

name already exists in the SAP HANA repository. If a schema with the specified name does not exist, the 

repository creates a schema with the specified name and makes _SYS_REPO the owner of the new schema. 

Note: The schema cannot be dropped even if the deletion of a schema object is activated. 

If you define a schema in SAP HANA XS, note the following important points regarding the schema name: 

● Name mapping 

The schema name must be identical to the name of the corresponding repository object. 

● Naming conventions 


Setting up the Persistence Model 

P U B L I C 


The schema name must adhere to the SAP HANA rules for database identifiers. 

● Name usage 

The Data Definition Language (DDL) rendered by the repository contains the schema name as a delimited 

identifier. 

5.2 Creating Schemas 

A schema defines the container that holds database objects such as tables, views, and stored procedures. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database schema as a design- 

time file in the repository. 

To create a schema definition file in the repository, perform the following steps: 




4. Create the schema definition file. 

Browse to the folder in your project workspace where you want to create the new schema-definition file and 

perform the following tasks: 

a) Right-click the folder where you want to save the schema-definition file and choose New in the contextsensitive 

popup menu. 

b) Enter the name of the schema in the File Name box and add the file suffix .hdbschema, for example, 

MYSCHEMA.hdbschema. 

c) Choose Finish to save the new schema in the repository. 

5. Define the schema name. 

To edit the schema file, in the Project Explorer view double-click the schema file you created in the previous 

step, for example, MYSCHEMA.hdbschema, and add the schema-definition code to the file: 

Note: The following code example is provided for illustration purposes only. 

schema_name=”MYSCHEMA” 

6. Save the schema file. 

7. Commit the changes to the repository. 

a) Locate and right-click the new schema file in the Project Explorer view. 

b) In the context-sensitive pop-up menu, choose Team Commit . 

5.3 Tables 

In the SAP HANA database, as in other relational databases, a table is a set of data elements that are organized 

using columns and rows. A database table has a specified number of columns, defined at the time of table 

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creation, but can have any number of rows. Database tables also typically have meta-data associated with them; 

the meta-data might include constraints on the table or on the values within particular columns. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database table as a designtime 

file in the repository. All repository files including your table definition can be transported to other SAP HANA 

systems, for example, in a delivery unit. 

Note: A delivery unit is the medium SAP HANA provides to enable you to assemble all your applicationrelated 

repository artifacts together into an archive that can be easily exported to other systems. 

If your application is configured to use the design-time version of a database table in the repository rather than 

the runtime version in the catalog, any changes to the repository version of the table are visible as soon as they 

are committed to the repository. There is no need to wait for the repository to activate a runtime version of the 

table. 

The following code illustrates a simple example of a design-time table definition: 

table.schemaName = "MYSCHEMA"; 

table.tableType = COLUMNSTORE; 

table.columns = [ 

{name = "Col1"; sqlType = VARCHAR; nullable = false; length = 20; 

comment = "dummy comment";}, 

{name = "Col2"; sqlType = INTEGER; nullable = false;}, 

{name = "Col3"; sqlType = NVARCHAR; nullable = true; length = 20; 

defaultValue = "Defaultvalue";}, 

{name = "Col4"; sqlType = DECIMAL; nullable = false; precision = 2; 

scale = 3;}]; 

table.indexes = [ 

{name = "MYINDEX1"; unique = true; indexColumns = ["Col2"];}, 

{name = "MYINDEX2"; unique = true; indexColumns = ["Col1", "Col4"];}]; 

table.primaryKey.pkcolumns = ["Col1", "Col2"]; 

If you want to create a database table as a repository file, you must create the table as a flat file and save the file 

containing the table dimensions with the suffix .hdbtable, for example, MYTABLE.hdbtable. The new file is 

located in the package hierarchy you establish in the SAP HANA repository. You can activate the repository files at 

any point in time. 

Note: On activation of a repository file, the file suffix, for example, .hdbtable, is used to determine which 

runtime plugin to call during the activation process. The plugin reads the repository file selected for 

activation, in this case a table, parses the object descriptions in the file, and creates the appropriate 

runtime objects. 

5.4 Creating Tables 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database table as a designtime 

file in the repository. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database table as a design- 

time file in the repository 

To create a table file in the repository, perform the following steps: 



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4. Create the table file. 

Browse to the folder in your project workspace where you want to create the new table file and perform the 

following tasks: 

a) Right-click the folder where you want to save the table file and choose New in the context-sensitive popup 

menu. 

b) Enter the name of the table in the File Name box and add the file suffix .hdbtable, for example, 

MYTABLE.hdbtable. 

c) Choose Finish to save the new table in the repository. 

5. Define the table. 

To edit the table file, in the Project Explorer view double-click the table file you created in the previous step, for 

example, MYTABLE.hdbtable, and add the table-definition code to the file: 


table.schemaName = "MYSCHEMA"; 



{name = "Col1"; sqlType = VARCHAR; nullable = false; length = 20; 

comment = "dummy comment";}, 

{name = "Col2"; sqlType = INTEGER; nullable = false;}, 

{name = "Col3"; sqlType = NVARCHAR; nullable = true; length = 20; 

defaultValue = "Defaultvalue";}, 

{name = "Col4"; sqlType = DECIMAL; nullable = false; precision = 2; 

scale = 3;}]; 

table.indexes = [ 

{name = "MYINDEX1"; unique = true; indexColumns = ["Col2"];}, 

{name = "MYINDEX2"; unique = true; indexColumns = ["Col1", 

"Col4"];}]; 

table.primaryKey.pkcolumns = ["Col1", "Col2"]; 

6. Save the table file. 


a) Locate and right-click the new table file in the Project Explorer view. 


5.5 Sequences 

A sequence is a database object that generates a serial list of unique numbers. You can use sequence definitions 

in mappings to generate unique numbers while transforming and moving data to your target system. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database sequence as a 

transportable design-time file in the repository. Repository files can be read by applications that you develop. 

You can use database sequences to perform the following operations: 

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● Generate unique, primary key values 

● Coordinate keys across multiple rows or tables 

If you want to define a transportable sequence using the design-time sequence specifications, use the 

configuration schema illustrated in the following example. 

string schema; 

int32 increment_by(default=1); 

int32 start_with(default=-1); 

optional int32 maxvalue; 

bool nomaxvalue(default=false); 

optional int32 minvalue; 

bool nominvalue(default=false); 

optional bool cycles; 

optional string reset_by; 

bool public(default=false); 

optional string depends_on_table; 

optional string depends_on_view; 

The following example shows the contents of a valid sequence-definition file for a sequence called MYSEQUENCE. 

schema= "TEST_DUMMY"; 

start_with= 10; 

maxvalue= 30; 

nomaxvalue=false; 

minvalue= 1; 

nominvalue=true; 

cycles= false; 

reset_by= "SELECT \"Col2\" FROM \"TEST_DUMMY\". 

\"com.sap.test.tables::MY_TABLE\" WHERE \"Col2\"='12'"; 

depends_on_table= "com.sap.test.tables::MY_TABLE"; 

The sequence is stored in the repository with the suffix hdbsequence, for example, MYSEQUENCE.hdbsequence. 

If you activate a sequence-definition object in SAP HANA XS, the activation process checks if a sequence with the 

same name already exists in the SAP HANA repository. If a sequence with the specified name does not exist, the 

repository creates a sequence with the specified name and makes _SYS_REPO the owner of the new sequence. 

Note: The sequence cannot be dropped even if the deletion of a sequence object is activated. 

5.6 Creating Sequences 

A database sequence generates a serial list of unique numbers that you can use while transforming and moving 

data to between systems. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database sequence as a 

design-time file in the repository. 

To create a sequence definition file in the repository, perform the following steps: 





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4. Create the sequence-definition file. 

Browse to the folder in your project workspace where you want to create the new sequence-definition file and 


a) Right-click the folder where you want to save the sequence-definition file and choose New in the contextsensitive 


b) Enter the name of the sequence in the File Name box and add the file suffix .hdbsequence, for example, 

MYSEQUENCE.hdbsequence. 

c) Choose Finish to save the new sequence in the repository. 

5. Define the sequence properties. 

To edit the sequence file, in the Project Explorer view double-click the sequence file you created in the 

previous step, for example, MYSEQUENCE.hdbsequence, and add the sequence code to the file: 

schema= "TEST_DUMMY"; 

start_with= 10; 

maxvalue= 30; 

nomaxvalue=false; 

minvalue= 1; 

nominvalue=true; 

cycles= false; 

reset_by= "SELECT \"Col2\" FROM \"TEST_DUMMY\". 

\"com.sap.test.tables::MY_TABLE\" WHERE \"Col2\"='12'"; 

depends_on_table= "com.sap.test.tables::MY_TABLE"; 

6. Save the sequence file. 


a) Locate and right-click the new sequence file in the Project Explorer view. 


5.7 SQL Views 

In SQL, a view is a virtual table based on the dynamic results returned in response to an SQL statement. Every 

time a user queries an SQL view, the database uses the view's SQL statement to recreate the data specified in the 

SQL view. The data displayed in an SQL view can be extracted from one or more database tables. 

An SQL view contains rows and columns, just like a real database table; the fields in an SQL view are fields from 

one or more real tables in the database. You can add SQL functions, for example, WHERE or JOIN statements, to a 

view and present the resulting data as if it were coming from one, single table. 

SAP HANA Extended Application Services (SAP HANA XS) enables you to create a database view as a design-time 

file in the repository. Repository files can be read by applications that you develop. In addition, all repository files 

including your view definition can be transported to other SAP HANA systems, for example, in a delivery unit. 

If your application refers to the design-time version of a view from the repository rather than the runtime version 

in the catalog, for example, by using the explicit path to the repository file (with suffix), any changes to the 

repository version of the file are visible as soon as they are committed to the repository. There is no need to wait 

for the repository to activate a runtime version of the view. 

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To define a transportable view using the design-time view specifications, use the configuration schema illustrated 

in the following example: 

string schema; 

string query; 

bool public(default=true); 

optional list depends_on_table; 

optional list depends_on_view; 

The following example shows the contents of a valid transportable view-definition file for a view called MYVIEW: 

schema="TEST_DUMMY"; 

query="SELECT * FROM \"TEST_DUMMY\".\"com.sap.test.tables:: 

02_HDB_DEPARTMENT_VIEW\""; 

depends_on_view=["com.sap.test.tables::02_HDB_DEPARTMENT_VIEW"]; 

If you want to create a view definition as a design-time object, you must create the view as a flat file and save the 

file containing the view definition with the suffix .hdbview, for example, MYVIEW.hdbview in the appropriate 

package in the package hierarchy established for your application in the SAP HANA repository. You can activate 

the design-time object at any point in time. 

Note: On activation of a repository file, the file suffix, for example, .hdbview, is used to determine which 

runtime plugin to call during the activation process. The plug-in reads the repository file selected for 

activation, parses the object descriptions in the file, and creates the appropriate runtime objects. 

5.8 Creating SQL Views 

A view is a virtual table based on the dynamic results returned in response to an SQL statement. SAP HANA 

Extended Application Services (SAP HANA XS) enables you to create a database view as a design-time file in the 

repository. 

To create a view-definition file in the repository, perform the following steps: 




4. Create the view-definition file. 

Browse to the folder in your project workspace where you want to create the new view-definition file and 


a) Right-click the folder where you want to save the view-definition file and choose New in the contextsensitive 


b) Enter the name of the view-definition file in the File Name box and add the file suffix .hdbview, for 

example, MYVIEW.hdbview. 

c) Choose Finish to save the new view-definition file in the repository. 

5. Define the view. 

To edit the view-definition file, in the Project Explorer view double-click the view-definition file you created in 

the previous step, for example, MYVIEW.hdbview, and add the view-definition code to the file: 



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schema="TEST_DUMMY"; 

query="SELECT * FROM \"TEST_DUMMY\".\"com.sap.test.tables:: 

02_HDB_DEPARTMENT_VIEW\""; 

depends_on_view=["com.sap.test.tables::02_HDB_DEPARTMENT_VIEW"]; 

6. Save the view-definition file. 


a) Locate and right-click the new view-definition file in the Project Explorer view. 


5.9 Data Provisioning Using Table Import 

You can import data from comma-separated values (CSV) into the SAP HANA tables using the SAP HANA 

Extended Application Services (SAP HANA XS) table-import feature. 

In SAP HANA XS, you create a table-import scenario by setting up an import-model file, a import-data file, and one 

or more comma-separated value (CSV) files containing the content you want to import into the specified SAP 

HANA table. The import-model file links the import operation to one or more target tables. The table definition (for 

example, in the form of a .hdbtable file) can either be created separately or be part of the table-import scenario 

itself. 

To use the SAP HANA XS table-import feature to import data into an SAP HANA table, you need to understand the 

following table-import concepts: 

● Table-Import Model 

You define the table-import model in a configuration file that specifies the data fields to import and import 

target tables of each data field. 

● Table-Import Data 

You define the table-import data in a configuration file that specifies how to link the CSV data files to the 

respective data field and, in turn, the target tables via the table-import model. 

● Table-Import Extension 

You define the table-import extension in a configuration file that modifies the relationship to an existing table 

import data file. 

CSV Data File Constraints 

The following constraints apply to the table-import feature in SAP HANA XS: 

● The number of table columns must match the number of CSV columns. 

● There must not be any incompatibilities between the data types of the table columns and the data types of the 

CSV columns. 

● Overlapping data in data files is not supported. 

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● The target table of the import must not be modified (or appended to) outside of the data-import operation. If 

the table is used for storage of application data, this data may be lost during any operation to re-import or 

update the data. 

5.9.1 Table-Import Model 

The table-import model is a configuration file that you use to specify the parameters associated with the list of 

comma-separated-value (CSV) files that you want to import. The table-import model also specifies, for each 

parameter, into which table the linked-data files are imported, for example, the CSV files linked in the table-import 

data file. 

You can declare a parameter as optional. If a parameter is optional, it is not necessary to assign a value to this 

parameter in the implementing table import data object. To declare a variable as optional in the table-import 

model, add the keyword optional before the variable, as illustrated in the example below. 

optional listCsvFile csvList; 

If you want to add comments to your table-import model, use two back slashes (//) as illustrated in the example 

below. 

listCsvFile fileList; //this is the csv file list 

Example Table-Import Model File 

listCsvFile csvFiles; 

import csvFiles "TISCHEMA" "TiPackage::TiTable"; 

5.9.2 Table-Import Data 

The table-import data configuration file enables you to specify which table-import model is to be implemented, for 

example, TiModel.hdbtim. The file-list parameters created in the table import-model file are assigned to lists of 

data-file links, for example, comma-separated values (.csv) files. In the example illustrated below, the .csv is 

called TiCsv.csv. 

If you want to add comments to your table-import model, use two back slashes (//) as illustrated in the example 

below. 

implements TiPackage:TiModel.hdbtim; //This is a the import model 

You can declare a parameter as final. If a parameter is defined as final, you can prevent modifications of values 

assigned to file lists, for example, in a table-import extension. To declare a variable as final in the table-import data 

file, add the keyword final before the variable, as illustrated in the example below. 

final csvFiles = ["sap.mypackage:data.csv"]; 

Example Table-Import Data File 

implements TiPackage:TiModel.hdbtim; //This is a comment 

csvFiles = ["TiPackage:TiCsv.csv"]; 

csvFilesExt = [ 

{ 

file="TiPackage:TiCsv.csv" 

}, 



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{ 

} 

]; 

header = false; 

file = "sap.xse:csv_config.csv"; 

keys = [ "Col1" : "b*", "Col1" : "a"]; 

5.9.3 Table-Import Extensions 

The table-import feature enables you to modify the initial settings for variables defined in table-import 

configuration files by specifying new settings for defined variables in separate extension files. 

If both a table-import model and a table-import data file exist, then you can modify initial variable assignments 

made in one table-import data file in a subsequent table-import data files (so called extensions) - as long as the 

variables are not declared explicitly as final in a previous file. The modification takes place only on the data values 

of variables, for example, in a table-import-extension data file, where values can be augmented or be replaced. 

The result is a chain of table-import data artifacts. The end result of a successful table import operation is based 

on the resulting definition of the file-list parameter as a result of all data files in the chain. 

Note: You can only create a linear chain of extensions. It is not permitted to create two table import data 

files modifying the same base table import data files. 

The following example illustrates a simple table-import model named timodel.hdbtim in the package 

TiPackage. 

csvFileList csvList; 

import csvList "TISCHEMA" "TiPackage::TiTable"; 

The following example illustrates the contents of a simple table-import data file named tidata.hdbtid, which 

implements the table-import model defined in timodel.hdbtim illustrated above. 

implements TiPackage:timodel.hdbtim; 

csvList = ["TiPackage:mydata.csv"]; 

The following example illustrates how to extend the definition in the table-import data file tidata.hdbtid 

illustrated above. 

modifies sap.myPackage:tidata.hdbtid; 

csvList = csvList + ["TiPackage:myotherdata.csv"]; 

After activation of the table-import files, the data from both CSV files (TiPackage:mydata.csv, and 

TiPackage:myotherdata.csv) is imported into the target table. 

5.9.4 Table-Import Configuration-File Syntax 

When you define the details of the table-import operation, you use the following file-list types to enable the 

processing of certain data formats: 

● csvFileList 

Used to specify list of comma-separated values (CSV) file links. The linked CSV files are imported into the 

target table specified in the table import model. The import process parses and validates the CSV file format. 

● csvFileListExt 

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Similar to (but more flexible than) csvFileList since more settings are possible. You must specify the target 

table and the destination file list of CSV files, which is also extendable. For each CSV file it is possible to define 

the following additional options: 

○ If a header is given or not 

○ Which delimiter is use to separate the CSV data 

○ The key area of the input values 

○ If values are optionally enclosed by an given delimiter 

Table Import Model Example 

The following example shows how to use the file list types csvFileList and csvFileListExt in the table-import 

model definition: 



listCsvFileExt csvFilesExt; 

import csvFilesExt "TISCHEMA" "TiPackage::TiTableExt"; 

Table Import Data Example 

The following example shows how to use the file list types csvFileList and csvFileListExt in the table-import 

data definition: 

implements TiPackage:TiModel.hdbtim; 


csvFilesExt = [ 

{ 

file="TiPackage:TiCsv.csv" 

}, 

{ 

header = false; 

file = "sap.xse:csv_config.csv"; 

keys = [ "Col1" : "b*", "Col1" : "a"]; 

} 

]; 

5.10 Importing Data Using Table Import 

The table-import function imports data from comma-separated values (CSV) files into SAP HANA tables. 

Before you start this task, make sure that the following prerequisites are met: 

● An SAP HANA database instance is available. 

● The SAP HANA database client is installed and configured. 

● You have a database user account set up with the roles containing sufficient privileges to perform actions in 

the repository, for example, add packages, add objects, and so on. 

● The SAP HANA studio is installed and connected to the SAP HANA repository. 



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● You have a development environment including a repository workspace, a package structure for your 

application, and a shared project to enable you to synchronize changes to the project files in the local file 

system with the repository. 

Note: The names used in the following task are for illustration purposes only; replace the names of 

schema, tables, files, and so on shown in the following examples with your own names. 

1. Create a root package for your table import application. 

In SAP HANA studio, open the SAP HANA Development perspective and perform the following steps: 

a) In the Navigator view, right-click the package in the package hierarchy where you want to create the new 

package for your table-import configuration and choose New > Package... . 

b) Enter a name for your package, for example TiPackage. 

Note: Naming conventions exist for package names, for example, a package name must not start 

with either a dot (.) or a hyphen (-) and cannot contain two or more consecutive dots (..). In 

addition, the name must not exceed 190 characters. 

a) Choose OK to create the new package. 

2. Create a set of table-import files. 

The following files are required for a table import scenario. 

○ The table-import data file, for example, TiData.hdbtid 

Links the CSV data files to the data field and thus the target tables via the model 

○ A table-import model, for example, TiModel.hdbtim 

Defines the data fields and import target tables of each data field 

○ A table import package, for example, TiPackage 

Contains all the artifacts you need to complete the table-import operation 

○ A CSV file, for example, TiCsv.csv 

Contains the data to be imported into the SAP HANA table 

○ A table definition, for example, TiTable.hdbtable 

Defines the structure of the target import table 

○ The schema definition, for example, TISCHEMA.schema 

Specifies the name of the schema in which the target import table is created 

○ An application-logic, for example, TiConsumerApp.xsjs 

Once all files are created, you can import data from a source file, such as a CSV file, into the desired table 

during a commit. 

3. Using any code editor, open the schema definition (TISCHEMA.schema) file that you just created and enter 

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the name of the schema you want to apply. 

schemaname=TISCHEMA 

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4. Open the table definition of the target import table (TiTable.hdbtable) file that you just created and enter 

the following lines of text. 

table.schemaName = "TISCHEMA"; 


table.columns = 

[ 

{name = "Surname"; sqlType = VARCHAR; nullable = false; length = 

40; comment = "Person's surname";}, 

{name = "Forename"; sqlType = VARCHAR; nullable = false; length = 

40; comment = "Person's forename";} 

... 

]; 

table.primaryKey.pkcolumns = ["Surname"]; 

5. Open the CSV file, for example, TiCsv.csv in a text editor and enter some values, for example, the following 

lines. 

Meyer,Hugo 

Schmitt,Michael 

Foo,Bar 

6. Open the table-import model (TiModel.hdbtim) file that you just created and enter the following lines of 

text. 



7. Open the data definition file (TiData.hdbtid) file that you just created in the same package and enter the 

following lines of text. 

implements TiPackage:TiModel.hdbtim; 


8. Deploy the table import. 

a) Select the package that you created in the first step. 

b) Click the alternate mouse button and choose Commit. 

c) Click the alternate mouse button and choose Activate. 

You have imported data into the SAP HANA table using the table import feature. 

5.11 Using Imported Table Data in SAP HANA 

Before you start, ensure that you have deployed a table import. 

Note: If you activate the files and then log on to the system using the SAP HANA studio, you do not have 

sufficient privileges to execute a SELECT statement on the table that was created. To be able to execute 



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the select statement on the table that was created, execute the following statement using the SQL editor 

in the SAP HANA studio: 

call 

_SYS_REPO.GRANT_PRIVILEGE_ON_ACTIVATED_CONTENT('select','"::"',''); 

1. In the SAP HANA studio, write a Select statement to view the imported data. 

For example: 

SELECT * FROM "TiPackage::TiTable"; 

2. Choose Execute. 

You can view the contents of the comma-separated values (CSV) file in the SAP HANA table. 

5.12 Using Imported Table Data in an SAP HANA XS 

Application 

Before you start, ensure that you have deployed a table import. 

Note: If you activate the files and then log on to the system using the SAP HANA studio, you do not have 

sufficient privileges to execute a SELECT statement on the table that was created. You must execute the 

following statement using the SQL editor in the SAP HANA studio: 

call 

_SYS_REPO.GRANT_PRIVILEGE_ON_ACTIVATED_CONTENT('select','"Ti 

Package::TiTable"',''); 

The example in the note above is for illustration purposes only. In the example shown, TiPackage is the path to 

the table-import package in the repository, where package names are separated by a dot (.); TiTable is the name 

of the table that is the target for the data-import operation; and is the name of a valid SAP HANA 

database user. 

To use imported table in an SAP HANA XS application, perform the following steps: 

1. Create an application-descriptor file and place it in your table-import package, for example, TiPackage. 

The application-descriptor file has no contents and no name; it only has the file extension .xsapp. 

2. Create an application-access file and place it in the package to which you want to grant access, for example, in 

same TiPackage package as the application descriptor file you created in the previous step. 

The application-access file does not have a name; it only has the file extension .xsaccess. 

3. In the application-access (.xsaccess) file, enter the following lines of text: 

88 

{ 

} 

"auth_required" : true 

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4. Create an application-logic file using server-side JavaScript, for example, TiConsumerApp.xsjs and place it 

in your table-import package, for example TiPackage. 

The application-logic file is the SAP HANA XS JavaScript application you use to access the data imported into 

the table. 

5. Enter the following lines of text into your application-logic file, for example, TiConsumerApp.xsjs. 

Note: The following example is for illustration purposes only. In the example shown, 

.TiPackage is the absolute path to the table-import package in the repository and 

TiTable is the name of the table that is the target for the data-import operation. 

$.response.contentType = "text/plain"; 


var pstatement1 = conn.prepareStatement( "SELECT * FROM 

\"TiPackage::TiTable\" WHERE \"Surname\"='Meyer"); 

var result = pstatement1.executeQuery(); 

if (result) 

{ 

if (result.next()) 

{ 

$.response.setBody('The sql statement execution was successful.'); 

} 

else 

{ 

$.response.setBody("No data found"); 

} 

$.response.status = $.net.http.OK; 

} 

else 

{ 


} 

result.close(); 

pstatement1.close(); 

conn.close(); 

6. Select the package that you created in the first step. 

7. Click the alternate mouse button and choose Commit. 

8. Click the alternate mouse button and choose Activate. 

9. Access the SAP HANA XS application with the following URL http://: 

80//.xsjs. 

You receive the message, The SQL statement execution was sucessful. 

5.13 Extending a Table Import 

Extend an existing table import file by creating a new table-import configuration file that you use to specify how to 

modify the relation to an existing table-import file. 

Before you start, ensure that you have deployed a table import; the following files are required for a table import 

extension scenario. 



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● The table-import data file, for example, TiData.hdbtid 

Links the new comma-separated-values CSV data files to the data fields and, in turn, the target tables via the 

model 

● The table-import extension file, for example, TiDataExtend.hdbtid 

Extends the table-import data file TiData.hdbtid 

● A table-import model, for example, TiModel.hdbtim 

Defines the data fields and import target tables of each data field 

● A table import package, for example, TiPackage 

Contains all the artifacts you need to complete the table-import operation 

● A CSV file, for example, TiCsv.csv 

Contains the data to be imported into the SAP HANA table 

● A second CSV file, for example, TiCsvExtend.csv 

Contains the new (extended) data to be imported into the table 

● A table definition, for example, TiTable.hdbtable 

Defines the structure of the target import table 

● The schema definition, for example, TISCHEMA.schema 

Specifies the name of the schema in which the target import table is created 

● An application-logic, for example, TiConsumerApp.xsjs 

1. Open the repository package that contains the table-import data file (for example, TiData.hdbtid) that you 

want to extend. 

2. Create a CSV file and give the new CSV file a name, for example, TiCsvExtend.csv. 

This is the CSV file that contains the new, extended data to be imported into the table. The extended data 

either changes or adds to the date specified in the original CSV file TiCsv.csv. 

3. Open the new CSV file TiCsvExtend.csv in any code editor and enter the new, extended values you want to 

import separated by a comma. 

For example, enter the name NewFoo,Bar. 

NewFoo,Bar 

Note: The value NewFoo in theTiCsvExtend.csv modifies the original Foo value specified in the first 

CSV file TiCsv.csv. 

4. Create a table-import data-extension file (for example, TiDataExtend.hdbtid) and place the new data- 

extension file in the same package (for example, TiPackage) as the other files. 

5. Enter the following lines into the data-extension file TiDataExtend.hdbtid. 

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.TiPackage is the absolute path to the table-import package in the repository and 

TiData.hdbtid is the name of the data-extension file for the data-import operation. 

modifies TiPackage:TiData.hdbtid; 

csvFiles = csvFiles + ["TiPackage:TiCsvExtend.csv"]; 

6. In the SAP HANA XS application .xsjs, modify the script to query the 

new value(s) specified in the table-import extension configuration. 

In this example, the table-import extension adds the name NewFoo to the data to be imported to SAP HANA; 

you now want to query the value NewFoo. 


TiPackage is the absolute path to the table-import package in the repository and 

TiTable is the name of the table that is the target for the data-import operation. 



var pstatement1 = conn.prepareStatement( "SELECT * FROM 

\"TiPackage::TiTable\" WHERE \"Surname\"='NewFoo"); 

var result = pstatement1.executeQuery(); 

if (result) 

{ 

if (result.next()) 

{ 

$.response.setBody('The sql statement execution was successful.'); 

} 

else 

{ 

$.response.setBody("No data found"); 

} 


} 

else 

{ 


} 

result.close(); 

pstatement1.close(); 

conn.close(); 

7. Access the SAP HANA XS application with the following URL http://: 

80//.xsjs. 

You receive the message, The SQL statement execution was successful. 



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6 Setting Up the Analytic Model 

Modeling refers to an activity of refining or slicing data in database tables by creating views to depict a business 

scenario. The views can be used for reporting and decision-making. 

The modeling process involves the simulation of entities, such as CUSTOMER, PRODUCT, and SALES, and 

relationships between them. These related entities can be used in analytics applications such as SAP 

BusinessObjects Explorer and Microsoft Office. In SAP HANA, these views are known as information views. 

Information views use various combinations of content data (that is, non-metadata) to model a business use case. 

Content data can be classified as follows: 

● Attribute: Descriptive data, such as customer ID, city, and country. 

● Measure: Quantifiable data, such as revenue, quantity sold and counters. 

You can model entities in SAP HANA using the Modeler perspective, which includes graphical data modeling tools 

that allow you to create and edit data models (content models) and stored procedures. With these tools, you can 

also create analytic privileges that govern the access to the models, and decision tables to model related business 

rules in a tabular format for decision automation. 

You can create the following types of information views: 

● Attribute Views 

● Analytic Views 

● Calculation Views 

The figure below shows the process flow for modeling in SAP HANA. 

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Setting Up the Analytic Model

You can perform the following tasks in the Modeler perspective: 

● Import metadata 

Create tables by importing the table definitions from the source systems using the Data Services 

infrastructure. For more information, see Importing Table Definitions. 

● Load data 

Note: You can also create tables from scratch using the SAP HANA Development perspective. For 

more information, see Setting Up the Persistence Model. 

Load data into the table definitions imported from the source system using the Load Controller, Sybase 

Replication Server or SAP Landscape Transformation, and from flat files. For more information, see Loading 

Data into Tables. 

● Create packages 

Note: You can also provision data into the table definitions in the SAP HANA Development perspective. 

For more information, seeSetting Up the Persistence Model. 

Logically group objects together in a structured way. For more information, see Maintaining Repository 

Packages. 

● Create information views 

Model various slices of the data stored in the SAP HANA database. Information views are often used for 

analytical use cases, such as operational data mart scenarios or multidimensional reporting on revenue, 

profitability, and so on. For more information, see Creating Views. 

● Create procedures 

Create procedures using SQLScript for implementing a complex logic that cannot be achieved using other 

objects. For more information, see Developing Procedures. 

● Create analytic privileges 

Control which data that individual users sharing the same data foundation or view can see. For more 

information, see Setting Up Roles and Authorizations. 

● Import SAP NetWeaver BW objects 

Import SAP NetWeaver BW objects into SAP HANA, and expose them as information views. For more 

information, seeImporting BW Objects. 

● Create decision tables 

Create a tabular representation of related rules using conditions and actions. For more information, see 

Creating Decision Tables. 

● Import and export objects 

Import and export the content objects from and to the client and server location. For more information, 

seeImplementing Lifecycle Management. 


Setting Up the Analytic Model 

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Related Links 

SAP HANA Studio [page 23] 

The SAP HANA studio is an Eclipse-based development and administration tool for working with SAP HANA, 

including creating projects, creating development objects, and deploying them to SAP HANA. As a developer, 

you may want to also perform some administrative tasks, such as configuring and monitoring the system. 

6.1 Setting Up the Modeling Environment 

6.1.1 Setting Modeler Preferences 

You can set preferences for your Eclipse workspace to set up the default settings that the system uses whenever 

you log on. 

1. Choose Window Preferences Modeler 

Note: You can also set the preferences choosing Quick Launch Manage Preferences 

2. Identify the required preference and perform the corresponding substeps from the table below: 

94 

Requirement Preference Substeps 

To specify the structure of content 

packages in the navigator panel 

To set the preferences for loading data 

using flat file 

To set the default value for the client 

that will be used while previewing 

model data 

Content Presentation Hierarchical - to view the package 

structure in a hierarchical manner 

such that, the child folder is inside the 

parent folder. Flat - to view all the 

packages at the same level for 

example, sap, sap.ecc, sap.ecc.ui. 

Show Object Type Folders - to group 

together similar objects in a package 

such as attribute views in the Attribute 

View package. 

Data From Local File 1. Browse the location to save error 

log files for data load using flat 

files. 

2. Enter the batch size for loading 

data. For example, if you specify 

2000 and a file has records of 

10000 rows the data load will 

happen in 5 batches. 

3. Enter a decision maker count that 

will be used to propose data types 

based on the file. For example, 

enter 200 if you want the 

proposal to be made based on the 

200 rows of file data. 

Default Model Parameters Select the client from the Default 

Client drop-down list. 

To enforce various rules on objects Validation Rules Select the required rules to be applied 

while performing object validation. 

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Requirement Preference Substeps 

Note: Enforcing validation 

rules with severity “Error” 

are mandatory. 

To determine the numbers of rows to 

be displayed in a page 

Data Preview Select the maximum rows for data 

preview as required. 

To specify a location for job log files Logs 1. Expand the Logs node. 

To enable logging the repository calls 

and specify location for repository log 

files 

To enable search for the attributes 

used in the views 

To allow lower case alphabets for 

attribute view, analytic view, 

calculation view, procedure and 

analytic privilege names 

2. Select Job Log. 

3. Browse the location where you 

want to save the job log files. 

Logs 1. Expand the Logs node. 

2. Select Job Log. 

3. Select true from the drop-down 

list. 

4. Browse the location where you 

want to save the repository log 

files. 

Search Options Select Enable Search Attributes. . 

Case Restriction Deselect the Model name in upper 

case checkbox. 

Note: After changing the preferences make sure you choose Apply and OK. 

6.1.2 Configuring the Import Server 

In order to load data from external sources to SAP HANA you need to establish a connection with the server. To 

connect you need to provide the details of BusinessObjects Data Services repository and ODBC drivers. Once the 

connection is established you can import the tables definition and then load the data into table definitions. 

1. In the Quick Launch tab page, choose Configure Import Server. 

2. Enter the IP address of the server from which you want to import data. 

3. Enter the repository name. 

4. Enter the ODBC data source, and choose OK. 

6.1.3 Importing Table Definitions 

One of the ways to create tables to load source system data into SAP HANA is to import the table definitions from 

the source system. 

You have configured the SAP HANA modeler for importing metadata using the Data Services infrastructure. 

Use this procedure to import table definitions (metadata) from a source system to load source system data into 

SAP HANA. You can point to these table definitions for creating various content models such as attribute, 

analytic, and calculation views. 



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Based on your requirements, use one of the following approaches: 

● Mass Import: To import all table definitions from a source system. For example, you can use this approach if 

this is a first import from the given source system. 

● Selective Import: To import only selected table definitions from a source system. For example, you can use 

this approach if there are only few table definitions added or modified in the source system after your last 

import. 

1. If you want to import all table definitions, do the following: 

a) In the File menu, choose Import. 

b) Expand the SAP HANA Content node. 

c) Choose Mass Import of Metadata, and choose Next. 

d) Select the target system where you want to import all the table definitions, and choose Next. 

e) In the Connection Details dialog, enter the operating system user name and password of the target 

system. 

f) Select the required source system, and choose Finish. 

Note: If the required system is not available from the dropdown list, you need to contact your 

administrator. 

2. If you want to import selective table definitions, do the following: 

a) In the File menu, choose Import. 

b) Expand the SAP HANA Content node. 

c) Choose Selective Import of Metadata, and choose Next. 

d) Select the target system where you want to import the table definitions, and choose Next. 

e) Select the required source system. 

Note: If the required system is not available from the dropdown list, you need to add the new 

source system using Manage Connections. 

f) In the Type of Objects to Import field, select the required type, and choose Next. 

g) Add the required objects (tables or extractors) that you want to import. 

Note: If you want to add dependent tables of a selected table, select the required table in the 

Target panel, and choose Add Dependent Tables in the context menu. 

h) Select the schema into which you want to import the metadata. 

i) If you selected object type as extractor, select the package into which you want to place the 

corresponding objects. 

j) Choose Next, then review and confirm the import by choosing Finish. 

If the source object is a table or non V-type extractor, the system creates physical tables and stores them in 

the selected schema. However, if the source object is a V-Type extractor, the system creates content models 

and stores these models in the selected package, and the underlying physical tables in the schema. 

Configuring Data Services for Metadata Import 

Use this procedure to enable the SAP HANA modeler to import table definitions from the source system using the 

Data Services infrastructure. 

1. Set the Passphrase 

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a) Log on to the Central Management Console of SAP BusinessObjects Enterprise (BOE). 

b) Choose Manage Applications Data Services Application Settings . 

c) In the Encryption Passphrase field, enter the passphrase that you have been using for the SAP HANA 

studio, and choose Save. 

d) Restart the TOMCAT and BOE services. 

2. Disable Session Security 

a) Log on to the Data Services Management Console. 

b) Choose Administrator. 

c) In the Navigator panel, choose Web Services. 

d) Choose the Web Services Configuration tab page. 

e) Select the Import_Repo_Object checkbox to save the connection details. 

f) Select Disable Session Security from the dropdown menu, and choose Apply. 

3. Creating a Data Source 

a) Go to Start Control Panel Administrative Tools . 

b) Choose Data Sources (ODBC). 

c) Choose the System DSN tab page, and choose Add. 

d) Select HDBODBC from the driver list, and choose Finish. 

e) Enter a name and description for the data source. 

f) Enter server details. 

Note: The format in which you need to enter details is . For 

example, abc2012.wdf.sap.corp:30115. 

g) Enter the required database details in the format, . For example, M4701. 

h) Choose Connect. 

Managing Source System Connections 

Use this procedure to add or manage a source system connection that is required to import table definitions. 

6.1.4 Loading Data into Tables 

● If you are using the Load Controller or Sybase Replication Server infrastructure, make sure that you have 

imported all table definitions into the SAP HANA database. For more information, see Importing Table 

Definitions. 

● If you are using the SLT component, the source system(s), target system and the target schema, are 

configured by the administrator during the installation. 

Use this procedure to load data into your table definitions. Depending on your requirements, you can perform the 

following: 

● Initial Load - to load all data from a source SAP ERP system into the SAP HANA database by using Load 

Controller or SAP Landscape Transformation (SLT). This is mostly applicable when you are loading data from 

the source for the first time. 



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● Data Replication - to keep the data of selected tables in the SAP HANA database up-to date with the source 

system tables by using SyBase Replication Server or SAP Landscape Transformation (SLT). 

1. In the Quick Launch tab page, choose Data Provisioning. 

2. If you are using SLT-based replication, choose Source. 

3. Choose Load (for initial load) or Replicate (for data replication) as appropriate. 

4. Select the required tables to load or replicate data in any of the following ways: 

○ Search for the required tables. 

1. Select the table from the list, and choose Add. 

2. If you want to save the selected list of tables locally for future reference, select the Export selected 

tables checkbox, and specify the target location. 

○ Load the list of tables from a local file as follows: 

1. Choose Load from file. 

2. Select the file that contains the required list of tables. 

Note: The supported file type is .csv. 

5. If you are using the load controller infrastructure, choose Next and enter the operating system user name and 

password. 

6. Choose Finish. 

Suspending and Resuming Data Load 

If you are using SLT- based replication, you can choose to stop data replication temporarily for a selected list of 

tables, and later resume data load for these. 

1. In the Quick Launch tab page, choose Data Provisioning. 

2. Select the source system for which you want to suspend or resume data load. 

3. Choose Suspend or Resume as required. 

4. Select the tables, and choose Add. 


Uploading Data from Flat Files 

Use this procedure to upload data from flat files available in a client file system, to SAP HANA database. 

● If the table schema corresponding to the file to be uploaded already exists in the SAP HANA database, the 

new data records are appended to the existing table. 

● If the required table for loading the data does not exist in the SAP HANA database, create a table structure 

based on the flat file. 

The application suggests the column names and data types for the new tables and allows you to edit them. The 

new table always has a 1:1 mapping between the file and table columns. The application does not allow you to 

overwrite any columns or change the data type of existing data. The supported file types are .csv, .xls, and .xlsx. 

1. In the File menu, choose Import. 

2. In the Select an import source section, expand the SAP HANA content node. 

3. Select Data from Local File, and choose Next. 

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4. In the Target System section, select the target system to which you want to import the data using the flat file, 

and choose Next. 

5. In the Define Import Properties page, browse and select the file containing the data you want to load. 

6. If you have selected a CSV file, select a delimiter. 

Note: A delimiter is used to determine columns and pick the correct data from them. In a csv file, the 

accepted delimiters are ',', ';' and ':'. 

7. If you have selected an .xls or .xlsx file, select a worksheet. 

8. If you want to load the data into a new table, select the New option and perform the following substeps: 

a. Choose Next. 

b. On the Manage Table Definition and Data Mapping screen, map the source and target columns. 

Note: 

○ Only 1:1 column mapping is supported. You can also edit the table definition by changing the 

data types, renaming columns, adding or deleting the columns, and so on. 

○ You can choose to map the source and target columns using the Auto Map option. If you 

choose the one to one option, then first column of the source is mapped to the first column at 

the target. If you choose the option Map by name, the source and target columns with the 

same name are mapped. 

9. If you want to append the data to an existing table, select the Existing option and perform the following 

substeps: 

a. Choose Next. 

b. On the Manage Table Definition and Data Mapping screen, map the source and target columns. 

10. If you want to provide a constant value for a column at the target, perform the following substeps: 

a. Right-click the column. 

b. From the context menu, choose Make As Constant. 

c. In the Constant dialog box, enter a value, and choose OK. 

Note: You can set a column to constant if it is not mapped to a source column. 

11. To provide a default value for a column at the target, enter a value in the Default Value column. 


6.1.5 Copying Content Delivered by SAP 

You have the following privileges: 

● REPO.READ for the source package. 

● REPO.MAINTAIN_NATIVE_PACKAGES and REPO.EDIT_NATIVE_OBJECTS for the root package. 



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Use this functionality for one of the most common scenarios, that is, to copy the standard content shipped by SAP 

or an SAP partner to your local package to meet your modeling and reporting use cases. For example, from 

sap.ecc.fin to customer.ecc.fin. 

Tip: We recommend you copy the content shipped by SAP or an SAP partner to your local package to 

avoid overwriting your changes during the subsequent import. 

You can also use this procedure to copy objects, other than SAP-shipped in a package to other packages in the 

same system based on your business use case. 

Caution: If you copy an object but not its dependent objects (if any), the copied object in the target 

package will have references to the dependent objects in the source package. 

To copy the objects, you need to map the source root packages to the target root packages. You need to activate 

the copied objects in the target package to consume them for reporting purposes. 

Restriction: For script-based calculation views and procedures, even if you copy the dependent objects, 

you need to change the script manually and adjust the dependent object references. 

1. In the Quick Launch tab page, choose Mass Copy. 

2. To create a mapping between the source package and the target package, perform the following substeps: 

a) Choose Add. 

b) Select a source package and a target package, and choose Next. 

Tip: If you want to create more package mapping, select the source and target packages as 

required. 

c) Select the required objects, and choose Add. 

3. Choose Next to view the summary. 

Tip: You can deselect an object to avoid copying it to the target package. 

4. Choose Finish to confirm content copy. 

6.1.6 Mapping the Authoring Schema to the Physical Schema 

Schema mapping is done when the physical schema in the target system is not the same as the physical schema 

in the source system, usually in a transport scenario. The schema mapping is maintained via a mapping table. 

You use this procedure to map the authoring schemas to the physical database schemas in the target system to 

access and deploy the transported objects. 

A physical schema is the schema in which the tables are available. It may differ in the source and target systems. 

An authoring schema (logical schema) is the physical database schema in the source system with which the 

content objects are created. 

Content object definitions are stored in the repository, and contain references to the physical database schemas. 

When you copy the content objects to a different system, for example, from an SAP system to a customer system, 

or between customer systems, the object definition still refers to the physical database schemas at the source. To 

resolve this, you use schema mapping. 

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Remember: Schema mapping only applies to references from repository objects to catalog objects. It is 

not intended to be used for repository to repository references. 

Restriction: You need to map the references of script-based calculation views and procedures manually, 

that is, by changing the script. 

You can map several authoring schemas to the same physical schema. For example, content objects delivered by 

SAP refer to different authoring schemas, whereas in the customer system, all these authoring schemas are 

mapped to a single physical schema where the tables are replicated. 

Remember: The mapping between authoring and physical schema is stored in the configuration table 

“_SYS_BI”.”M_SCHEMA_MAPPING” 

Note: 

● In a system having no schema mapping, the authoring schema is filled 1:1 from the physical schema 

otherwise it would not be possible to change the default schema. 

● In a system if authoring schema mapping is found, it is checked that whether the current authoring 

schema is mapped to the current physical schema as follows: If yes, nothing is done. If not (including 

an empty authoring schema case), then the authoring schema is filled. With the backwards mapped 

authoring schema if there is a 1:1 mapping i.e. only one authoring schema was found. With this we 

simplify the mapping table in customer systems because even for enhancements the content schema 

is kept and no additional mapping must be introduced if the customer transports from development 

to production With the physical schema in case no or more than one authoring schemas are found. 

This indicates that the customer has changed the schema-dependent parts and that therefore his 

physical schema is stored also in the authoring schema. 

Example use case: Lets assume we have only SAP_ERP -> ERP in the mapping table and an analytic 

view having defaultSchema = SAP_ERP. Let's assume the customer changes the defaultSchema to 

CUS. Since CUS has no mapping the authoringSchema of the defaultSchema is set to CUS as well. 

Then the customer changes the defaultSchema back to ERP. A 1:1 mapping for ERP is found 

(SAP_ERP) and then the authoring schema is set back to SAP_ERP. 

1. In the Quick Launch tab page, choose Schema Mapping. 

2. Choose Add. 

3. Enter the authoring schema and physical schema that need to be mapped. 

4. Choose OK. 



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Consider a source system, SAP, with an information object, AV1. This refers to the table MARA in the 

SAP_ERP physical database schema. There is a target system, Customer, with the physical database 

schema EMEA. 

After you import content, the object AV1 cannot be activated in the Customer system, since it still refers 

to SAP_ERP schema. 

AV1 in the Customer system currently refers to SAP_ERP. To be able to activate the object, you need to 

modify the mapping of AV1 in the Customer system. 

To do this, a mapping is created in the target system Customer between the authoring and physical 

schema as follows: 

Authoring Schema Physical Schema 

SAP_ERP EMEA 

6.1.7 Generating Time Data 

For modeling a business scenario that requires time dimension, you can populate time data in the default time- 

related tables present in _SYS_BI schema, for example while creating time attribute views. You can choose to 

generate the time data for a given time span based on your requirements such as, calendar type and granularity. 

If you model a time attribute view without generating time data, when you use data preview an empty view is 

shown. Note that if you populate the data before modeling time attribute views, you can use the Value Help from 

the respective time tables. 

1. In the Quick Launch tab page, choose Generate Time Data. 

2. If your financial year is same as that of the calendar year, that is, January to December, in the Calendar Type 

dropdown, select Gregorian. 

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a) Enter the period for which you want to generate time data. 

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) Select the required granularity 

c) Choose Generate. 

Note: If the selected granularity is Week or Month, specify the First day of the week. 

System populates the generated time data in M_TIME_DIMENSION_YEAR, M_TIME_DIMENSION_MONTH, 

M_TIME_DIMENSION_WEEK, M_TIME_DIMENSION tables in _SYS_BI schema. 

3. If your financial year is not same as that of the Calendar Year for example, March to April, , in the Calendar 

Type dropdown, select Fiscal. 

a) Enter the period for which you want to generate the time data. 

b) Select the Variant Schema where tables containing variant data are maintained. 

Note: Tables T009 and T009B contains Variants information. 

c) Select the required variant that specifies the number of periods along with their start and end dates 

according to your use case. 

d) Choose Generate. 

System populates the generated time data in M_FISCAL_CALENDAR table present in the _SYS_BI schema. 

6.2 Creating Views 

6.2.1 Attributes and Measures 

Attributes and measures form the content data that is used for modeling. While attributes represent the 

descriptive data like city and country, measures represent quantifiable data like revenue and quantity sold. 

Attributes 

Attributes are the individual non-measurable analytical elements. 

● Simple Attributes 

Simple attributes are individual non-measurable analytical elements that are derived from the data 

foundation. 

For example, PRODUCT_ID and PRODUCT_NAME are attributes of a PRODUCT subject area. 

● Calculated Attributes 

Calculated attributes are derived from one or more existing attributes or constants. 

For example, deriving the full name of a customer (first and last name), assigning a constant value to an 

attribute that can be used for arithmetic calculations. 

● Private Attributes 

Private attributes used in an analytic view allow you to customize the behavior of an attribute for only that 

view. 

For example, if an analytic view or a calculation view include an attribute view, it inherits the behavior of the 

attributes from the attribute view (set the parameter once and it is replicated in all views consuming it). 



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By contrast, if you create an analytic view for one specific use case in which you want a particular attribute to 

behave differently than it does in the attribute view to which it belongs, you can define it as a private attribute. 

Measures 

Measures are simple measurable analytical elements. Measures are derived from analytic and calculation views. 

● Simple Measures 

A simple measure is a measurable analytical element that is derived from the data foundation. 

For example, PROFIT. 

● Calculated Measure 

Calculated measures are defined based on a combination of data from OLAP cubes, arithmetic operators, 

constants, and functions. 

For example, calculated measures can be used to calculate the total sales of a product across five regions, or 

to assign a constant value to a measure for a calculation. 

● Restricted Measure 

Restricted measures are used to filter the value based on the user-defined rules for the attribute values. 

● Counters 

Counters add a new measure to the calculation view definition to count the recurrence of an attribute. For 

example, to count how many times Product appears. 

Note: 

You can choose to hide the attributes and measures that are not required for client consumption. For 

example, for a complex calculation that is derived from a series of computations, you can hide the levels of 

computations that are not required for reporting purposes. 

6.2.2 Attribute Views 

Attribute views are used to model an entity based on the relationships between attribute data contained in 

multiple source tables. 

For example, customer ID is the attribute data that describes measures (that is, who purchased a product). 

However, customer ID has much more depth to it when joined with other attribute data that further describes the 

customer (customer address, customer relationship, customer status, customer hierarchy, and so on). 

You create an attribute view to locate the attribute data and to define the relationships between the various tables 

to model how customer attribute data, for example, will be used to address business needs. 

You can model the following elements within an attribute view: 

● Columns 

● Calculated Columns 

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● Hierarchies 

Note: In the Semantics node, you can classify the columns as attributes and build calculated columns 

of attribute type. 

Note: For more information about the attributes and hierarchies mentioned above, see sections 

Attributes and Measures, and Hierarchies. 

You can choose to further fine-tune the behavior of the attributes of an attribute view by setting the properties as 

follows: 

● Filters to restrict values that are selected when using the attribute view. 

● Attributes can be defined as Hidden so that they can be used in processes but are not visible to end users. 

● Attributes can be defined as key attributes and used when joining multiple tables. 

● The Drill Down Enabled property can be used to indicate if an attribute is available for further drill down when 

consumed. 

Attribute views can later be joined to tables that contain measures within the definition of an analytic view or a 

calculation view to create virtual star schema on the SAP HANA data. 

6.2.3 Creating Attribute Views 

Attribute views are used to define joins between tables, and to select a subset (or all) of the table's columns and 

rows. The rows selected can also be restricted by filters. One application of attribute views is to join multiple 

tables together when using star schemas, to create a single dimension table. The resultant dimension attribute 

view can then be joined to a fact table via an analytic view to provide meaning to its data. In this use case, the 

attribute view adds more columns and also hierarchies as further analysis criteria to the analytic view. In the star 

schema of the analytic view, the attribute view is shown as a single dimension table (although it might join multiple 

tables), that can be joined to a fact table. For example, attribute views can be used to join employees to 

organizational units which could then be joined to a sales transaction via an analytic view 

You have imported T009 and T009B tables for creating attribute view of type Time. 

Use this procedure to create a view that is used to model descriptive attribute data (that does not contain 

measures) using attributes. 

Tip: You need this view for creating a multidimensional view. 

1. Set Parameter 

1. In the Modeler perspective, expand the Content node of the required system. 

2. Expand the package to which you want to save your information object. 

3. In the context menu of Attribute Views node, choose New . 

4. Enter a name and description for the view. 

5. To create data foundation for the view, perform substeps of the required scenario given in the table 

below: 

Scenario Substeps 

Create a view with table 

attributes. 



In the Sub Type dropdown list, choose Standard. 

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Create a view with time 

characteristics. 

Copy a view from an 

existing view – in this case, 

you can modify the copied 

view. 

Derive a view from an 

existing view – in this case, 

you cannot modify the 

derived view that acts as a 

reference to the base 

attribute view. 


1. In the Sub Type dropdown list, choose Time. 

2. Select the required calendar type as follows: 

a. If the calendar type is Fiscal, select a variant schema, and a fiscal 

variant. 

b. If the calendar type is Gregorian, select the granularity for the 

data. 

3. To use the system-generated time attribute view, select Auto Create. 

Note: 

The system creates a time attribute view based on the default 

time tables, and defines the appropriate columns/attributes 

based on the granularity. It also creates the required filters. 

Note: The tables used for time attribute creation with calendar 

type Gregorian are, M_TIME_DIMENSION, M_TIME_DIMENSION_ 

YEAR, M_TIME_DIMENSION_ MONTH, 

M_TIME_DIMENSION_WEEK and for calendar type Fiscal is 

M_FISCAL_CALENDAR. If you want to do a data preview for the 

created attribute view, you need to generate time data into the 

mentioned tables from the Quick Launch tab page. 

1. Choose Copy From. 

2. Select the required attribute view. 

1. In the Sub Type dropdown, choose Derived. 

2. Select the required attribute view. 

The attribute view editor opens. The Scenario panel of the editor consist of two nodes - Data Foundation and 

Semantics. The Data Foundation node represents the tables used for defining the output structure of the view. 

The Semantics node represents the output structure of the view, that is, the dimension. In the Details panel 

you define the relationship between data sources and output elements. 

2. Define Output Structure 

106 

a) Add the tables that you want to use in any of the following ways: 

○ Drag the required tables present in the Catalog to the Data Foundation node. 

○ Select the Data Foundation node in the Scenario panel, and in the context menu of the Details panel, 

choose Add. 

Note: You can choose to add the same table again in Data Foundation using table aliases in the 

editor. For example, in cases where you want to have different cardinalities from the same table. 

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Restriction: It is not allowed to add column views to the Data Foundation. 

b) If you want to query data from more than one table, in the Details panel context menu, choose Create 

Join, and enter the required details. 

Note: After creating the join, you can edit its properties like join type, cardinality, etc in the 

Properties view. You can choose to create Text Join between table fields in order to get languagespecific 

data. For example, consider that you have a product table that contains product IDs and 

no description about products, and you have a text table for products that has a language-specific 

description for each product. You can create a text join between the two tables to get languagespecific 

details. In a text join, the right table should be the text table and it is mandatory to specify 

the Language Column. 

c) Add the table columns to the output structure that is, the Semantics node that you want to use to define 

attribute data. You can define the attribute data by doing one of the following: 

○ Select the toggle button on the left of the table field. 

○ Right-click the table field, and choose Add to Output. 

d) If you want to specify a filter condition based on which system must display data for a table field in the 

output do the following: 

1. Right-click the table field, and choose Apply Filter. 

2. Select the required operator, and enter filter values. 

All the table fields that you have added to the output are automatically mapped as attributes. 

3. Define Key Attributes 

a) Select the Semantics node. 

b) In the Attributes tab page of the Column panel, select the required attribute and select the Type as Key 

Attribute. 

Remember: If there is more than one key attribute, all key attributes of the attribute view must 

point to the same table in the data foundation. The central table of the attribute view is the one to 

which all the key attributes point. 

Note: In case of auto-generated time attribute views, the attributes and key attributes are 

automatically assigned. 

4. Optional Step: Create Calculated Columns 

a) In the Output of Data Foundation panel, right-click Calculated Columns. 

b) In the context menu, choose New. 

c) Enter a name and description (label) for the calculated column. 

d) Select a data type for the calculated column. 

e) Enter length and scale for the calculated coulmn. 

f) In the Expression Editor enter the expression. For example, you can write a formula such as, 

if("PRODUCT" = 'ABC', "DISCOUNT" * 0.10, "DISCOUNT"). This means if attribute PRODUCT equals the 

string ‘ABC’ then DISCOUNT equals to DISCOUNT multiplied by 0.10 should be returned. Otherwise the 

original value of attribute DISCOUNT should be used. 

g) Choose OK. 



Note: The expression can also be assembled by dragging and dropping the expression elements 

from the menus below the editor window. 

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5. Optional Step: To filter and view the table data in the modeled view, which is relevant to a specific client as 

specified in the table fields, such as, MANDT or CLIENT, at runtime perform the following: 

1. Select the Semantics node, in the Properties panel edit the Default Client property. 

Note: The default value for the property is the one that is specified as a preference. At runtime, if the 

property is set to Dynamic then, the value set for the Session Client property is used to filter table 

data. The Session Client property is set while creating a user. 

Note: You can choose to create hierarchies in order to define relationships between attributes. 

Note: 

You can choose to associate an attribute with another attribute, which describes it in detail. For 

example, when reporting via Label Mapping (also known as Description Mapping), you can associate 

Region_ID with Region_Text. 

Before SP05, you could associate an attribute with another attribute in a model. In the runtime 

object an .description column is generated and is shown during data preview. Now, from 

SP05 onwards the behavior is as follows: 

○ For an attribute (CUSTOMER) you can now maintain label mapping by selecting another 

attribute (TEXT) from the same model as "Label Column" in the Semantics node. The result is 

"TEXT" displaying as the label column in data preview. Note that the CUSTOMER.description 

column is not generated and is not shown in data preview anymore. 

○ If you have created an object using the old editor (which supported the old style of description 

mapping) and try to open it using the new editor you will see a new column 

CUSTOMER.description (as an attribute) which is hidden and disabled because this column 

cannot be used in other places such as parameter/variable, calculated column, restricted 

column and so on. You cannot maintain properties for this attribute for example, description. 

CUSTOMER.description displays in the data preview as long as you do not change it in the 

editor. You can change its name. After changing the name you can maintain its properties and 

use it like other attributes. 

6. Activate the view using one of the following options in the toolbar: 

○ Save and Activate - to activate the current view and redeploy the affected objects if an active version of 

the affected object exists. Otherwise only current view gets activated. 

○ Save and Activate All - to activate the current view along with the required and affected objects. 

Note: You can also activate the current view by selecting the view in the Navigator panel and choosing 

Activate in the context menu. 

You can find the activated model in the related package. If you want to modify this model, from the context menu, 

choose Open and make the necessary changes. 

108 

Restriction: The behavior of attribute views with the new editor is as follows: 

● When an object (a table of an attribute view) is removed and added again in an attribute view in order 

to reflect the recently modified columns with its data type, it reflects the previous state of the columns 

alone. For more information, see SAP Note 1783668. 

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Related Links 

● When you open an attribute view and there is a missing column in the required object, an error is 

shown and the editor does not open. For information regarding the solution of this issue, see SAP 

Note 1788552. 

Creating Hierarchies [page 127] 

Activating Objects [page 132] 

Generating Time Data [page 102] 

6.2.4 Analytic Views 

Analytic views are used to model data that includes measures. 

For example, an operational data mart representing sales order history would include measures for quantity, 

price, and so on. 

The data foundation of an analytic view can contain multiple tables. However, measures that are selected for 

inclusion in an analytic view must originate from only one of these tables (for business requirements that include 

measure sourced from multiple source tables, see calculation view ). 

Analytic views can be simply a combination of tables that contain both attribute data and measure data. For 

example, a report requiring the following: 

 

Optionally, attribute views can also be included in the analytic view definition. In this way, you can achieve 

additional depth of attribute data. The analytic view inherits the definitions of any attribute views that are included 

in the definition. For example: 

 

You can model the following elements within an analytic view: 

● Columns 

● Calculated Columns 

● Restricted Columns 

● Variables 

● Input parameters 

Remember: In the Semantics node, you can classify columns and calculated columns as type 

attributes and measures. The attributes you define in an analytic view are Local to that view. However, 

attributes coming from attribute views in an analytic view are Shared attributes. For more information 

about the attributes and measures mentioned above, see section Attributes and Measures. 

Note: For more information about the variables and input parameters mentioned above, see sections 

Assigning Variables and Creating Input Parameters. 

You can choose to further fine-tune the behavior of the attributes and measures of an analytic view by setting the 

properties as follows: 

● Filters to restrict values that are selected when using the analytic view. 

● Attributes can be defined as Hidden so that they are able to be used in processes but are not viewable to end 

users. 



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● Attributes can be defined as key attribute and used when joining multiple tables. 

● The Drill Down Enabled property can be used to indicate if an attribute is available for further drill down when 

consumed. 

● Aggregation type on measures 

● Currency and Unit of Measure parameters (you can set the Measure Type property of a measure, and also in 

Calculated Column creation dialog, associate a measure with currency and unit of measure) 

6.2.5 Creating Analytic Views 

Analytic views are typically defined on a fact table that contains transactional data (as measures). Using analytic 

views you can create a selection of measures, add attributes and join attribute views. 

Analytic views leverage the computing power of SAP HANA to calculate aggregate data, e. g. the number of sold 

cars per country, or the maximum power consumption per day. They are defined on only one fact table, a table 

which contains for example, one row per sold car or one row per power meter reading, or some form of business 

transaction records. Fact tables can be joined to allow access to more detailed data using a single analytic view as 

long as the facts (measures) come from a single table. Analytic views can be defined in a single table, or in joined 

tables. 

Analytic views can contain two types of columns, attributes and measures, for which measures are of type simple, 

calculated, and restricted. Measures are attributes for which an aggregation must be defined. If analytic views are 

used in SQL statements then the measures have to be aggregated e. g. using the SQL functions SUM(), MIN(), or MAX(). Normal columns can be handled as regular attributes. 

They do not need to be aggregated. 

1. Set Parameters 

a) In the Modeler perspective, expand the Content node of the required system. 

b) Select the package in which you want to save your information object. 

c) From the context menu of the package, choose New Analytic View . 

Note: Once you have an analytic view in a package, you can also create another one from the 

context menu of the Analytic View node in the respective package. 

d) Enter a name and description for the view. 

e) If you want to create a view based on the existing one, choose Copy From option, and select the required 

view. 

f) Choose Finish. 

The analytic view editor opens. The Scenario panel of the editor consist of the following three nodes: 

○ Data Foundation - represents the tables used for defining the fact table of the view. 

○ Logical Join - represents the relationship between the selected table fields (fact table) and attribute views 

that is, used to create the star schema. 

○ Semantics - represents the output structure of the view. 

In the Details panel you define the relationship between data sources and output elements. 

2. Define Output Structure 

110 

a) Add the tables that you want to use in any of the following ways: 

○ Drag the required tables present in the Catalog to the Data Foundation node. 

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○ Select the Data Foundation node in the Scenario panel, and in the context menu of the Details panel, 

choose Add Tables. 

Note: You can choose to add the same table again in Data Foundation using table aliases in the 

editor. For example, if you want to have different cardinalities from the same table. 

Restriction: It is not allowed to add column views to the Data Foundation of an analytic view. 

However, you can add column views in a calculation view. 

Remember: If there is more than one table, you need to specify one of the tables as the central 

table (fact table) from which the measures will be derived. You can specify the central table by 

selecting a value in the Central Entity property of the Data Foundation node. 

b) If you want to query data from more than one table, in the Details panel context menu, choose Create 

Join, and enter the required details. 

Tip: After specifying the central table or choosing one of the field as measure, when you save the 

view automatic assignment of attributes and measures is done. All the numeric fields from the 

central table are assigned as measures and others as attributes. In this case, you will not be able 

to join measures with other numeric fields. Also, if you have specified all the attributes and 

measures of the view before saving it, automatic assignment of attributes and measures will not 

overwrite them. 

Note: After creating the join, you can edit its properties such as join type, cardinality, etc in the 

Properties view. You can choose to create a Text Join between table fields in order to get language 

specific data. For example, consider that you have a product table that contains product IDs but 

no product description, and you have a text table for products that has language-specific 

description for each product. You can create a text join between the two tables to get languagespecific 

details. In a text join, the right table should be the text table and it is mandatory to specify 

the Language Column. 

c) Add the table columns to the output structure (Semantics node) that you want to use to define the facts 

in any of the following ways: 

○ Select the toggle button on the left of the table field. 

○ Right-click the table field, and choose Add to Output. 

d) If you want to specify a filter condition based on which system must display data for a table field in the 

output, for example to display revenue for only selected companies based on the filter value, do the 

following: 

1. Right-click the table field, and choose Apply Filter. 

2. Select the required operator, and enter filter values. 

The table fields selected above form the fact table. 

e) To create a star schema that is, linking the fact table with the descriptive data (attribute views), do the 

following: 

1. Add the required attribute views in the Logical Join node in any of the following ways: 

○ Drag the required attribute views present in the Content node to the Logical Join node. 

○ Select the Logical Join node in the Scenario panel, and choose Add button to add the attribute 

views. 

2. Create joins between the views and fact table. 



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Note: In the Logical Join, you can create a temporal join between the date field of the fact 

table to an interval (to and from) field of the attribute view. The temporal join has to start from 

the fact table such that the single column must be in the fact table and, the to and from 

columns must be in the table that is directly joined to the fact table. The join type must be a 

referential join. The supported data types are timestamp, date, and integer. 

Restriction: While creating joins you must ensure that a table does not appear twice in any join path (in 

particular a self join is not supported). A join path is the set of joins that links the fact table to other 

tables. 

While creating joins between analytic view and attribute view the same table cannot be used both in 

the join path of analytic view and attribute view. Also, in a join path of analytic view and attribute view, 

the table of the attribute view which is linked to the fact table should not have an alias table. 

3. Optional Step: Create Calculated Column 

a) In the Output of Logical Join panel, right-click Calculated Columns. 

b) In the context menu, choose New. 

c) Enter a name and description (label) for the calculated column. 

d) Select a data type, and enter the length and scale for the calculated column. 

e) Select the Column Type to determine whether it is a calculated attribute or a calculated measure. 

f) If you select Calculate Before Aggregation, select the aggregation type. 

Note: If you select Calculate Before Aggregation, the calculation happens as per the expression 

specified and then the results are aggregated as SUM, MIN, MAX or COUNT. If Calculate Before 

Aggregation is not selected, the data is not aggregated but it gets calculated as per calculation 

expression (formula), and the aggregation is shown as FORMULA. If the aggregation is not set, 

then it will be considered as an attribute. 

g) In the Expression Editor enter the expression. For example, you can write a formula: 

if("PRODUCT" = 'ABC, "DISCOUNT" * 0.10, "DISCOUNT") which is equivalent to, if attribute PRODUCT 

equals the string ‘ABC’ then DISCOUNT equals to DISCOUNT multiplied by 0.10 should be returned. 

Otherwise the original value of attribute DISCOUNT should be used. 

Note: The expression can also be assembled by dragging and dropping the expression elements 

from the menus below the editor window. 

h) If you want to associate the calculated column with currency and unit of measuring quantity, select the 

Advanced tab page and select the required Type. 

i) Choose OK. 

Remember: Calculated Columns can be created only at the Logical Join level and not at the Data 

Foundation level. 

Note: The aggregation type for calculated columns is only taken into account, if they are calculated 

before aggregation 

4. Optional Step: Create Restricted Columns 

112 

You can create restricted columns if you want to filter the value for an output field based on the user-defined 

rules. For example, you can choose to restrict the value for the Revenue column only for Region = APJ, and 

Year = 2012. 

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a) In the Output panel of the Logical Join, right-click Restricted Columns, and choose New. 

b) Enter a name and description for the restricted column. 

c) From the Column dropdown list, select the column for which you want to apply a restriction. 

Caution: The column for which you apply a restriction must be defined as measure in the 

semantics node otherwise the validation will fail. 

d) Choose Add Restriction. 

e) In the Parameter field, select the column that you want to create a restriction for, then select the operator 

and value. 

f) Choose OK. 

Note: For a restricted column the aggregation type of the base column is applied. 

5. Define Attributes and Measures 

a) Select the Semantics node. 

b) In the Column panel, select the Local tab page, and change the type as attributes and measures. 

Note: The Shared tab page shows the attributes of the used attribute views. While generating the 

column views, the joined private attribute name is ignored and the shared attribute name is 

considered, therefore the joined private attribute is not shown on the Semantics node. 

Remember: If the MultiDimensional Reporting property of the analytic view is set to false, the view 

will not be available for reporting purposes. If the value is set to true, an additional column 

Aggregation is available to specify the aggregation type for measures. 

Note: 



You can choose to associate an attribute with another attribute, which describes it in detail. For 

example, when reporting via Label Mapping (also known as Description Mapping), you can 

associate Region_ID with Region_Text. 

Before SP05, you could associate an attribute with another attribute in a model. In the runtime 

object an .description column is generated and is shown during data preview. Now, 

from SP05 onwards the behavior is as follows: 

○ For an attribute (CUSTOMER) you can now maintain label mapping by selecting another 

attribute (TEXT) from the same model as "Label Column" in the Semantics node. The result is 

"TEXT" displaying as the label column in data preview. Note that the CUSTOMER.description 

column is not generated and is not shown in data preview anymore. 

○ If you have created an object using the old editor (which supported the old style of description 

mapping) and try to open it using the new editor you will see a new column 

CUSTOMER.description (as an attribute) which is hidden and disabled because this column 

cannot be used in other places such as parameter/variable, calculated column, restricted 

column and so on. You cannot maintain properties for this attribute for example, description. 

CUSTOMER.description displays in the data preview as long as you do not change it in the 

editor. You can change its name. After changing the name you can maintain its properties and 

use it like other attributes. 

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Note: You can change the type of a measure and perform currency conversion by selecting it in 

the Local tab page and changing the Measure Type property in the properties panel. 

6. Optional Step: You can filter and view the table data in the modeled view for a specific client as specified in the 

table fields, such as MANDT or CLIENT, by doing the following: 

1. Select the Semantics node, in the Properties panel, edit the Default Client property. 

Note: The default value for the property is the one that is specified as a preference. If the property is 

set to Dynamic, at runtime the value set for the Session Client property is considered to filter table 

data. The Session Client property is set while creating a user. 

7. Optional Step: Assign Variable 

You assign variables to a field at design time for obtaining data based on the values you provide for the 

variable. At runtime, you can provide different values to the variable to view the corresponding set of attribute 

data. 

a) In the Semantics node Variables/Input Parameter panel, choose the Create Variable option. 

b) Enter a name and description for the variable. 

c) Select the required attribute from the dropdown list. 

Note: At runtime, the value for the variable is fetched from the selected attribute's data. 

d) Choose the required Selection Type from the dropdown list. 

Note: 

○ Single Value - Used to filter and view data based on a single attribute value. For example, to 

view the sales of a product where the month is equal to January. 

○ Interval - Used to filter and view a specific set of data. For example, to view the expenditure of 

a company from March to April. 

○ Range - Used to filter and view data based on the conditions that involve operators such as: 

○ "="(equal to) 

○ ">" (greater than) 

○ "=" (greater than or equal to) 

○ "

Related Links 

Note: If an active version of the affected objects exist, activating the current view redeploys the 

affected objects. You can also activate an object from the object context menu in the Navigator panel. 

Tip: You can choose to activate the other objects (required or impacted objects) along with the 

currenct object using the Save and Activate All option in the toolbar. 

Note: 

Restriction: The behavior of analytic views with the new editor is as follows: 

○ When an object (a table of or an attribute view) is removed and added again in an attribute 

view and analytic view editor in order to reflect the recently modified columns with its data 

type, it reflects the previous state of the columns . For more information about the 

problem and its solution, see SAP Note 1783668. 

○ When you open an analytic view and there is a missing column in the required object, an 

error is shown and the editor does not open. For information regarding the solution of this 

issue, see SAP Note 1788552. 

Using Currency and Unit of Measure [page 130] 


Creating Input Parameters [page 125] 

6.2.6 Calculation Views 

A calculation view is used to define more advanced slices on the data in SAP HANA database. Calculation views 

can be simple and mirror the functionality found in both attribute views and analytic views. However, they are 

typically used when the business use case requires advanced logic that is not covered in the previous types of 

information views. 

For example, calculation views can have layers of calculation logic, can include measures sourced from multiple 

source tables, can include advanced SQL logic, and so on. The data foundation of the calculation view can include 

any combination of tables, column views, attribute views and analytic views. You can create joins, unions, 

projections, and aggregation levels on the sources. 

You can model the following elements within a calculation view: 

● Attributes 

● Measures 

● Calculated measures 

● Counters 

● Hierarchies (created outside of the attribute view) 

● Variables 

● Input parameters 



Note: For more information about the attributes, measures, counters, and hierarchies mentioned 

above, see sections Attributes and Measures, and Hierarchies. 

Note: For more information about the variables and input parameters mentioned above, see sections 

AssigningVariables and Creating Input Parameters. 

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Calculation views can include measures and be used for multi-dimensional reporting or can contain no measures 

and used for list-type of reporting. Calculation views can either be created using a graphical editor or using a SQL 

editor. These various options provide maximum flexibility for the most complex and comprehensive business 

requirements. 

6.2.7 Creating Calculation Views 

Calculation views are used to provide composites of other views. Essentially they are based on a join or union of 

two or more data flows or on invoke of built-in or generic SQL functions. 

Calculation views are defined as either graphical views or scripted views but not as SQLScript (for exceptions, see 

below) depending on how they are created. They can be used in the same way as analytic views, however, in 

contrast to analytic views it is possible to join several fact tables in a calculation view. 

Graphical views can be modeled using the graphical modeling features of the SAP HANA Modeler. Scripted views 

are created as sequences of SQL statements. 

As mentioned previously calculation views are generally not created using SQLScript. There are however, 

exceptions to this rule. SQLScripts with the following properties can be used in calculation views: 

- No input parameters 

- Always read-only (that is, do not make changes to the database) 

- Side-effect free 

You can use calculation views to derive values and key performance indicators(KPIs). 

Note: The terms "attribute" and "columns" are used interchangeably in this procedure. They may denote a 

table column, a particular data field of a table row, or the contents of such a data field. The respective 

meaning should be clear from the context. 

Procedure 

1. In the Modeler perspective, expand the system node from the Navigator pane. 

2. Expand the Content node. 

3. Right-click the required package. 

4. From the context menu, choose New Calculation View . 

a. Enter a name and description. 

b. Select the required package. 

Create a Script-Based Calculation View 

1. Choose SQL Script. 

2. Select the required schema from the Default Schema dropdown list, for unqualified access in SQL. 

Note: If you do not select a default schema, while scripting, you need to provide fully qualified names 

of the objects used. 

3. Select the required option from the Run With dropdown list, which identifies whose rights are to be considered 

116 

while executing the calculation scenario. 

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Note: 

Definer's right: If you want system to use the rights of the definer while executing the view or 

procedure for any user. 

Invoker's right: If you want system to use the rights of the current user while executing the view or 

procedure . 


5. Define the Output Structure 

a. Choose Define Output Parameter from the Output pane. 

b. To add the output parameters with the required data type and length, from the Output pane toolbar, 

choose Define Output Parameter button. 

c. Choose OK. 

6. Define the Function 

Note: The order and data types of the output parameters should match the table columns order 

and data type which is used in the select query. 

a. Define the function using SQL Script commands. 

Note: 

7. Save and Activate 

○ You can create variables, and bind them to attributes for filtering data. The values you provide 

for the variables at runtime determine which data records are selected for consumption. 

○ You can create input parameters for the calculation view that works as a placeholder in a 

query. 

○ You can create a hierarchy between attributes of the view. 

a. To save the view, choose File Save . 

b. From the context menu of the calculation view, choose Activate. 

Create a Graphical Calculation View 

1. Choose Graphical. 

2. Select the required schema from the Schema for Conversion dropdown list. 

Note: The schema selected for conversion is used during the currency conversion. It list down all the 

schemas which has currency related tables and the same can be changed during design time from the 

properties. 

3. Choose Next. 

4. Follow the instructions in the wizard to select the required tables and content models. 



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118 

Adding Unions/Joins/ Projections/ Aggregation 

a. From the Tools Palette, choose the required option as follows: 

View Description 

Union Used to combine the result set of two or more data 

sources. For example, to show the names of all the 

employees of a store which has different branches each 

maintaining its own employee records table. 

Join Used to query data from two or more data sources, 

based on a specified condition. For example, to retrieve 

the sales of two stores maintaining individual table for 

sales based on the customer ID. 

Projection Used to filter or create a subset of the required columns 

of a table or view for creating the model. For example, 

selecting the employee name and sales quantity from a 

table consisting of many more columns. 

Aggregation Used to summarize data of a group of rows by 

calculating values in a column. For example, to retrieve 

total sales of a product in a month. The supported 

aggregation types are sum, min, and max. 

Note: 

○ The input for union, join, projection, and aggregation views can consist of data sources, union, 

join, projection, or aggregation views. 

○ You can have only one source of input for aggregation and projection views. 

○ You can choose to create filters on projection and aggregation view attributes. 

b. Map the input to the selected option. 

Mapping attributes 

a. To map attributes in a union view, drag and drop the required columns from Source to Target. 

You can also modify the attribute mapping. For more information, see Managing Attribute Mappings 

[page 122] 

Tip: To create a system generated mapping, choose Auto Map By Name. 

b. In case of a join view, join the columns of the source data sources. 

Note: 

○ The output of a union view is the attributes that you added to the Target. 

○ The output of a join view is the joined attributes. However, to add additional attributes to the 

view's output, from the context menu, choose Add to Output. 

○ To add attributes of projection or aggregation view to its output, choose Add to Output from 

the context menu. 

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Optional Step: Creating Calculated Columns 

The output of union, join, or projection view is stored under the Column node in the Output panel.To 

perform calculations on these columns, do the following: 

1. Right-click the Calculated Columns node. 

2. From the context menu, choose New. 

a. Enter the name. 

b. Select the data type. 

c. Enter the length and scale. 

d. To perform calculations on the output columns, do the following: 

○ If you know the formula, enter the expression to perform the calculation. 

○ From the list, select the required elements, operator, and functions. 

e. Choose Add. 

Optional Step: Applying Filter on Aggregation and Projection View Attributes 

1. Right-click the required attribute. 

2. From the context menu, choose Apply Filter. 

3. Select the required operator. 

4. Enter value. 

5. Choose OK. 

Note: You can edit a filter using filter expressions from the Output pane which provides you 

with more conditions that can be used in the filter including AND, OR, and NOT. For example, 

to retrieve the sales of a product where (revenue >= 100 AND region = India) OR (revenue 

>=50 AND region = Germany). 

Note: In order to define pattern-based filters in calculation views, you use the expression 

editor accessed by double-clicking the expression icon under the filter node of the Output 

panel. If you type 

match("ABC",'*abc*') 

the equivalent SQL is 

. 

where “ABC“ like ‘%abc%’ 

Adding Attributes and Measures to Calculation View Output 

a. From the designer panel, choose the Output node. 

b. To add an attribute, from the context menu, choose Add as Attribute. 



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120 

c. To add a measure, from the context menu, choose Add as Measure. 

Note: You can choose to associate a measure with the currency or unit of measure. To do so, 

select the measure and in the Properties panel select Measure Type. 

d. If you want to create calculated attributes, perform the following substeps: 

a. In the Output pane, right-click Calculated Attributes. 

b. From the context menu, choose New. 

c. Enter a name and description. 

d. On the Key tab, define the formula for the calculated attribute as follows: 

a. Select a data type for the calculated attribute from the dropdown list. 

b. Enter the length and scale. 

c. Select the required attributes, operator, and function. 

d. To check the validity of the formula, choose Validate. 

e. Choose Add. 

e. To add a Description to the calculated attribute, write the formula as above. 

e. If you want to create calculated measures, do the following: 

a. In the Output pane, right-click Calculated Measures. 

b. From the context menu, choose New. 


b. Select the required Aggregation Type. 

c. If you want to hide the measure while previewing data, choose Hidden. 

d. Select the required data type. 

e. Enter the length and scale. 

f. Define the measure by selecting the required measures, operator, and function. 

g. Choose Validate. 

h. Choose OK. 

Note: You can choose to rename the attributes, calculated attributes, measures, and calculated 

measures of the view using the Rename button in the Output panel toolbar. However, renaming a 

field can impact other objects that reuse the field as the new name is not reflected in the other 

objects. 

Optional Step: Creating Counters 

To obtain the number of distinct values of an attribute, do the following: 

1. In the Output pane, right-click Counters. 


3. Choose Add Attribute. 

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4. Choose OK. 

Activate 

Note: 

1. If you set the calculation view property Multidimensional Reporting as disabled, you can 

create a calculation view without adding any measure to the calculation view output. A 

calculation view without any measure works like an attribute view and is not available for 

reporting purposes. 

2. You can choose to hide the attributes and measures that are not required for client 

consumption by assigning value true to the property Hidden in the Properties pane. 

3. You can choose to create variables, and bind them to attributes for filtering data. The values 

you provide to the variables at runtime determine which data records are selected for 

consumption. 

4. You can choose to create input parameters for the union, join, projection, aggregation, and 

calculation view output. Also, if the calculation view data sources have input parameters, you 

can map them to the calculation view input parameters. 

5. You can choose to create hierarchy between attributes of the view. 

6. You can specify a value for the view's Default Client property to filter the table data that is 

relevant to a specific client as specified in the table fields at runtime, such as, MANDT or 

CLIENT. The default value for the property is the one that is specified as a preference. If the 

property is set to Dynamic, at runtime, the value set for the Session Client property is 

considered to filter table data. The Session Client property is set while creating a user. 

a. To activate the view select Save and Activate from the toolbar. 

Note: 

Note: Activating the current view redeploys the impacted objects if an active version of the 

impacted objects exist. You can also activate an object from the context menu of the object in 

the Navigator panel. 

Tip: You can choose to activate the other objects (required or impacted objects) along with 

the current object using the Save and Activate All from the toolbar. 

Note: For more information about activation, see Activating Objects [page 132]. 

1. For an active calculation view, you can preview the data of an intermediate node in a calculation view, 



which helps to debug each level of a complex calculation scenario having join, union, aggregation, 

projection, and output nodes. The data you preview for a node is for the active version of the 

calculation view. If no active version for the object exists then you need to activate the object first. You 

can choose the Data Preview option from the context menu of a node. 

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Related Links 

2. You can choose to generate documentation for the calculation view. For more information, see 

Generating Object Documentation [page 144]. 

Assigning Variables [page 123] 

Creating Input Parameters [page 125] 

Creating Hierarchies [page 127] 

Managing Attribute Mappings [page 122] 

Using Currency and Unit of Measure [page 130] 


Mapping Input Parameters [page 122] 

Mapping Input Parameters 

You use this procedure to map the input parameters in the underlying data sources (analytic views and 

calculation views) of the calculation view to the calculation view parameters. You can: 

● Map many data source parameters to one calculation view input parameter. 

● Perform a one on one mapping of the data source parameters to the calculation view parameters. 

Procedure 

1. In the Output pane, select an input parameter. 

2. In the context menu, choose Manage Mappings. 

3. In the Map Data Source Parameters dialog, map the data source input parameters with the calculation view 

parameters. 

Note: You can choose the Auto Map by Name option to automatically create the input parameters 

corresponding to the source and perform a 1:1 mapping. You can also select a source input parameter 

and use the following context menu options: 

○ Create New Map 1:1 - to create the same input parameter for the calculation view as for the 

source, and create a 1:1 mapping between them. 

○ Map By Name - to map the source input parameter with the calculation view input parameter 

having the same name. 

○ Remove Mapping - to delete the mapping between the source and calculation view input 

parameter. 

Managing Attribute Mappings 

You use this procedure to map the source attribute to the target attribute if there are a large number of attributes, 

or to assign a constant value to the target attribute. 

Procedure 

1. Right-click the attribute in the target list. 

2. From the context menu, choose Manage Mappings. 

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a. To map the source to the target column, select the required source from the dropdown list. 

b. To assign a default value to the constant column, enter the value in the Constant Value field. For more 

information, see Constant Column [page 123]. 

c. Select the required data type. 

d. Enter the length and scale as required. 

e. Choose OK. 

Constant Column 

In a union view, a Constant Column is created if there are any target or output attributes for which there are no 

mappings to the source attributes. The default value for the constant column is NULL. 

Note: The target attribute is mapped to all the sources. 

For example, you have two tables with similar structures, Actual Sales and Planned Sales, corresponding to the 

sales of products. You want to see the combined data in a single view, but differentiate between the data from the 

two tables for comparison. To do so, you can create a union view between the two tables and have a constant 

column indicating constant values like A & P, as shown below: 

Actual Sales 

Sales Product 

5000 A1 

2000 B1 

Planned Sales 

Sales Product 

3000 A1 

6000 B1 

The result of this query can be as follows: 

Actual Planned Indicator Sales Product 

A 5000 A1 

P 3000 A1 

A 2000 B1 

P 6000 B1 

6.2.8 Assigning Variables 

You use this procedure to assign variables to a filter at design time for obtaining data based on the values you 

provide for the variable. At runtime, you can provide different values to the variable to view the corresponding set 

of attribute data. You provide values to the variables either by entering the values manually, or by selecting them 

from the Value Help dialog. 

Note: You can apply variables to attributes of analytic and calculation views. 

The following types of variables are supported: 



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Type Description 

Single Value Use this to filter and view data based on a single attribute 

value. For example, to view the sales of a product where the 

month is equal to January. 

Interval Use this to filter and view a specific set of data. For example, 

to view the expenditure of a company from March to April. 

Range Use this to filter and view data based on the conditions that 

involve operators such as "="(equal to), ">" (greater than), 

"=" (greater than or equal to), and "


b. Select the required attribute from the dropdown list. 

Note: At runtime, the value for the variable is fetched from the selected attribute's data. 

c. Choose the required Selection Type from the dropdown list. 

d. If you want to specify a default value that is used to filter attribute data, enter the value in the Default 

Value field. 

e. Choose OK. 

Note: You can also choose to create a variable using the Create Variable option from the context menu of 

an attribute. In this case, the details of the variable are pre-filled. 

2. Assign a Variable to a Filter 

1. On the Output panel, right-click the attribute. 

2. In the context menu, choose Apply Filter. 

3. In the Operator dropdown list, choose Variable. 

4. In the Variable dropdown list, choose the required variable. 

5. Choose OK. 

Note: You can also choose to create a variable and apply a filter using the Create Variable - Apply Filter 

option from the context menu of an attribute. 

6.2.9 Creating Input Parameters 

Use this procedure to allow you to provide input for the parameters within stored procedures, in order to obtain a 

desired functionality when the procedure is executed. 

In an analytic view you use input parameters as placeholders during currency conversion and formulas like 

calculated columns. When used in formulas, the calculation of the formula is based on the input that you provide 

at runtime during data preview. Input parameters are not used for filtering attribute data in analytic views that can 

be achieved using variables. 

In calculation views you can use input parameter during currency conversion, calculated measures, input 

parameters of the script node, and to filter data as well. 

You can apply input parameters in analytic and calculation views. If a calculation view is created using an analytic 

view with input parameters, those input parameters are also available in the calculation view but you cannot edit 

them. 

The following types of input parameters are supported: 


Attribute Value/ Column Use this when the value of a parameter comes from an 

attribute. 

Currency (available in Calculation View only) Use this when the value of a parameter is in a currency 

format, for example, to specify the target currency during 

currency conversion. 



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Date (available in Calculation View only) Use this when the value of a parameter is in a date format, for 

example, to specify the date during currency conversion. 

Static List Use this when the value of a parameter comes from a userdefined 

list of values. 

Derived From Table (available in Analytic View and Graphical 

Calculation View) 

Use this when the value of a parameter comes from a table 

column based on some filter conditions and you do not need 

to provide any input at runtime. 

Empty Use this when the value of a parameter could be anything 

from the selected data type. 

Direct Type (available in Analytic View) Use this to specify an input parameter as currency and date 

during currency conversion. 

In the case of analytic views, all input parameters are mandatory. However, in the case of calculation views, each 

type of input parameter can be either mandatory or non-mandatory. For a mandatory input parameter, it is 

necessary to provide a value at runtime. However, for a non-mandatory input parameter, if you do not specify a 

value at runtime, the data for the column in which the input parameter is used remains blank. 

Note: You can check whether an input parameter is mandatory or not from the properties of the input 

parameter in the Properties pane. 

Procedure 

● If you want to create a formula to analyze the annual sales of a product in various regions, you can use 

Year and Region as input parameters. 

● If you want to preview a sales report with data for various countries in their respective currency for a 

Analytic View 

particular date for correct currency conversion, you can use Currency and Date as input parameters. 

1. In the Output panel of the Data Foundation or Logical Join node, right-click the Input Parameters node. 

Note: You can also create input parameters at the Semantics node level, using the Create Input 

Parameter option in the Variables/Input Parameters panel. 


126 


b. Select the type of input parameter from the Parameter Type dropdown list. 

Note: 

○ For the Column type of input parameter, you need to select the attribute from the dropdown 

list. At runtime the value for the input parameter is fetched from the selected attribute's data. 

○ For an input parameter of type Derived from Table, you need to select a table and one of it's 

column as Return Column whose value is then used as input for the formula calculation. You 

can also define conditions to filter the values of Return Column in the Filters panel. For 

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example, to calculate Discount for specific clients, you can create an input parameter based 

on Sales table and return column Revenue with filter set on the Client_ID. 

○ For Direct Type input parameter, specify the Semantic Type that describes the use parameter 

as a currency or date, for example, to specify the target currency during currency conversion. 

c. If required, select a data type. 

d. Enter length and scale for the input parameter. 

e. Choose OK. 

Calculation View 

1. In the Output panel, right-click the Input Parameters node. 



b. Select the type of input parameter from the dropdown list. 

Note: 

c. Select a data type. 

○ For the Attribute Value type of input parameter, you need to select the attribute from the 

dropdown list. At runtime the value for the input parameter is fetched from the selected 

attribute's data. 

○ For an input parameter of type Derived from Table, you need to select a table and one of it's 

column as Return Column whose value is then used as input for the formula calculation. You 

can also define conditions to filter the values of Return Column in the Filters panel. For 

example, to calculate Discount for specific clients, you can create an input parameter based 

on Sales table and return column Revenue with filter set on the Client_ID. 

d. Enter length and scale for the input parameter. 

e. Choose OK. 

6.2.10 Creating Hierarchies 

You use this procedure to create hierarchies between attributes to enhance analysis by displaying attributes 

according to their defined hierarchical relationships. Hierarchies can exist cross-attributes (that is, Country - 

State - City) or within the values of a single attribute (that is, employee manager - employee direct report). 

You structure and define relationships between attributes in the attribute view and calculation view using the 

following hierarchy types: 

● Level Hierarchy 

A level hierarchy is rigid in nature, and the root and the child nodes can be accessed only in the defined order. 

Level hierarchies consist of one or more levels of aggregation. Attributes roll up into the next higher level in a 

many-to-one relationship, and members at this higher level roll up into the next higher level, and so on to the 

top level. 



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For example: an address hierarchy comprised of region, country, state, and so on. 

● Parent/Child Hierarchy 

A parent/child hierarchy is a hierarchy in a standard view that contains a parent attribute. A parent attribute 

describes a self-referencing relationship, or self-join, within the main table. Parent-child hierarchies are 

constructed from a single parent attribute. 

For example: a bill of materials hierarchy (parent and child) or an employee master (employee and manager) 

hierarchy. 

Procedure 

Creating a Level Hierarchy 

1. Select the Semantics node. 

2. In the Hierarchies panel, choose Create option . 

3. Enter a name and description for the hierarchy. 

4. In the Hierarchy Type dropdown, select Level Hierarchy. 

5. Select the required value in the Aggregate All Nodes. 

Note: This option indicates that data is posted on aggregate nodes and should be shown in the user 

interface. For example, if you have the members A with value 100, A1 with value 10, and A2 with value 

20 where A1 and A2 are children of A. By default the value is set to false, and you will see a value of 30 

for A. 

With the value set to true, you will count the posted value 100 for A as well and see a result of 130. 

If you are sure that there is no data posted on aggregate nodes you should set the option to false. The 

engine will then calculate the hierarchy faster as when the option is set. 

Note that this flag is only interpreted by the SAP HANA MDX engine. In the BW OLAP engine the node 

values are always counted. 

6. Enter a value for the default member. 

7. Select the required option in the With Root Node dropdown. 

Note: If a hierarchy doesn't have a root node but needs one for reporting use case, set the option to 

true. This will create a root node. 

8. Select the required value from the Node Style dropdown list. 

128 

Note: Node style determines the composition of a unique node ID. The different values for node styles 

are as: 

○ Level Name - the unique node ID is composed of level name and node name, for example "[Level 

2].[B2]". 

○ Name Only - the unique node ID is composed of level name, for example "B2". 

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○ Name Path - the unique node ID is composed of the result node name and the names of all 

ancestors apart from the (single physical) root node. For example "[A1].[B2]". 

9. Add the required attributes from the drop-down list. 

Note: You can select attributes from the required table columns in the drop-down list to add to the 

view. 

10. Select the required Level Type. 

11. Choose OK. 

Note: The level type is used to specify formatting instructions for the level attributes. 

For example, a level of the type LEVEL_TYPE_TIME_MONTHS can indicate that the attributes of the 

level should have a text format such as "January", and LEVEL_TYPE_REGULAR indicates that a level 

does not require any special formatting. 

Creating a Parent/Child Hierarchy 

1. Select the Semantics node. 

2. In the Hierarchies panel, choose Create option . 

3. Enter a name and description for the hierarchy. 

4. In the Hierarchy Type dropdown, choose Parent Child Hierarchy. 

5. Select the required value in the Aggregate All Nodes. 

Note: This option indicates that data is posted on aggregate nodes and should be shown in the user 

interface. For example, if you have the members A with value 100, A1 with value 10, and A2 with value 

20 where A1 and A2 are children of A. By default the value is set to false, and you will see a value of 30 

for A. 

With the value set to true, you will count the posted value 100 for A as well and see a result of 130. 

If you are sure that there is no data posted on aggregate nodes you should set the option to false. The 

engine will then calculate the hierarchy faster as when the option is set. 

Note that this flag is only interpreted by the SAP HANA MDX engine. In the BW OLAP engine the node 

values are always counted. 

6. Enter a value for the default member. 

7. Select the required option in the With Root Node dropdown. 

Note: If a hierarchy doesn't have a root node but needs to have one for reporting use case, set the 

option to true. This will create a root node. 

8. Select the Parent Node and Child Node from the dropdown list. 

9. Choose OK. 



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Note: The hierarchies belonging to an attribute view are available in an analytic view that reuses the 

attribute view, in read-only mode. However, the hierarchies belonging to an attribute view are not available 

in a calculation view that reuses the attribute view. 

6.2.11 Using Currency and Unit of Measure 

Use this procedure to define a measure as an amount or weight in the analytical space and to perform currency 

conversion. 

To simplify the process of currency conversion, the system provides a list of currencies, and exchange rates 

based on the tables imported for currency. Currency conversion is performed based on source currency, target 

currency, exchange rate, and date of conversion. You can also select currency from the attribute data used in the 

view. 

For example, you need to generate a sales report for a region in a particular currency, and you have sales data in 

database tables in a different currency. You can create an analytic view by selecting the table column containing 

the sales data in this other currency as a measure, and perform currency conversion. Once you activate the view, 

you can use it to generate reports. 

Note: Currency conversion is enabled for analytic views and base measures of calculation views. 

Prerequisites 

● You have imported tables T006 and T006A for Unit of Measure. 

● You have imported TCURC, TCURF, TCURN, TCURR, TCURT, TCURV, TCURW, and TCURX for currency. 

Procedure 

1. Select a measure. 

2. In the Properties pane, select Measure Type. 

3. If you want to associate the measure with a currency, do the following: 

130 

a. In the Measure Type dropdown list, select the value Amount with Currency. 

b. In the Currency Dialog, select the required Type as follows: 

Type Purpose 

Fixed To select currency from the currency table TCURC. 

Attribute To select currency from one of the attributes used in the 

view. 

c. Select the required value, and choose OK. 

d. If you want to convert the value to another currency, choose Enable for Conversion. 

a. To select the source currency, choose Currency. 

b. Select the target currency. 

Note: For currency conversion, in addition to the types Fixed and Attribute, you can select an 

Input Parameter to provide target currency at runtime. If you select an input parameter for 

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specifying target currency and deselect Enable for Conversion checkbox, the target currency 

field is cleared because input parameters can be used only for currency conversion. 

c. To specify exchange rate type, in the Exchange Rate Types dialog, select the Type as follows: 

Type Purpose 

Fixed To select exchange rate from the currency table 

TCURW. 

Input Parameter To provide exchange rate input at runtime as input 

parameter. 

d. To specify the date for currency conversion, in the Conversion Date dialog, select the Type as follows: 

Type Purpose 

Fixed To select conversion date from the calendar. 

Attribute To select conversion date from one of the attributes 

used in the view. 

Input Parameter To provide conversion date input at runtime as input 

parameter. 

e. To specify the schema where currency tables are located for conversion, in the Schema for currency 

conversion, select the required schema. 

f. To specify the client for which the conversion rates to be looked for, in the Client for currency 

conversion, select the required option. 

e. From the dropdown list, select the required value that is used to populate data if the conversion fails: 

Option Result 

Fail In data preview, the system displays an error for 

conversion failure. 

Set to NULL In data preview, the value for the corresponding records 

is set to NULL. 

Ignore In data preview, you view the unconverted value for the 

corresponding records. 

4. If you want to associate a measure with a unit of measure other than currency, do the following: 

a. Select the value Quantity with Unit of Measure in the Measure Type dropdown list. 

b. In the Quantity Units dialog , select the required Type as follows: 

Type Purpose 

Fixed To select a unit of measure from the unit tables T006 

and T006A. 

Attribute To select a unit of measure from one of the attributes 

used in the view. 

c. Select the required value, and choose OK. 

5. Choose OK. 

Note: You can associate currency or unit of measure with a calculated measure, and perform currency 

conversion for a calculated measure by editing it. 



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6.2.12 Activating Objects 

You activate objects available in your workspace to expose the objects for reporting and analysis. Based on your 

requirements, you can do the following: 

● Activate - Deploys the inactive objects. 

● Redeploy - Deploys the active objects in one of the following scenarios: 

○ If your runtime object gets corrupted or deleted, and you want to create it again. 

○ If an object goes through client-level activation and server-level activation but fails at MDX, and the object 

status is still active. 

The following activation modes are supported: 

● Activate and ignore the inconsistencies in impacted objects - To activate the selected objects even if it results 

in inconsistent impacted objects. For example, if you choose to activate an object A that is used by B and C, 

and it causes inconsistencies in B and C but you can choose to go ahead with the activation of A. This is the 

default activation mode. 

● Stop activation in case of inconsistencies in impacted objects - To activate the selected objects only if there 

are no inconsistent impacted objects. 

Note: Irrespective of the activation mode, if even one of the selected objects fails (either during validation 

or during activation), the complete activation job will fail and none of the selected objects will be activated. 

Depending on where you invoke the activation, redeployment or cascade activation, the behavior is as follows: 

Context Activate Redeploy 

Quick Launch tab page A dialog box appears with a preselected 

list of all your inactive objects. 

Package context menu A dialog box appears with a preselected 


Content context menu A dialog box appears with a preselected 


Editor ● If you select Save and Activate, 

current object is activated and the 

impacted objects are redeployed if 

an active version for the impacted 

objects exist. 

● If you select Save and Activate All, a 

dialog box appears with a 

preselected list of the selected 

object along with all the required 

and impacted objects. 

Object context menu A dialog box appears with a preselected 

list of the selected object along with all 

the required objects. 

132 

Note: 

A dialog box appears with a list of active 

objects in your workspace. 

A dialog box appears with a list of active 

objects in your workspace. 

Not applicable 

Not applicable 

A redeployment job is submitted for the 

selected object. 

● If an object is the only inactive object in the workspace, the activation dialog box is skipped and the 

activation job is submitted. 

● If an object is inactive and you want to revert back to the active version, from the editor or object 

context menu, choose Revert To Active. 

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● In the Activate dialog, you can select the Bypass validation checkbox in order to skip validation before 

activation to improve the activation time. For example, if you have imported a number of objects and 

want to activate them without spending time on validation. 

Note: During delivery unit import, full server side activation is enabled, activation of objects after import is 

done. In this case all the imported objects are activated (moved to active table), even if there are errors in 

activated or impacted objects. But the objects for which activation results in error are considered as 

broken or inconsistent objects which means that the current runtime representation of these objects is 

not in sync with the active design time version. The broken objects are shown in the Navigator with an ‘x’ 

along side. 

Note: The behavior of activation job is as follows: 

● The status (completed, completed with warnings, and completed with errors) of the activation job 

indicates whether the activation of the objects is successful or failed. 

● In case of failure that is when the status is completed with errors, the process is rolled back. This 

means, even if there are individual objects successfully activated, since the activation job is rolled 

back, none of the objects are activated. 

● Even in case of failure, the job log shows success in the summary part. This is to help the user to 

indicate that those objects were successfully activated without any issues. But because the entire job 

is a failure, none of the objects are activated and all of them are rolled back. 

● When you open the job log, the summary list shows only those objects that are submitted for 

activation. It does not list all the affected objects. They are listed only in detail section. 

6.3 Creating Decision Tables 

You use this procedure to create a decision table to model related business rules in a tabular format for decision 

automation. Using decision tables you can manage business rules, data validation, data quality rules without any 

IT knowledge on technical languages like, SQL Script, MDX . A data architect or a developer creates the decision 

table and activates it. The active version of the decision table can be used in applications. 

Procedure 

1. Set Parameters 

1. In the Modeler perspective, expand Content . 

2. In the context menu of the package, choose New Decision Table . 

3. In the New Decision Table dialog box, enter a name and description for the decision table. 

4. To create data foundation for the decision table, perform substeps of the required scenario given in the table 

below: 


Create a decision table from scratch. 1. Choose Create New. 



2. Choose Next. 

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Note: If you launch the New Decision Table 

dialog from the Quick Launch tab page, 

specify the package where you want to save 

the decision table. 

3. Add the required tables, table type or an information 

view to the Selected list. 


Create a decision table from an existing decision table. 1. Choose Copy From. 

Note: 

Note: You can choose to add the required 

data sources to the decision table later by 

dragging them from the Catalog node in the 

Navigator panel to the Data Foundation 

panel. 

Note: If you launch the New Decision Table 

dialog from the Quick Launch page, specify 

the package where you want to save the 

decision table. 

2. Select the required decision table. 


○ Only an active version of an information view can be used. Any changes made to the information 

view are not reflected in the decision table. 

○ You can create a decision table using an analytic view only if it has a calculated attribute. 

○ If you create a decision table using an analytic view, the analytic view must have a calculated 

attribute. 

2. Create Joins 

○ If you choose to create a decision table based on a table type or an information view, you cannot 

add any other data source. This implies that a decision table can be based on multiple tables or a 

table type or an information view. 

○ You can add only one table type or information view to the data foundation. 

○ You can mark table type columns and information view columns only as conditions. 

1. If you want to define a relationship between tables to query data from two or more tables, do the following: 

134 

a. In the editor pane, from the context menu, choose Create Join. 

b. In the Create Join dialog, select the required tables, columns, join type, and cardinality. 

c. Choose Create Join. 

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Note: You can also create a join between table columns by dragging it from one table column to 

another table column. The supported join types are inner, left outer and right outer. 

3. Add Conditions and Actions 

1. In the Data Foundation view, select the required column, and perform substeps of the required scenario given 

in the table below: 


Include table field in the output structure. From the context menu, choose Add as Attribute. 

Note: Attributes contains a subset of columns 

that you use to derive conditions and actions. 

Add conditions based on which you want to derive actions. 1. In the Output view, select the required attributes . 

2. From the context menu, choose Add as Conditions. 

Add actions for the selected conditions. 1. In the Output view, select the required attributes . 

2. To add condition values, do the following: 

2. From the context menu, choose Add as Actions. 

a. In the Decision Table view, right-click a condition, and choose Add Conditions Values. 

Note: The supported data types for an operator are: 

Operator Supported Data Types Syntax 

Not Equal To Number & CHAR-based != ABC 

In Number & Char-based In ABC;CDA 

Not In Number & Char-based Not In A;B;C 

Like CHAR-based Like Abc* 

Not Like CHAR-based Not Like Abc* 

Greater Than 

Greater Than or Equals 

Less Than 



Less Than or Equals 

Number & CHAR-based >20 

>=20 

Number & CHAR-based

Operator Supported Data Types Syntax 

< 2012-12-12 

After Date Dates After 2012-12-12 

Or 

> 2012-12-12 

Between Date Dates Between 2012-12-12 and 

b. Enter a value, and choose OK. 

Note: 

2012-12-25 

○ If a database table column is used as condition, you can use the value help dialog to select the 

condition values. You can select multiple values at one time. You can edit a condition value by 

selecting the condition, and entering a value. 

○ You can enter a pattern for the condition values having data type as VARCHAR. The pattern 

must be prefixed with the LIKE and NOT LIKE operators. For example, LIKE a*b or NOT LIKE 

a?b. If the LIKE or NOT LIKE operator is not present the pattern is treated as a string 

3. To set action values, right-click an action cell, and enter value. 

4. If you want to write a complex expression as action value, do the following: 

a. Right-click the action field. 

b. From the context menu, choose Set Dynamic Value. 

c. Write the expression for example, PRICE-(PRICE*0.1). 

d. To edit a value you need to select that value. 

Note: You can use parameters and table columns of the same data type as that of the action in 

expressions. 

5. To assign a value to a condition or an action based on the table data, choose Open Value Help Dialog, and do 

136 

the following: 

a. In the Value Help for Column dialog, enter the search string, and choose Find. 

Note: If you do not provide a value for search and choose Find, all the data corresponding to the 

selected column is shown. 

b. Select a value, and choose OK. 

Remember: 

● You can provide an alias name to a condition or an action by editing the value of Alias name property. 

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● You can choose to create parameters and use them as conditions or actions. The values you provide 

to the parameters at the runtime determine which data records are selected for consumption. For 

more information regarding how to use parameters, Using Parameters in a Decision Table [page 

139]. 

● You can export decision table data to an excel sheet using context menu option Export Data to Excel in 

the Decision Table view. You can also import decision table data from an excel using context menu 

option Import Data from Excel in the Decision Table view. 

● You can arrange the condition and action columns of the decision table depending on how you want 

them to appear. For more information, see Changing the Layout of a Decision Table [page 139]. 

6. Optional Step: Validate Decision Table 

1. To set the rules that you want to use for validation do the following: 

a. Choose Window Preferences . 

b. In the Preferences dialog box, expand Modeler Validation Rules . 

c. In the Validation Rules view, select Decision Table checkbox to check for all the rules during validation. 

d. If you want to check for individual rules, select the required rules. 

e. Choose OK. 

2. In the decision table editor, choose Validate in the editor toolbar . 

Note: In the Job Log section, you can see the validation status and detailed report of the decision table 

7. Activate Decision Table 

1. Choose File Save . 

2. From the context menu of the decision table, choose Activate. 

Note: You can choose to save and activate the view from the editor using . 

Result: On successful activation, a procedure corresponding to the decision table is created in _SYS_BIC schema. 

The name of the procedure is in the format, /. In addition, if a parameter 

is used as an action in the decision table, the corresponding table type is created in _SYS_BIC schema. The name 

of the table type is in the format, //TT. 

Remember: If in a decision table, parameters are used as conditions then corresponding IN parameters 

are generated. Also, if the parameters are used as actions then an OUT parameter is generated. 

8. Execute Decision Table Procedure 

1. To execute the decision table procedure perform the following steps as required: 



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Data Source Condition Action Script 

Physical tables Physical table 

column 

Physical table 

column 

Physical tables Parameters Physical table 

Physical tables Physical table 

column 

column 

call "".""; 

call "".""(,…,); 

Parameters call "".""(?); 

Physical tables Parameters Parameters call "".""(,…,,?); 

View attributes Parameters call "".""(?); 

Parameters Parameters call "".""(,…,,?); 

Parameters call "".""(?); 

Table Type Parameters Parameters call "".""(,…,,?); 

Tip: You can view the procedure name using the Open Definition context menu option on the selected 

procedure. 

Result: On execution of the procedure, the physical table data is updated (if no parameters are used) based on the 

data that you enter in the form of condition values and action values. 

Remember: If parameters are being used as actions in a decision table, the physical table is not updated. 

9. Data Preview 

To preview the populated data in the decision table, in the Decision Table editor, from the toolbar, choose Open 

Data Preview. 

138 

Restriction: Data preview is supported only if: 

● A decision table is based on physical tables and has at least one parameter as action. 

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● A decision table is based on information views and parameter(s) as action. 

6.3.1 Changing the Layout of a Decision Table 

Use this procedure to change the decision table layout by arranging the condition and action columns. By default, 

all the conditions appear as vertical columns in the decision table. You can choose to mark a condition as a 

horizontal condition, and view the corresponding values in a row. The evaluation order of the conditions is such 

that first the horizontal condition is evaluated and then the vertical ones. 

Note: You can only change the layout of a decision table if it has more than one condition. You can select 

only one condition as horizontal condition. 

Procedure 

1. In the context menu of the Decision Table editor, choose Change Layout. 

2. If you want to view a condition as a horizontal condition, in the Change Decision Table Layout dialog, select 

Table has Horizontal Condition (HC) checkbox. 

Note: By default the first condition in the list of conditions is marked as horizontal. 

3. In the Conditions and Actions sections, choose options on the right-hand side of the dialog box to arrange the 

conditions and actions in the desired sequence. 

4. Choose OK. 

5. Save the changes. 

Note: The available options to arrange the conditions in a sequence are: 

○ Move Condition to Top 

○ Move Condition Up 

○ Move Condition Down 

○ Move Condition to Bottom 

Note: You can also set a condition as horizontal from the context menu of the condition in the Output view. 

You can also arrange the conditions and actions in the desired sequence in the Output view using the 

respective buttons. 

6.3.2 Using Parameters in a Decision Table 

You use this procedure to create a parameter that can be used to simulate a business scenario. You can use 

parameters as conditions and actions in the decision table at design time. Parameters used as conditions, 

determine the set of physical table rows to be updated based on the condition value that you provide at runtime 

during procedure call. Parameters used as actions, simulate the physical table without updating to it. 

The following parameter types are supported: 


Static List Use this when the value of a parameter comes from a userdefined 

list of values. 



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Empty Use this when the value of a parameter could be anything of 

the selected data type. 

Procedure 

Consider a sales order physical table with column headers as follows: 

ID Name Supplier Model Price Quantity 

If you want to evaluate Discount based on the Quantity and Order Amount, you can create two 

parameters, Order Amount and Discount. Use Quantity and Order Amount as the condition, and Discount 

as the action. The sample decision table could be: 

Quantity Order Amount Discount 

>5 50000 10 

>=10 100000 15 

1. Create a Parameter 

1. In the Output pane, right-click the Parameters node. 

2. From the context menu, choose New and do the following: 


b. Select the required data type from the dropdown list. 

c. Enter the length and scale as required. 

d. Choose the required Type from the dropdown list. 

e. Choose OK. 

Note: If you have selectedStatic List for Type, choose Add in the List of Values section to add 

values. You can also provide an alias for the enumeration value. 

2. Use Parameter as Condition or Action 

1. In the Output pane, expand the Parameters node. 

2. Right-click a parameter, choose Add As Conditions/ Add as Actions. 

6.4 Managing Object Versions 

6.4.1 Switching Ownership of Inactive Objects 

Use this procedure to take over the ownership of the inactive version of an object from other users' workspace. 

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Objects in edit mode in other workspaces are not available for modification. In order to modify such objects you 

need to own the inactive object. 

The options available for changing the inactive object ownership are as follows: 

Option Purpose 

Switch Ownership To take over multiple inactive objects from other users. 

Inactive objects that do not have an active version are also 

available for take over using this option 

Take Over To take a single inactive object from another workspace that 

you wish to edit using the editor. 

Note: Using this functionality you can only own the inactive version of the object. The active version is 

owned by the user who created and activated the object. 

Prerequisite 

You have obtained the Work in Foreign Workspace authorization. 

Procedure 

1. If you want to own multiple inactive objects from other workspaces, do the following: 

a. In the Quick Launch page, choose Switch Ownership. 

b. In the Source User field, select the user who owns the inactive objects. 

c. Add the required inactive objects to the Selected Models section. 

d. Choose OK. 

2. If an object opens in read-only mode and you want to edit it, do the following: 

a. In the editor toolbar, select Switch Version. 

b. Choose Take Over. 

Note: You can choose to save the changes made by the other user (previous owner of the inactive 

version) to the inactive version of the object. 

6.4.2 Toggling Versions of Content Objects 

You use this procedure to view the active version of an information object while working with its inactive version 

for example, to view the changes made to the active version. 

Procedure 


2. Select the required object from a package. 

3. From the context menu, choose Open. 

4. In the editor pane, choose Show Active Version. 

5. Compare the inactive and active versions of the object. 



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6. Choose OK. 

6.4.3 Viewing Version History of Content Objects 

You use this procedure to view the version details of an information model for tracking purposes. 

Procedure 


2. Select the required object from a package. 

3. From the context menu, choose History. 

6.5 Working with Objects 

6.5.1 Managing Layout 

You use this procedure to adjust the data foundation and logical view layout comprising user interface controls 

like, tables and attribute views in a more readable manner. This functionality is supported for attribute views and 

analytic views. 

The options available are as follows: 

Option Purpose Substeps 

Auto Arrange Use this option to arrange the user 

interface elements automatically. 

Show outline Use this option to view an outline of the 

elements arranged so that , you do not 

have to navigate in the editor using 

horizontal and vertical scrollbars. 

Highlight related tables Use this option if you want to view only 

those tables that are related to a table 

selected in the editor. 

Display Use this option if you have a table with a 

large number of columns in the editor, 

and you want to view them in a way that 

meets your needs: for example, only the 

table name, or only joined columns, or 

the expanded form with all the columns. 

6.5.2 Filtering Packages and Objects 

In the editor tool bar, choose . 

In the editor tool bar, choose . 

1. In the editor, right-click the 

selected table. 

2. From the context menu, choose 

Highlight related tables. 

1. In the editor, right-click the relevant 

table. 

2. From the context menu, choose 

Display. 

3. If you want to view only the table 

name, choose Collapsed. 

4. If you want to view all the columns 

of the table, choose Expanded. 

5. If you want to view only the joined 

columns of the table, choose Joins 

only. 

You use this procedure to filter the content, and view packages and objects that you want to work with. If you 

apply a filter at the package level, all the packages including subpackages that satisfies the search criteria are 

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shown. You can apply a filter for packages only on the Content node in the Navigator panel. You can apply a filter 

for objects at the package level including subpackages. 

Applying Filter for Packages 

1. In the Navigator pane, select the Content node. 

2. In the context menu, choose Filter Packages.... 

3. In the Filter Packages dialog, enter the filter text. 

4. If you want to search for the exact word written in the filter text, select Match whole word checkbox. 

5. Choose OK. 

Note: If a filter already exists on the Content node, the new filter will overwrite the existing one. You can 

also apply the previous filter on the Content using Apply Filter '' option. 

Applying Filter for Objects 

1. In the Navigator pane, expand the Content node. 

2. In the context menu of a package, choose Filter Objects.... 

3. In the Filter Objects dialog, enter the filter text. 

4. If you want to search for the exact word written in the filter text, select Match whole word checkbox. 

5. If you want to apply the filter on the subpackages, choose Apply filter to sub packages checkbox. 

○ If you want to apply a filter only if no filter already exists on the selected package or otherwise retain the 

existing filter, choose Apply only if no filter already exists. 

○ If you want to apply filter even if there is an existing filter, choose Apply to all and overwrite existing. 

6. Choose OK. 

Note: If a filter already exists on the package, the new filter will overwrite the existing one. 

6.5.3 Refactoring Objects 

You use this procedure to restructure your content objects in the Navigator without changing their behavior. As 

you move the objects, their references are automatically adjusted. Objects available for refactoring are, packages, 

attribute views, analytic views, graphical calculation views, and analytic privileges. 

The activation state of the objects from source package to target package is maintained as follows: 

At Source At Target 

Base Object- active 

Impacted Object- active 

Base Object- inactive 

Impacted Object- inactive 

Base Object- active 




Base Object- active Base Object- active 



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At Source At Target 

Impacted Object- inactive Impacted Object- active 





Note: An impacted object (also known as affected object) is the one that uses the base object. For 

example, an analytic view using an attribute view is called impacted object for that attribute view. 

1. Open the Modeler perspective. 


3. Select the required objects, in the context menu, choose Refactor Move . 

4. In the Move dialog, select the target package where you want to move the package/objects, and choose Next. 

5. If you want to skip the movement of objects/packages, in the Changes to be performed panel, deselect them. 


6.5.4 Validating Models 

You use this procedure to check if there are any errors in an information object and if the object is based on the 

rules that you specified as part of preferences. For example, the "Check join: SQL" rule checks that the join is 

correctly formed. 

For more information about setting preferences, see Setting Preferences for Modeler . 

Procedure 

1. On the Quick Launch page, choose Validate. 

2. From the Available list, select the required models that system must validate. 


4. Choose Validate. 

6.5.5 Generating Object Documentation 

Use this procedure to capture the details of an information model or a package in a single document. This helps 

you view the necessary details from the document, instead of referring to multiple tables. The following table 

specifies the details that you can view from the document. 


Attribute View General object properties, attributes, calculated attributes, 

data foundation joins, cross references, and where-used 

Analytic View General object properties, private attributes, calculated 

attributes, attribute views, measures, calculated measures, 

restricted measures, variables, input parameters, data 

foundation joins, logical view joins, cross references, and 

where-used 

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Calculation View General object properties, attributes, calculated attributes, 

measures, calculated measures, counters, variables, input 

parameters, calculation view SQL script, cross references, 

and where-used 

Package Sub-packages, general package properties, and list of 

content objects 

Procedure 

1. From the Quick Launch page, choose Auto Documentation. 

2. In the Select Content Type field, select one of the following options as required: 

Option Description 

Model Details To generate documentation for models such as attribute, 

analytic, and calculation views. 

Model List To generate documentation for packages. 

3. Add the required objects to the Target list. 

4. Browse the location where you want to save the file. 


6.5.6 Enabling Multilanguage Support for Objects 

You use this procedure to enable translation of text pertaining to objects and their elements that did not have 

multilanguage support. 

For example, you can enable multilanguage support for models along with their elements like attributes and 

measures in different languages. 

Procedure 

1. From the Quick Launch tab page, choose Migrate. 

2. Select the required objects. 


4. Choose OK. 

Result 

Object texts along with the corresponding elements are flagged for translation. These objects can be viewed in 

multiple languages provided that the object texts are translated. 

6.5.7 Checking Model References 

You use this procedure to identify whether an information model is referenced by any other information model(s). 



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Procedure 

1. In the Modeler perspective, expand the system node in the Navigator pane. 


3. Expand the required package node. 

4. Select the required object. 

5. From the context menu, choose Where Used. 

6.5.8 Viewing the Job Log 

The job log displays information related to requests entered for a job. A job log consists of two tab pages as 

follows: 

● Current: Lists all waiting, running, and last five jobs. 

● History: Lists all the jobs. 

Note: You can terminate the job only if it is in the waiting state. 

You can perform the following operations using the job log: 

● Open Job Details: Use this to view the job summary in the current tab page. 

● Open Job Log File: Use this to view the information pertaining to a job in detail using the internal 

browser. 

● Clear Log Viewer: Use this to delete all the job from the current tab page. 

● Export Log File: Use this to export the log file to a target location other than the default location for 

further reference. 

● Delete Job: Use this to delete single job from the current tab page. 

6.5.9 Maintaining Search Attributes 

You use this procedure to enable an attribute search for an attribute used in a view. Various properties related to 

attribute search are as follows: 

● Freestyle Search: Set to True if you want to enable the freestyle search for an attribute. You can exclude 

attributes from freestyle search by setting the property to False. 

● Weights for Ranking: To influence the relevancy of items in the search results list, you can vary the weighting 

of the attribute. You can assign a higher or lower weighting (range 0.0 to 1.0). The higher the weighting of the 

attribute, the more influence it has in the calculation of the relevance of an item. Items with a higher relevance 

are located higher up the search results list. Default value: 0.5. 

Note: To use this setting the property Freestyle Search must be set to True. 

● Fuzziness Threshold: This parameter is reserved for the future usage of the fault-tolerant search.. 

Note: It is recommended to use the default values for ranking and fuzziness at the beginning. You can finetune 

the search settings based on the experience gained using the search. You can also fine-tune the 

search using feedback collected from your users. 

6.5.10 Previewing Data of Content Objects 

You use this procedure to preview the content of content models for analysis purposes. 


2. Select the object from a package for which you want to view the content. 

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3. From the context menu, choose Data Preview. 

The system displays the content in different formats as shown in the table below. 

Tab Page Displays… 

Raw Data All attributes along with data in a table format. 

Distinct values All attributes along with data in a graphical format. 

Analysis All attributes and measures in a graphical format. 

Tip: If there are inconsistencies in runtime information (that is, calculation views in catalog or in tables 

related to runtime) of a view, you might get invalidated view error. In such cases, you need to 

redeploy the view in order to correct the inconsistencies with runtime information. 

4. Navigate to the required tab page and view the content. 

6.5.11 Functions used in Expressions 

This topic covers the functions that you can use while creating expressions like, calculated attributes and 

calculated measures. 

Conversion Functions 

Function Syntax Purpose Example 

int int int(arg) convert arg to int type int(2) 

float float float(arg) convert arg to float type float(3.0) 

double double double (arg) convert arg to double type double(3) 

sdfloat sdfloat sdfloat (arg) convert arg to sdfloat type 

decfloat decfloat decfloat (arg) convert arg to decfloat type 

fixed fixed fixed (arg, int, int) arg2 and arg3 are the 

intDigits and fractdigits 

parameters, respectively. 

Convert arg to a fixed type of 

either 8, 12, or 16 byte length, 

depending on intDigits and 

fractDigits 

string string string (arg) convert arg to string type 

raw raw raw (arg) convert arg to raw type 

date date date(stringarg) 



date date(fixedarg) 

date date(int, int) 

date date(int, int, int) 

date date(int, int, int, int) 

convert arg to date type. The 

first version parses a string in 

the format "yyyy-mm-dd 

hh:mi:ss" where trailing 

components except for the 

year may be omitted. The 

version with one fixed 

number arg strips digits 

fixed(3.2, 8, 2) + fixed(2.3, 8, 

3) 

date(2009) -> date('2009') 

date(2009, 1, 2) -> 

date('2009-01-02') 

date(fixed(20000203135026 

.1234567, 10, 4)) -> 

date('2000-02-03 13:50:26') 

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date date(int, int, int, int, int) 

date date(int, int, int, int, int, 

int) 

longdate longdate longdate(stringarg) 

longdate longdate(fixedarg) 

longdate longdate(int, int, int) 

longdate longdate(int, int, int, 

int, int) 


int, int, int) 


int, int, int, int) 

time time time(stringarg) 

String Functions 

time time(fixedarg) 

time time(int, int) 

time time(int, int, int) 

behind the comma and tries 

to make a date from the rest. 

The other versions accept the 

individual components to be 

set. 

convert arg to longdate type, 

similar to date function 

above. 

convert arg to time type, 

similar to date function above 

Function Syntax Purpose 

longdate(fixed(2000020313 

5026.1234567, 10, 5)) -> 

longdate('2000-02-03 

13:50:26.1234500') 

longdate(2011, 3, 16, 9, 48, 

12, 1234567) -> 

longdate('2011-03-16 

09:48:12.1234567') 

strlen int strlen(string) returns the length of a string in bytes, as 

an integer number. 

midstr string midstr(string, int, int) returns a part of the string starting at 

arg2, arg3 bytes long. 

arg2 is counted from 1 (not 0) 

leftstr string leftstr(string, int) returns arg2 bytes from the left of the 

arg1. If arg1 is shorter 

than the value of arg2, the complete 

string will be returned. 

rightstr string rightstr(string, int) returns arg2 bytes from the right of the 

arg1. If arg1 is shorter 

than the value of arg2, the complete 

string will be returned. 

instr int instr(string, string) returns the position of the first 

occurrence of the second string 

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within the first string (>= 1) or 0, if the 

second string is not 

contained in the first. 




hextoraw string hextoraw(string) convert a hexadecimal representation of 

bytes to a string of 

bytes. The hexadecimal string may 

contain 0-9, upper or lowercase a-f and 

no spaces between the two digits of a 

byte; spaces between bytes are allowed. 

rawtohex string rawtohex(string) convert a string of bytes to its 

hexadecimal representation. 

ltrim string ltrim(string) 

string ltrim(string, string) 

rtrim string rtrim(string) 

string rtrim(string, string) 

trim string trim(string) 

string trim(string, string) 

lpad string lpad(string, int) 

string lpad(string, int, string) 

rpad string rpad(string, int) 



string rpad(string, int, string) 

The output will contain only 0-9 and 

(upper case) A-F, no spaces and is twice 

as many bytes as the original string. 

removes a whitespace prefix from a 

string. The Whitespace characters may 

be specified in an optional argument. 

This functions operates on raw bytes of 

the UTF8-string and has no knowledge 

of multi byte codes (you may not 

specify multi byte whitespace 

characters). 

removes trailing whitespace from a 

string. The Whitespace characters may 

be specified in an optional argument. 

This functions operates on raw bytes of 

the UTF8-string and has no knowledge 

of multi byte codes (you may not 

specify multi byte whitespace 

characters). 

removes whitespace from the beginning 

and end of a string. 

add whitespace to the left of a string. A 

second string argument specifies the 

whitespace which will be added 

repeatedly until the string has reached 

the intended length. If no second string 

argument is specified, chr(32) (' ') will 

be added. This function operated on 

UTF-8 bytes and has no knowledge of 

unicode characters (neither for the 

whitespace string nor for length 

computation). 

add whitespace to the end of a string. A 

second string argument specifies the 

whitespace which will be added 

repeatedly until the string has reached 

the intended length. If no second string 

argument is specified, chr(32) (' ') will 

be added. This function operated on 

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UTF-8 bytes and has no knowledge of 

unicode characters (neither for the 

whitespace string nor for length 

computation). 

replace string replace(string, string, string) replace every occurrence of arg2 in arg1 

with arg3 and return the resulting string 

Mathematical Functions 


sign int sign(double) 

int sign(time) 

int sign(date) 

abs double abs(double) 

round 

. 

rounddown 

Date Functions 

decfloat abs(decfloat) 

decfloat abs(decfloat) 

time abs(time) 

Sign returns -1, 0 or 1 

depending on the sign of its 

argument. Sign is 

implemented for all numeric 

types, date and time. 

Abs returns arg, if arg is 

positive or zero, -arg else. 

Abs is implemented for all 

numeric types and time. 

double round(double, int) round does rounding of 

absolute values toward zer 

while the sign is retained 

double rounddown(double, 

int) 

rounddown rounds toward 

negative infinity making 

rounddown(-1.1, 0) = -2 


round(123.456, 0) = 123 

round(123.456, 1) = 123.5 

round(-123.456, 1) = -123.5 

round(123.456, -1) = 120 

rounddown(123.456, -1) = 

120 

rounddown(-123.456, -1) = 

-130 

utctolocal utctolocal(datearg, timezonearg) interprets datearg (a date, without 

timezone) as utc and convert it to the 

timezone named by timezonearg (a 

string) 

localtoutc localtoutc(datearg, timezonearg) converts the local datetime datearg to 

the timezone specified by the string 

timezonearg, return as a date 

weekday weekday(date) returns the weekday as an integer in the 

range 0..6, 0 is monday. 

now now() returns the current date and time 

(localtime of the server timezone) as 

date 

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daysbetween daysbetween(date1, date2) 

daysbetween(daydate1, daydate2) 

daysbetween(seconddate1, 

seconddate2) 

daysbetween(longdate1, longdate2) 

secondsbetween secondsbetween(seconddate1, 

seconddate2) 

secondsbetween(longdate1, longdate2) 

returns the number of days (integer) 

between date1 and date2. The first 

version is an alternative to date2 - date1. 

Instead of rounding or checking for 

exactly 24 hours distance, this will 

truncate both date values today 

precision and subtract the resulting day 

numbers, meaning that if arg2 is not the 

calendar day following arg1, 

daysbetween will return 1 regardless of 

the time components of arg1 and arg2. 

returns the number of seconds the first 

to the second arg, as a fixed point 

number. The returned value is positive if 

the first argument is less than the 

second. The return values are fixed18.0 

in both cases (note that it may prove 

more useful to use fixed11.7 in case of 

longdate arguments). 

component component(date, int) the int argument may be int the range 

1..6, the values mean year, day, month, 

hour, minute, second, respectively. If a 

component is not set in the date, the 

component function will return a default 

value, 1 for the month or the day, 0 for 

other components. The component 

function may also be applied to 

longdate and time types. 

addseconds addseconds(date, int) 

addseconds(seconddate, decfloat) 

addseconds(longdate, decfloat) 

adddays adddays(date, int) 

Misc Functions 

adddays(daydate, int) 

adddays(seconddate, int) 

adddays(longdate, int) 

Return a date plus a number of seconds. 

Fractional seconds will also be used in 

case of longdate. Null handling is (in 

opposition to the default done with 

adds) to return null if any argument is 

null. 

Return a date plus a number of days. 

Null handling is (in opposition to the 

default done with adds) to return null if 

any argument is null. 


if if(intarg, arg2, arg3) return arg2 if intarg is 

considered true (not equal to 

zero), else return arg3. 

Currently, no shortcut 

evaluation is implemented, 



if("NETWR"


meaning that both arg2 and 

arg3 are evaluated in any 

case. This means you cannot 

use if to avoid a divide by zero 

error which has the side 

effect of terminating 

expression evaluation when it 

occurs. 

in in(arg1, ...) return 1 (= true) if arg1 is 

equal to any of the remaining 

args, return 0 else 

case 

case(arg1, default) case(arg1, 

cmp1, value1, cmp2, 

value2, ..., default) 

return value1 if arg1 == cmp1, 

value2 if arg1 == cmp2 etc, 

default if there no match 

isnull isnull(arg1) return 1 (= true), if arg1 is set 

to null and null checking is on 

during Evaluator run 

(EVALUATOR_MAY_RETURN 

_NULL) 

6.5.12 Searching Tables, Models and Column Views 

case("CATEGORY", 'A', 'LV', 

'B', 'MV', 'HV') 

You use this feature to search for tables, models and column views in a system. You can search these objects in 

any system from the list of systems added in the Navigator panel that has all services started, and is up and 

running. 

In the search results, for a matching object you can perform the following actions: 

● Tables - you can open the table definition and add the table in the analytic and attribute view editor. 

Note: You can add a table only if the editor is open otherwise it results in error. 

● Models - you can open the models in the editor and in case of attribute view, you can add it in the view editor 

of an analytic view. 

Note: You can add a model only if the editor is open otherwise it results in error. 

● Column Views - you can only open and view the definition. 

1. Enter the object that you want to search in the Modeler toolbar search field. 

2. Select the system in which you want to search the object from the dropdown option next to the Search 

button. 

3. To execute the search, choose Search. 

The matching objects are listed in the expanded results pane with three tab pages, Tables, Models, and 

Column Views. You can select each to view the matching objects and corresponding actions that you can 

perform on them, for example, Open and Add. 

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6.5.13 Setting Keyboard Shortcuts 

You use this procedure to enable the keyboard shortcuts for Modeler actions like, activate, validate, and so on. 

The list of supported commands with the default keyboard shortcuts is as follows: 

Command Binding When Category 

Activate Ctrl+Shift+A Navigator Modeler Keys 

Activate Ctrl+Shift+A In Windows Modeler Keys 

Add Table/Model Ctrl+Shift+= In Windows Modeler Keys 

Auto Arrange Ctrl+L In Windows Modeler Keys 

Data Preview Alt+Shift+P Navigator Modeler Keys 

Data Preview Alt+Shift+P In Windows Modeler Keys 

Display XML Alt+D In Windows Modeler Keys 

Find Ctrl+F Navigator Modeler Navigator 

Fit to Window Ctrl+0 In Windows Modeler Keys 

Move Element in Output 

Pane (Direction: Down) 

Move Element in Output 

Pane (Direction: Up) 

Ctrl+] In Windows Modeler Keys 

Ctrl+[ In Windows Modeler Keys 

Open Ctrl+O Navigator Modeler Keys 

Show View (View: History) Alt+Shift+H In Windows Views 

Show View (View: Job 

Log) 

Show View (View: Where- 

Used List) 

Alt+Shift+L In Windows Views 

Alt+Shift+U In Windows Views 

Validate Ctrl+Shift+V In Windows Modeler Keys 

Validate Ctrl+Shift+V Navigator Modeler Keys 

Zoom (Type: In) Ctrl+= In Windows Modeler Keys 

Zoom (Type: Out) Ctrl+- In Windows Modeler Keys 

Zoom (Type: Reset) Alt+Shift+0 In Windows Modeler Keys 

1. Choose Window Preferences General Keys . 

2. In the Keys panel, select Modeler as Scheme. 

3. If you want to view only the commands supported by Modeler for keyboard shortcut, in the text field enter 

Modeler Keys. 



Note: You cannot add new commands but can choose to customize the commands using the 

following options: 

○ Copy Command - to provide alternate keyboard shortcut for an existing command. 

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4. Choose Apply. 

○ Unbind Command - to clear the key bindings with the command and provide new keyboard 

shortcut for an existing command. 

○ Restore Command - to restore the default key bindings provided by Modeler for an existing 

command. 

6.5.14 Copying an Object 

You can choose to copy an object in the Navigator panel and paste it to a required package. You must have write 

permissions on the target package where you are pasting the object. The copy paste feature is supported for all 

Modeler objects that is, attribute view, analytic view, calculation view, procedure and analytic privilege. The object 

that is copied to the target package is always inactive, even if in the source package it is in active state. 

By default the keyboard shortcut for copy and paste is CTRL + C and CTRL + V respectively. To enable keyboard 

shortcut for copy and paste you must apply the Modeler keyboard shortcuts from the Window Preferences 

General Keys and select Modeler as scheme. 

Note: Copy paste is supported only for a single object. 

1. In the Navigator panel, select an object and in the contect menu, choose Copy. 

Note: If you have applied the Keyboard shortcuts then you can also press CTRL + C to copy an object. 

2. Navigate to the package where you want to paste the object, and choose Paste. 

Note: If you have applied the Keyboard shortcuts then you can also press CTRL + V to paste an object. 

6.6 Importing BW Objects 

● You have implemented SAP Notes 1703061, 1759172, 1752384,1733519, and 1769374. 

● You have upgraded your Modeler to SAP HANA 1.0 SP04 Rev 37. 

● You have added BW schema in the SQL privileges for the Modeler user to import BW models. 

● _SYS_REPO user has SELECT with GRANT privileges on the schema that contains the BW tables. 

You use this feature to import SAP NetWeaver Business Warehouse (SAP NetWeaver BW) models that are SAP 

HANA-optimized InfoCubes, SAP HANA-optimized DataStore objects, and Query Snapshot InfoProviders to the 

SAP HANA modeling environment. These imported objects are exposed as SAP HANA information models and 

can be consumed for reporting using client tools such as, SAP BusinessObjects Explorer, SAP BusinessObjects BI 

4.0 Suite (Web Intelligence via Universes, Dashboards, Crystal Reports), Microsoft Office and so on. The model 

properties are set based on the SAP NetWeaver BW models metadata. 

If you select a DataStore object, the resultant SAP HANA model is an analytic view with the same name as that of 

the DataStore object. If you select an InfoCube, two objects- analytic view and calculation view are created. In this 

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case, the name of calculation view and analytic view is same as that of the InfoCube and the name of the analytic 

view is suffixed with _INTERNAL. The analytic view generated in the case of an InfoCube is used internally for the 

generation of the respective calculation view and is not available for client consumption. If you select a 

QuerySnapshot InfoProvider, the resultant SAP HANA model is an analytic view. 

When you choose to import the SAP NetWeaver BW InfoProviders, the analysis authorizations set on the 

InfoProviders are also imported as analytic privileges in the SAP HANA Modeler. The name of the analytic privilege 

is the same as that of the BW Analysis Authorization object. These analysis authorizations set on the 

InfoProviders are applicable at runtime for reporting. 

Note: In the case of Query Snapshot, all the BW Analysis Authorization objects which are applicable on the 

underlying InfoProvider of the query, will also be applicable on the Query Snapshot. These BW analysis 

authorization objects will be imported as analytic privileges when importing the query snapshot. 

The generated models and analytic privileges are placed in the sap.bw package. You can choose to enhance the 

generated models. However, with the subsequent import of the same objects, the changes are overridden. Also, 

changes made to the models on BW side are not automatically reflected in the generated models. This may lead 

to inconsistent generated models based on the changes made to the physical tables. To avoid this, you need to re- 

import the models. 

Caution: 

● The calculated key figures (CKFs) and restricted key figures (RKFs) defined on the SAP BW models 

are not created for the generated SAP HANA models. In this case, you can create an RKF as restricted 

measure in the generated analytic view. For CKF you can create calculated measures in the generated 

calculation view or analytic view. These CKFs and RKFs are retained during subsequent import. If a 

change is made to the characteristics or key figures based on which these restricted measures and 

calculated measures are created, this may lead to inconsistency in the generated models. In this case, 

you need to manually adjust these restricted measures and calculated measures. 

● The restricted measures and calculated measures that you define for the analytic view that 

correspond to a query snapshot, is overwritten with the subsequent import. 

● The BW analysis authorization objects are not always mapped 1:1 with the generated analytic 

privileges on the SAP HANA Modeler side. If the BW Analysis Authorization object does not include 

0TCAIPROV, the authorization is not moved to SAP HANA. Also, restrictions created in the BW 

analysis authorization are skipped if they do not match with the restrictions supported by the SAP 

HANA Modeler. In such cases, the data available for reporting for a SAP HANA Modeler user differs 

from the SAP NetWeaver BW user with the assigned restrictions. 

For reporting purposes, data which is visible for a user is: 

● For a DSO generated analytic view, all the data in the active table is available for reporting. 

● For an InfoCube generated calculation view, only successfully loaded requests are available for reporting 

(these are the green requests in manage InfoCube section). 

Restriction: 



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● The following features are not supported on the generated SAP HANA models: 

○ DSO without any key figure 

○ Currency and unit of measure conversion 

Note: Only currency mapping is supported and not the conversion. 

○ Time dependent text and attributes 

○ Non-cumulative key figures 

○ Conversion routines in the BW system 

● The following features are not supported on generated analytic privileges: 

○ Exclude operator 

○ Aggregated value operator ‘:’ 

○ Variables, User exits 

○ Authorization on Key Figures 

○ Authorization on hierarchy node 

○ Exception aggregation such as, average, counter, first value, last value, no aggregation, standard 

deviation is not supported for generated measures. 

● The query name for the Query Snapshot should not be the same as the BW InfoProvider name (this 

results in conflict on the SAP HANA side). 

● Query Snapshot InfoProvider for BOE supports only key figures with aggregation types MIN, MAX, 

SUM, and COUNT. 

1. Open the Modeler perspective. 

2. In the main menu, choose File Import . 

3. Expand the SAP HANA Content node. 

4. Choose Import SAP NetWeaver BW Models, and choose Next. 

5. To establish a connection with the SAP NetWeaver BW system (underlying BW Application Server), in the 

Source System page, enter the SAP NetWeaver BW system credentials and choose Next. 

Note: To add new connection details, select New Connection option from the Connection dropdown 

list. The connection details are saved and are available as dropdown options on subsequent logons. 

6. Select the target system (an SAP NetWeaver BW on SAP HANA) to which you want to import the models, and 

choose Next. 

7. Select the BW InfoProviders that you want to import and expose as SAP HANA information models. 

Remember: In order to import the QuerySnapshot InfoProvider, make sure that the BW Query is 

unlocked in transaction RSDDB, and an index is created via the same transaction before it can be used 

as InfoProviders. 

8. If you want to replace previously imported models in the target system with a new version, select Overwrite 

existing models. 

9. If you want import the selected models along with the display attributes for IMO Cube and IMO DSO, select 

Include display attributes. 

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The generated information models and analytic privileges are placed in the sap.bw package. In order to view the 

data of generated models, you need to assign the associated analytic privileges that are generated as part of the 

model import to the user. If these privileges are not assigned, user is not authorized to view the data. 



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7 Developing Procedures 

SQL in SAP HANA includes extensions for creating procedures, which enables you to embed data-intensive 

application logic into the database, where it can be optimized for performance (since there are no large data 

transfers to the application and features such as parallel execution is possible). Procedures are used when other 

modeling objects, such as analytic or attribute views, are not sufficient. 

Some of the reasons to use procedures instead of standard SQL: 

● SQL is not designed for complex calculations, such as for financials. 

● SQL does not provide for imperative logic. 

● Complex SQL statements can be hard to understand and maintain. 

● SQL queries return one result set. Procedures can return multiple result sets. 

● Procedures can have local variables, eliminating the need to explicitly create temporary tables for 

intermediate results. 

Procedures can be written in the following languages: 

● SQLScript: The language that SAP HANA provides for writing procedures. 

● R: An open-source programming language for statistical computing and graphics, which can be installed and 

integrated with SAP HANA. 

There are additional libraries of procedures, called Business Function Library and Predictive Analysis Library, that 

can be called via SQL or from within another procedure. 

SQL Extensions for Procedures 

SQL includes the following statements for enabling procedures: 

● CREATE TYPE: Creates a table types, which are used to define parameters for a procedure that represent 

tabular results. For example: 

CREATE TYPE tt_publishers AS TABLE ( 

publisher INTEGER, 

name VARCHAR(50), 

price DECIMAL, 

cnt INTEGER); 

● CREATE PROCEDURE: Creates a procedure. The LANGUAGE clause specifies the language you are using to 

158 

code the procedure. For example: 

CREATE PROCEDURE ProcWithResultView(IN id INT, OUT o1 CUSTOMER) 

LANGUAGE SQLSCRIPT READS SQL DATA WITH RESULT VIEW ProcView AS 

BEGIN 

o1 = SELECT * FROM CUSTOMER WHERE CUST_ID = :id; 

END; 

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Developing Procedures

● CALL: Calls a procedure. For example: 

CALL getOutput (1000, 'EUR', NULL, NULL); 

Tools for Writing Procedures 

Use the SQLScript editor, which includes debugging capabilities, to build SQLScript procedures. 

You can also use the Navigator in the Modeler perspective to build procedures, but there are no debugging 

capabilities. You should only use this method: 

● If you need to develop a procedure using a local table type as an input or output parameter. A local table type 

is created within the Navigator procedure tool and for only the current procedure. If you can use a global table 

type, then use the SQLScript Editor. 

● If you need to edit a procedure previously created in the Navigator that contains table type parameters. 

Related Links 

SAP HANA SQL Reference 

SAP HANA SQLScript Reference 

SAP HANA R Integration Guide 

SAP HANA Business Function Library (BFL) Reference 

SAP HANA Predictive Analysis Library (PAL) Reference 

Creating Procedures 

7.1 Editing SQLScript 

The SAP HANA SQLScript editor allows you to create, edit and activate procedures. 

Before you begin working in the SAP HANA SQLScript editor, open the SAP HANA Development perspective and 

do the following: 

● Create a development workspace. For more information, see Creating a Repository Workspace [page 39]. 

● Checkout a package. For more information, see Working with the Repository [page 27] . 

Note: After checking out a package that contains active procedures, you can modify and debug the 

procedures. 

● Create and share a project. For more information, see Using SAP HANA Projects [page 37]. 

. 

Note: You can also share your project after you create your procedure. 

To write and edit a procedure in the SAP HANA SQLScript editor, perform the following steps: 


Developing Procedures 

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1. After you have created your workspace and your project, go to the Project Explorer view in the SAP HANA 

Development perspective , right-click on the file name, select New, and select File. The New File wizard will 

appear. 

2. Enter or select the parent folder and enter the file name using the following naming convention 

.procedure. Choose Finish. The icon shows that your procedure is created locally. Choose Save. 

Your procedure will open containing the default Create Procedure template. In the Properties view, you will 

see the properties of your procedure, such as Access Mode, Name and Language. You can also change the 

default schema that this procedure is using. 

Note: You can also create a folder first and add a file. Right-click on the project name, select New, and 

select Folder. The New Folder wizard will appear. Enter or select the project, enter the folder name, 

and choose Finish. 

3. To share your project, right-click on the project name, select Team, and select Share Project. The Share 

Project wizard will appear. Choose Finish. The icon shows that your procedure is not committed and not 

activated. 

4. You can begin writing your code inside your new procedure and save it locally. The syntax is checked 

simultaneously and is highlighted. Auto-completion of the syntax appears as you type; press Ctrl + Spacebar 

to get a list of relevant SQLScript statements. 

Note: You can only write one stored procedure per file. The file name and the procedure name must 

be the same. 

5. To commit your new procedure or make changes to an existing one, first save it, right-click on the procedure, 

select Team, and select Commit. Your procedure is now synchronized to the repository as a design-time 

object and the icon shows that your procedure is committed . 

Caution: The design-time presentation of the procedure is currently in XML format that you must not 

edit. 

6. When you have finished writing your procedure and you are ready to activate it, right-click on the procedure, 

select Team, and select Activate. Your procedure is created in the catalog as a runtime object and the icon 

shows that your procedure is activated . This will allow you and other users to call the procedure and debug it. 

If an error is detected during activation, an error message will appear in the Problems view. 

Related Links 

Note: You can also activate your procedure at the project and folder level. 

SAP HANA Development Perspective [page 25] 

SAP HANA Repository Packages and Namespaces [page 43] 

In SAP HANA, a package typically consists of a collection of repository objects, which can be transported 

between systems. Multiple packages can be combined in a delivery unit (DU). 

About SAP HANA SQLScript 

SAP HANA SQL Reference 

SAP HANA System Tables and Monitoring Views Reference 

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7.2 Debugging SQLScript 

The SAP HANA SQLScript debugger allows you to debug and analyze procedures. In a debug session, your 

procedures will be executed in a serial mode, not in parallel (not-optimized). This allows you to test the 

correctness of the procedure logic and is not for evaluating the performance. 

Before you begin using the SAP HANA SQLScript debugger, you must activate your procedures and they must 

belong to a project on your local work station. For more information, see Editing SQLScript. 

To debug a procedure in the SAP HANA SQLScript debugger, perform the following steps: 

1. Open the Debug perspective in the SAP HANA studio and select the procedure you want to debug by clicking 

on the relevant tab in the Editor view. 

2. Double-click on the left vertical ruler to add breakpoints to your procedure. You can see a list of all of the 

breakpoints in the Breakpoints view. 

From the Breakpoints view, you can: 

○ Deselect specific breakpoints or skip all of them. 

○ Delete a specific breakpoint or delete all. 

○ Double-click on a breakpoint to see which line it belongs to in the Editor view. 

○ See the status of the breakpoint: 

○ Pending 

○ Valid 

○ Invalid 

3. To create a debug session you must first create a debug configuration. Choose and select Debug 

Configurations.... The Debug Configurations wizard will appear. 

Note: The current debug configuration allows you to debug any stored procedure that is opened in the 

editor. Therefore, you do not have to create a new debug configuration for every procedure you want 

to debug. 

4. Double-click SQLScript Procedure, enter a name, choose Apply, and choose Close. 



Note: If you want to start debugging your procedure, choose Apply and choose Debug. 

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5. To start your debug session, choose and select your debug configuration. The debug session will begin 

and you will see the status of the session in the Debug view. The status of a breakpoint may change after the 

server has validated it. The breakpoint position might change if it is placed on an invalid line where the 

debugger cannot stop. The debugger will stop at the first breakpoint and the session will be suspended until 

you resume it. 

If your run is successful, the valid status will appear next to the breakpoints in the Breakpoints view. 

Note: You must set breakpoints in the lines you want to break at and resume the session again. 

You can evaluate your local scalar and table variables in the Variable view. The view shows the values of the 

scalar variables and the number of rows in each table. 

6. To view the content of the tables listed in the Variable view, right-click on the table name and select Open Data 

Preview. The results will appear in the Preview view. This view will automatically close when you resume your 

debug session. 

The session will be terminated when you reach the end of the procedure run. 

7.3 Developing Procedures in the Modeler Editor 

To create procedures, use the SQLScript Editor, as described in Editing SQLScript [page 159]. 

If you need to create procedures with local table types, that is, table types created only for the procedure, perform 

the steps described in this section. 

1. On the Quick Launch tab page, choose Procedure. 

If the Quick Launch page is not open, go to Help Quick Launch . 

2. Enter a name and description for the procedure. 

3. For unqualified access in SQL, select the required schema from the Default Schema dropdown list. 

Note: 

○ If you do not select a default schema, while scripting you need to provide fully qualified names of 

the catalog objects that include the schema. 

○ If you specify a default schema, and write SQL such as select * from myTable, the 

specified default schema is used at runtime to refer to the table. 

4. Select the package in which you want to save the procedure. 

5. Select the required option from the Run With dropdown list to select which privileges are to be considered 

while executing the procedure. 

162 

Note: 

There are two types of rights, as follows: 

Definer's right: If you want the system to use the rights of the definer while executing the procedure 

for any user. 

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Invoker's right: If you want the system to use the rights of the current user while executing the 

procedure. 

6. Select the required access mode as follows: 

Access Mode Purpose 

Read Only Use this mode to create procedures for fetching table data. 

Read Write Use this mode to create procedures for fetching and 

updating table data. 

7. Select the language in which you are writing the procedure. 


9. In the function editor pane, write a script for the function using the following data types: 

○ Table or scalar data types for input parameters. 

○ Table data types for output parameters. 

Note: You can only write one function in the function body. However, you can refer to other functions. 

10. Choose File Save . 

11. Activate the procedure using one of the following options in the toolbar: 

○ Save and Activate: Activate the current procedure and redeploy the affected objects if an active version of 

the affected object exists. Otherwise only the current procedure gets activated. 

○ Save and Activate All: Activate the current procedure along with the required and affected objects. 



Note: You can also activate the current procedure by selecting the procedure in the Navigator view 

and choosing Activate in the context menu. For more information about activation, see Activating 

Objects [page 132]. 

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8 Defining Web-based Data Access 

SAP HANA extended application services (SAP HANA XS) provide applications and application developers with 

access to the SAP HANA database using a consumption model that is exposed via HTTP. 

In addition to providing application-specific consumption models, SAP HANA XS also host system services that 

are part of the SAP HANA database, for example: search services and a built-in Web server that provides access 

to static content stored in the SAP HANA repository. 

The consumption model provided by SAP HANA XS focuses on server-side applications written in JavaScript and 

making use of a powerful set of specially developed API functions. However, you can use other methods to 

provide access to the data you want to expose in SAP HANA. For example, you can set up an ODATA service or 

use the XML for Analysis (XMLA) interface to send a Multi-dimensional Expressions (MDX) query. This section 

describes how to set up a service that enables you to expose data using OData or XMLA. 

8.1 Data Access with OData in SAP HANA XS 

In SAP HANA Extended Application Services (SAP HANA XS), the persistence model (for example, tables, views, 

and stored procedures) is mapped to the consumption model that is exposed to clients - the applications you 

write to extract data from the SAP HANA database. 

You can map the persistence and consumption models with OData, a resource-based Web protocol for querying 

and updating data. An OData application running in SAP HANA XS is used to provide the consumption model for 

client applications exchanging OData queries with the SAP HANA database.: 

You can use OData to enable clients to consume authorized data stored in the SAP HANA database. OData 

defines operations on resources using RESTful HTTP commands (for example, GET, PUT, POST, and DELETE) 

and specifies the URI syntax for identifying the resources. Data is transferred over HTTP using either the Atom 

(XML) or the JSON (JavaScript) format. 

Applications running in SAP HANA XS enable accurate control of the flow of data between the presentational 

layer, for example, in the Browser, and the data-processing layer in SAP HANA itself, where the calculations are 

performed, for example, in SQL or SQLScript. If you develop and deploy an OData service running in SAP HANA 

XS, you can take advantage of the embedded access to SAP HANA that SAP HANA XS provides; the embedded 

access greatly improves end-to-end performance. 

8.1.1 OData in SAP HANA XS 

OData is a resource-based web protocol for querying and updating data. OData defines operations on resources 

using HTTP commands (for example, GET, PUT, POST, and DELETE) and specifies the uniform resource 

indicator (URI) syntax to use to identify the resources. 

Data is transferred over HTTP using the Atom or JSON format: 

164 

Note: OData makes it easier for SAP, for partners, and for customers to build standards-based 

applications for many different devices and on various platforms, for example, applications that are based 

on a lightweight consumption of SAP and non-SAP business application data. 

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Defining Web-based Data Access

The main aim of OData is to define an abstract data model and a protocol which, combined, enable any client to 

access data exposed by any data source. Clients might include Web browsers, mobile devices, businessintelligence 

tools, and custom applications (for example, written in programming languages such as PHP or Java); 

data sources can include databases, content-management systems, the Cloud, or custom applications (for 

example, written in Java). 

The OData approach to data exchange involves the following elements: 

● OData data model 

Provides a generic way to organize and describe data. OData uses the Entity 1 Data Model (EDM). 

● OData protocol 

Enables a client to query an OData service. The OData protocol is a set of interactions, which includes the 

usual REST-based create, read, update, and delete operations along with an OData-defined query language. 

The OData service sends data in either of the following ways: 

○ XML-based format defined by Atom/AtomPub 

○ JavaScript Object Notation (JSON) 

● OData client libraries 

Enables access to data via the OData protocol. Since most OData clients are applications, pre-built libraries 

for making OData requests and getting results reduces and simplifies work for the developers who create 

those applications. 

A broad selection of OData client libraries are already widely available, for example: Android, Java, JavaScript, 

PHP, Ruby, and the best known mobile platforms. 

● OData services 

Exposes an end point that allows access to data in the SAP HANA database. The OData service implements 

the OData protocol (using the OData Data Services runtime) and uses the Data Access layer to map data 

between its underlying form (database tables, spreadsheet lists, and so on) and a format that the requesting 

client can understand. 

8.1.2 OData Service Definitions 

The OData service definition is the mechanism you use to define what data to expose with OData, how, and to 

whom. Data exposed as an OData collection is available for analysis and display by client applications, for 

example, a browser that uses functions provided by an OData client library running on the client system. 

To expose information by means of OData to applications using SAP HANA XS, you must define database views 

that provide the data with the required granularity. Then you create an OData service definition, which is a file you 

use to specify which database views or tables are exposed as OData collections. 

Note: SAP HANA XS currently supports OData version 2.0, which you can use to send OData queries 

(using the http GET method). Language encoding is restricted to UTF-8. 

An OData service for SAP HANA XS is defined in a text file with the file suffix .xsodata, for example, 

OdataSrvDef.xsodata. The file must contain at least the entry service {}, which would generate a 

completely operational OData service with an empty service catalog and an empty metadata file. However, usually 

you use the service definition to expose objects in the database catalog, for example: tables, SQL views, or 

calculation rules. 

In the OData service-definition file, you can use the following ways to name the SAP HANA objects you want to 

expose by OData: 

● Repository objects 


Defining Web-based Data Access 

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Expose an object using the object's repository (design-time) name in the OData service-definition file. This 

method of exposing database objects by OData has the advantage that the OData service is automatically 

updated if the underlying repository object changes. 

● Database objects 

Expose an object using the object's database catalog (runtime) name (along with the schema name). The 

support for database objects is mainly intended for existing or replicated objects that do not have a repository 

design-time representation. 

Note: Although both declaration methods are supported, the recommended method is to use the 

repository name of the object(s) you want to expose using OData. 

OData Service-Definition Type Mapping 

During the activation of the OData service definition, SQL types are mapped to EDM types according to a mapping 

table. For example, the SQL type "Time" is mapped to the EDM type "EDM.Time"; the SQL type "Decimal" is 

mapped to the EDM type "EDM.Decimal"; the SQL types "Real" and "Float" are mapped to the EDM type 

"EDM.Single". 

In the following example, the SQL types of columns in a table are mapped to the EDM types in the properties of an 

entity type. 

{name = "ID"; sqlType = INTEGER; nullable = false;}, {name = "RefereeID"; 

sqlType = VARCHAR; nullable = true;} 

 

OData Service-Definition Features 

The OData service definition provides a list of keywords that you use in the OData service-definition file to enable 

important features. For example, the following list illustrates the most-commonly used features used in an OData 

service-definition and, where appropriate, indicates the keyword to use to enable the feature: 

● Aggregation 

The results of aggregations on columns change dynamically, depending on the grouping conditions. As a 

result, aggregation cannot be done in SQL views; it needs to be specified in the OData service definition itself. 

Depending on the type of object you want to expose with OData, the columns to aggregate and the function 

used must be specified explicitly (explicit aggregation) or derived from metadata in the database (derived 

aggregation). Note that aggregated columns cannot be used in combination with the $filter query 

parameter, and aggregation is only possible with generated keys. 

● Association 

Define associations between entities to express relationships between entities. With associations it is possible 

to reflect foreign key constraints on database tables, hierarchies and other relations between database 

objects. 

● Key Specification 

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The OData specification requires an EntityType to denote a set of properties forming a unique key. In SAP 

HANA, only tables can have a unique key, the primary key. All other (mostly view) objects require you to 

specify a key for the entity. The OData service definition language (OSDL) enables you to do this by denoting a 

set of existing columns or by generating a local key. Bear in mind that local keys are transient; they exist only 

for the duration of the current session and cannot be dereferenced. 

Note: OSDL is the language used to define a service definition; the language includes a list of keywords 

that you use in the OData service-definition file to enable the required features. 

● Parameter Entity Sets 

You can use a special parameter entity set to enter input parameters for SAP HANA calculation views and 

analytic views. During activation of the entity set, the specified parameters are retrieved from the metadata of 

the calculation (or analytical) view and exposed as a new EntitySet with the name suffix "Parameters", for 

example "CalcViewParameters". 

● Projection 

If the object you want to expose with an OData service has more columns than you actually want to expose, 

you can use SQL views to restrict the number of selected columns in the SELECT. However, for those cases 

where SQL views are not appropriate, you can use the with or without keywords in the OData service 

definition to include or exclude a list of columns. 

8.1.3 OData URI Parameters, Query Options, and Features 

Since OData fully embraces Web technologies, and more specifically URI concepts, all the actions that manage 

the interaction with the service at runtime are controlled by HTTP methods, the URI structure, or URI query 

parameters. 

The examples listed here illustrate how to use the OData service-definition file to specify what data to extract and 

what to do with it. You can find examples of the following features: 

● HTTP Methods 

For example, HTTPGET 

● Resource types 

For example: Service documents, entity sets, $metadata, and so on 

● Query options 

For example, $format, $filter, $select, and so on 

HTTP Methods 

Since the current OData Infrastructure only supports read services (no Create/Update/Delete), the only 

supported HTTP Method is GET and POST for $batch (containing only GET requests). The result is that only read 

requests are possible. 



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Resource Types 

You can use the resource types (or constructs) described and explained here to define how the service definition 

exposes data. For example, the Service Document, Resource Type, or Entity sets enable you to select and view 

the contents of the entity sets that are queried. 

Service Document 

The most basic resource type is the call to the .xsodata resource itself. This supplies information about the 

entity set within this resource; otherwise known as the Service Document. 

● Sample XSODATA Service: 

service namespace "SAMPLE" { 

"sample.hello::hello_tbl" as "Entries"; 

} 

● URI Construct: 

/.xsodata/ 

● Sample URI: 

http://hanaxs:8000/sample/hello/hello_odata.xsodata/ 

● Sample XML Output: 

● Sample JSON Output: 

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Entity Sets 

This construct allows you to view the entire content of the queried Entity Set. 

● URI Construct 

/.xsodata/ 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries 

● Sample ATOM Output: 




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Single Entity 

Any single entity (record) can be accessed by supplying the key field values after the Entity Set. 


○ Single Key: /.xsodata/() 

○ Multiple Keys: /.xsodata/(=,)/ 


○ Single Key: /.xsodata/() 

○ Multiple Keys: http://hanaxs:8000/sap./sflight/spfli.xsodata/ 

FLIGHTS(CARRID='AA',CONNID='0017')# 


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Single Property 

Likewise, any single property of an entry can be directly accessed as well. 


○ Single Key: /.xsodata/()/ 



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○ Multiple Keys: http://hanaxs:8000/sap./sflight/spfli.xsodata/ 

FLIGHTS(CARRID='AA',CONNID='0017')/CITYFROM 


○ Single Key: http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries(1)/ 

TEXT 

○ Multiple Key: http://hanaxs:8000/sap./sflight/spfli.xsodata/ 

FLIGHTS(CARRID='AA',CONNID='0017')/CITYFROM 



$metadata 

This parameter requests that the OData service return a special document that describes the structure of the 

service itself. All properties, their data types, and all associations and relationships are described in this 

document. 


/.xsodata/$metadata 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/$metadata 

● Sample Output: 

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$count 

This request allows you to return the number of records in an Entity Set instead of the details of the Entity Set. It is 

basically the same as using a SELECT COUNT(*) in an SQL Statement without top limitation. 


/.xsodata//$count 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/$count 




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$value 

By specifying this segment after a single property, the service returns the value of the property as plain text. 


/.xsodata//$value 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries(1)/Text/$value 


$batch 

The $batch resource allows you to send multiple requests in one multipart request by using the POST http 

method. 


/.xsodata/$batch 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/$batch 

● Sample Request: 

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● Sample ATOM and JSON Output: 



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Query Parameters 

$format 

This parameter controls the output format. The default format is ATOM. However, the other supported option is 

JSON, which can be triggered by setting the $format=json. 


/.xsodata//$format= 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/$format=json 


$filter 

A parameter that allows you to restrict the entities in the entity set. This option builds a dynamic WHERE condition 

into the underlying query. 


/.xsodata//$filter = '' 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/? 

$filter=CREATED%20eq%20datetime'2012-05-14T08:28:44.405' 


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$orderby 

This is a parameter that controls how the entities in the entity set are sorted. 


/.xsodata//$orderby= asc|desc 



$orderby=CREATED%20desc 




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$skip 

This is a parameter that allows you to skip ahead in an entity set only. It is useful when creating "paging" through 

an entity set. 


/.xsodata//$skip=n 


http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/?$skip=2 


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$top 

This option allows you to limit the number of records returned regardless of how many records exist in the Entity 

Set. It is basically the same as using a SELECT ... UP TO n ROWS in an SQL Statement. 


/.xsodata//$top=n 




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http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/?$top=3 



$inlinecount 

This parameter triggers the OData service to embed an extra property with the total count in the complete entity 

set. This is the count of all entities after the $filter option has been applied. 


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.xsodata//$inlinecount=allpages 



$inlinecount=allpages 



$select 

This property allows you to control which properties for each entity are returned in the entity set. 


/.xsodata//$select=,, 



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http://hanaxs:8000/sample/hello/hello_odata.xsodata/Entries/?$select=TEXT 



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8.1.4 OData Security Considerations 

Enabling access to data by means of OData can create some security-related issues that you need to consider and 

address, for example, the data you want to expose, who can start the OData service, and so on. 

If you want to use OData to expose data to users and clients in SAP HANA application services, you need to bear 

in mind the security considerations described in the following list: 

● Data Access 

Restrict user select authorization for tables/views exposed by the OData service 

● OData Service 

Restrict authorization rights to start the OData service 

● OData Statistical content 

Restrict access to the URL/Path used to expose OData content in the Web browser 

8.1.5 Defining the Data an OData Service Exposes 

An OData service exposes data stored in database tables or views as OData collections for analysis and display by 

client applications. However, first of all, you need to ensure that the tables and views to expose as an OData 

collection actually exist. 

To define the data to expose using an OData service, you must perform at least the following tasks: 

1. Create a database schema. 

2. Create a simple database table to expose with an OData service. 

3. Create a simple database view to expose with an OData service. 

This step is optional; you can expose tables directly. In addition, you can create a repository view (for 

example, Analytic, Attribute, Calculation). 

4. Grant select privileges to the tables and views to be exposed with the OData service. 

8.1.6 Creating an OData Service Definition 

The OData service definition is a configuration file you use to specify which data (for example, views or tables) is 

exposed as an OData collection for analysis and display by client applications. 

An OData service for SAP HANA XS is defined in a text file with the file suffix .xsodata, for example, 

OdataSrvDef.xsodata. The file resides in the package hierarchy of the OData application and must contain at 

least the entry service {}, which would generate an operational OData service with an empty service catalog and 

an empty metadata file. 

Prerequisites for the creation of an OData service definition: 

● SAP HANA studio/client installed and configured 

● SAP HANA database user available with repository privileges (for example, to add packages) 

● A SAP HANA development system added to (and available in) SAP HANA studio, for example, in either the 

Navigator view or the SAP HANA Repositories view 

● A working development environment including a repository workspace, a package structure for your OData 

application, and a shared project to enable you to synchronize changes to the OData project files in the local 

file system with the repository 



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● Defined data to expose with the OData application, for example, at least the following: 

○ A database schema 

○ A database table 

1. In the shared project you are using for your OData application, use the Project Explorer view to locate the 

package where you want to create the new OData service definition. 

Note: The file containing the OData service definition must be placed in the root package of the OData 

application for which the service is intended. 

2. Create the file that will contain your OData service definition. 

In the Project Explorer view, right-click the folder where you want to create the new OData service-definition 

file and choose New File in the context-sensitive popup menu. 

3. Define the OData service. 

The OData service definition uses the OData Service Definition Language (OSDL), which includes a list of 

keywords that you specify in the OData service-definition file to enable important features. 

The following example shows a simple OData service definition exposing a simple table: 

service namespace "my.namespace" { 

"sample.odata:table.hdbtable" as "MyTable"; 

} 

This service definition exposes a table defined in the file sample.odata:table.hdbtable and creates an 

EntitySet for this entity named MyTable. The specification of an alias is optional. If omitted, the default name 

of the EntitySet is the name of the repository object file, in this example, table. 

4. Place the valid OData service definition in the root package of the OData application to which it applies. 

5. Save, commit, and activate the OData service definition in the SAP HANA repository. 

Related Links 

OData Service Definitions [page 165] 

The OData service definition is the mechanism you use to define what data to expose with OData, how, and to 

whom. Data exposed as an OData collection is available for analysis and display by client applications, for 

example, a browser that uses functions provided by an OData client library running on the client system. 

8.1.7 OData Service Definition Language Syntax 

The OData Service Definition Language (OSDL) provides a set of keywords that enable you to set up an ODATA 

service definition file that specifies what data to expose, in what way, and to whom. 

The following list shows the syntax of the OData Service Definition Language (OSDL) in an EBNF-like format; 

conditions that apply for usage are listed after the table. 

definition :='service' [namespace] body 

namespace :='namespace' quotedstring 

quotedstring :=quote string quote 

string :=UTF8 

quote :='"' 

body :='{' content '}' 

content :=entry [content] 

entry :=( entity | association ) ';' 

entity :=object [entityset] [with] [keys] [navigates] 

[aggregates] [parameters] 

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object :=['entity'] ( repoobject | catalogobject ) 

repoobject :=quote repopackage '/' reponame '.' repoextension 

quote 

repopackage :=string 

reponame :=string 

repoextension :=string 

catalogobject :=catalogobjectschema '.' catalogobjectname 

catalogobjectschema :=quotedstring 

catalogobjectname :=quotedstring 

entityset :='as' entitysetname 

entitysetname :=quotedstring 

with :=( 'with' | 'without' ) propertylist 

propertylist :='(' columnlist ')' 

columnlist :=columnname [',' columnlist] 

columnname :=quotedstring 

keys :='keys' ( keylist | keygenerated ) 

keylist :=propertylist 

keygenerated :='generate' ( keygenlocal ) 

keygenlocal :='local' columnname 

navigates :='navigates' '(' navlist ')' 

navlist :=naventry [',' navlist] 

naventry :=assocname 'as' navpropname [fromend] 

assocname :=quotedstring 

navpropname :=quotedstring 

fromend :='from' ( 'principal' | 'dependent' ) 

aggregates :='aggregates' 'always' [aggregatestuple] 

aggregatestuple :='(' aggregateslist ')' 

aggregateslist :=aggregate [',' aggregateslist] 

aggregate :=aggregatefunction 'of' columnname 

aggregatefunction :=( 'SUM' | 'AVG' | 'MIN' | 'MAX' ) 

parameters :='parameters' 'via' 'entity' 

[parameterentitysetname] [parametersresultsprop] 

parameterentitysetname :=quotedstring 

parametersresultsprop :='results' 'property' quotedstring 

association :=associationdef principalend dependentend 

[assoctable] 

associationdef :='association' assocname 

principalend :='principal' end 

dependentend :='dependent' end 

end :=endref multiplicity 

endref :=endtype '(' joinproperties ')' 

endtype :=entitysetname 

joinproperties :=columnlist 

multiplicity :='multiplicity' quote multiplicityvalue quote 

multiplicityvalue :=( '1' | '0..1' | '1..*' | '*' ) 

assoctable :='over' repoobject overprincipalend 

overdependentend 

overprincipalend :='principal' overend 

overdependentend :='dependent' overend 

overend :=propertylist 

Conditions 

The following conditions apply when using the listed keywords: 

1. If the namespace is not specified, the schema namespace in the EDMX metadata document will be the 

repository package of the service definition file concatenated with the repository object name. E.g. if the 



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epository design time name of the .xsodata file is sap.hana.xs.doc/hello.xsodata the 

namespace will implicitly be sap.hana.xs.doc.hello. 

2. keyslist must not be specified for objects of type 'table'. They must only be applied to objects referring a 

view type. keygenerated in turn, can be applied to table objects. 

3. If the entityset is not specified in an entity, the EntitySet for this object is named after the repository 

object name or the catalogobjectname. E.g. if object is "sap.hana.xs.doc/odata_docu" the 

entitysetname is implicitly set to odata_docu which then can also be referenced in associations. 

4. The fromend in a naventry must be specified if the endtype is the same for both the principalend 

and the dependentend of an association. 

5. The number of joinproperties in the principalend must be the same as in the dependentend. 

6. Ordering in the joinproperties of ends is relevant. The first columnname in the joinproperties of 

the principalend is compared with the first columnname of the dependentend, the second with the 

second, and so on. 

7. The overprincipalend corresponds to the principalend. The number of properties in the 

joinproperties and the overproperties must be the same and their ordering is relevant. The same 

holds for the dependent end. 

8. aggregates can only be applied in combination with keygenerated. 

9. If aggregatestuple is omitted, the aggregation functions are derived from the database. This is only 

possible for calculation views and analytic views. 

10. Specifying parameters is only possible for calculation views and analytic views. 

11. The default parameterentitysetname is the entitysetname of the entity concatenated with the 

suffix "Parameters". 

12. If the parametersresultsprop is omitted, the navigation property from the parameter entity set to the 

entity is called "Results". 

8.1.8 OData Service Definition: SQL-EDM Type Mapping 

During the activation of the OData service definition, the SAP HANA SQL types are mapped to the required OData 

EDM types according to the rules specified in a mapping table. 

The following mapping table lists how SAP HANA SQL types are mapped to OData EDM types during the 

activation of an OData service definition. 

Note: The OData implementation in SAP HANA XS supports only those SQL types listed in the following 

table. 

Table 8: SAP HANA SQL to OData EDM Type Mapping 

SAP HANA SQL Type OData EDM Type 

Time Edm.Time 

Date Edm.DateTime 

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SAP HANA SQL Type OData EDM Type 

SecondDate Edm.DateTime 

LongDate Edm.DateTime 

Timestamp Edm.DateTime 

TinyInt Edm.Byte 

SmallInt Edm.Int16 

Integer Edm.Int32 

BigInt Edm.Int64 

SmallDecimal Edm.Decimal 

Decimal Edm.Decimal 

Real Edm.Single 

Float Edm.Single 

Double Edm.Double 

Varchar Edm.String 

NVarchar Edm.String 

Char Edm.String 

NChar Edm.String 

Binary Edm.Binary 

Varbinary Edm.Binary 

Example SQL Type Mapping 

The following examples shows how SAP HANA SQL types (name, integer, Varchar) of columns in a table are 

mapped to the OData EDM types in the properties of an entity type. 

SAP HANA SQL: 

{name = "ID"; sqlType = INTEGER; nullable = false;}, 

{name = "RefereeID"; sqlType = VARCHAR; nullable = true;} 

The following example illustrates how the SAP HANA SQL types illustrated in the previous example are mapped to 

EDM types: 

 

 



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8.1.9 OData Service-Definition Examples 

The OData service definition describes how data exposed in an end point can be accessed by clients using the 

OData protocol. 

Each of the examples listed below is explained in a separate section. The examples show how to use the OData 

Service Definition Language (OSDL) in the OData service-definition file to generate an operational OData service 

that enables clients to use SAP HANA XS to access the OData end point you set up. 

● Empty Service 

● Namespace Definition 

● Object Exposure 

● Property Projection 

● Key Specification 

● Associations 

● Aggregation 

● Parameter Entity Sets 

OData Empty Service 

An OData service for SAP HANA XS is defined by a text file containing at least the following line: 

Service definition sample.odata:empty.xsodata 

service {} 

A service file with the minimal content generates an empty, completely operational OData service with an empty 

service catalog and an empty metadata file: 

http://localhost:8002/sample/odata/empty.xsodata 

http://localhost:8002/sample/odata/empty.xsodata/$metadata 

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An empty service metadata document consists of one Schema containing an empty EntityContainer. The 

name of the EntityContainer is the name of the .xsodata file, in this example "empty". 

OData Namespace Definition 

By default, as shown in the metadata file of an empty OData service, the namespace of the generated Schema is 

created by concatenating the package name of the .xsodata file with the file name, and separating the 

concatenated names with a dot. You can specify your own namespace by using the namespace keyword: 

Service definition sample.odata:namespace.xsodata 

service namespace "my.namespace" {} 

The resulting service metadata document has the specified schema namespace: 

http://localhost:8002/sample/odata/namespace.xsodata/$metadata 

OData Object Exposure 

There are two ways of exposing SAP HANA objects. You can either specify the repository design-time name or the 

database-object runtime name (with database schema). Although both variants are supported, the preferred 

method is the exposure via the repository design-time name. It has the advantage that the OData service is 

automatically updated, if the underlying repository object changes. The support for database objects is mainly 

intended for existing or replicated objects that do not have a related repository design-time object. 

In the examples provided to illustrate object exposure, the following definition of a table applies: 



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Table definition sample.odata:table.hdbtable 

table.schemaName = "ODATASAMPLES"; 



{name = "ID"; sqlType = INTEGER;}, 

{name = "Text"; sqlType = NVARCHAR; length=1000;}, 

{name = "Time"; sqlType = TIMESTAMP;} 

]; 

table.primaryKey.pkcolumns = ["ID"]; 

Repository Objects 

If the object to expose via an OData service is created during an activation in the repository, then it has a 

repository design-time representation. Examples for those objects are tables, SQL views and calculation views. An 

example for exposing the table above is shown in the next listing. 

Service definition sample.odata:repo.xsodata 

service { 

"sample.odata:table.hdbtable" as "MyTable"; 

} 

This service definition exposes a table defined in the .hdbtable file sample.odata:table.hdbtable and 

creates an EntitySet for this entity named "MyTable". The specification of an alias is optional. If omitted the 

default name of the EntitySet is the name of the repository object file, here "table". 

http://localhost:8002/sample/odata/repo.xsodata 

http://localhost:8002/sample/odata/repo.xsodata/$metadata 

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All information about the table, for example, the properties, the data types, and the primary key, is gathered from 

the database catalog. 

Database Objects 

Caution: Do not use catalog objects if a repository design-time object is available, as changes in the 

catalog object are not automatically reflected in the OData service. 

Similar to the exposure of an object by using the repository design-time name is the exposure by the database 

name: 

Service definition sample.odata:db.xsodata 

service { 

"ODATASAMPLES"."sample.odata:table.hdbtable" as "MyTable"; 

} 

The service exposes the same table by using the database catalog name of the object and the name of the 

schema where the table is created in. The collection in the service catalog and the EntityType that is created in the 

metadata document is exactly the same as for repository objects. 



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OData Property Projection 

If the object you want to expose with an OData service has more columns than you actually want to expose, you 

can use SQL views to restrict the number of selected columns in the SELECT. 

Nevertheless, SQL views are sometimes not appropriate, for example with calculation views, and for these cases 

we provide the possibility to restrict the properties in the OData service definition in two ways. By providing an 

including or an excluding list of columns. 

Including Properties 

You can specify the columns of an object that have to be exposed in the OData service by using the with keyword. 

Key fields of tables must not be omitted. 

Service definition sample.odata:with.xsodata 

service { 

"sample.odata:table.hdbtable" as "MyTable" with ("ID","Text"); 

} 

The resulting EntityType then contains only the properties derived from the specified columns: 

http://localhost:8002/sample/odata/with.xsodata/$metadata 

Excluding Properties 

The opposite of the with keyword is the without keyword, which enables you to specify which columns you do 

NOT want to expose in the OData service: 

Service definition sample.odata::without.xsodata 

service { 

"sample.odata:table.hdbtable" as "MyTable" without ("Text","Time"); 

} 

The generated EntityType then does NOT contain the properties derived from the specified columns: 

http://localhost:8002/sample/odata/without.xsodata/$metadata 

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OData Key Specification 

The OData specification requires an EntityType to denote a set properties forming a unique key. In HANA only 

tables may have a unique key, the primary key. For all other (mostly view) objects you need to specify a key for the 

entity. In OSDL you can do this by denoting a set of existing columns or by generating a key. 

For the examples illustrating key specification, we use the following SQL view, which selects all data from the 

specified table. 

View definition sample.odata:view.hdbview 

{ 

} 

"name": "view", 

"schema": "ODATASAMPLES", 

"query": "SELECT * FROM \"ODATASAMPLES\".\"sample.odata::table\"" 

Existing Key Properties 

If the object has set of columns that may form a unique key, you can specify them as key for the entity. These key 

properties are always selected from the database, no matter if they are omitted in the $select query option. 

Therefore explicit keys are not suitable for calculation views and analytic views as the selection has an impact on 

the result. 

Service definition sample.odata:explicitkeys.xsodata/$metadata 

service { 

"sample.odata:view.hdbview" as "MyView" keys ("ID","Text"); 

} 

The created metadata document for the exposure of the view above is almost equal to the metadata document for 

repository objects. Only the key is different and consists now of two columns: 

http://localhost:8002/sample/odata/explicitkeys.xsodata/$metadata 



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Caution: The OData infrastructure cannot check whether your specified keys are unique. So be careful 

when choosing keys. 

Generated Local Key 

For objects that do not have a unique key in their results, for example, calculation views or aggregated tables, you 

can generate a locally valid key. This key value numbers the results starting with 1 and is not meant for 

dereferencing the entity; you cannot use this key to retrieve the entity. The key is valid only for the duration of the 

current session and is used only to satisfy OData's need for a unique ID in the results. The property type of a 

generated local key is Edm.String and cannot be changed. 

Service definition sample.odata:generatedkeys.xsodata 

http://localhost:8002/sample/odata/generatedkeys.xsodata/$metadata 

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As a consequence of the transient nature of generated local keys, it is not possible to define navigation properties 

on these entities or use them in filter or order by conditions. 

OData Associations 

You can define associations between entities to express relationships between entities. With associations it is 

possible to reflect foreign key constraints on database tables, hierarchies and other relations between database 

objects. OSDL supports simple associations, where the information about the relationship is stored in one of the 

participating entities, and complex associations, where the relationship information is stored in a separate 

association table. 

Associations themselves are freestanding. On top of them you can specify which of the entities participating in the 

relationship can navigate over the association to the other entity by creating NavigationPropertys. 

For the examples used to illustrate OData associations, we use the tables customer and order: 

Table definition: sample.odata:customer.hdbtable 





{name = "RecruitID"; sqlType = VARCHAR; nullable = true;} 

]; 


Table definition: sample.odata:order.hdbtable 





{name = "CustomerID"; sqlType = INTEGER; nullable = false;} 

]; 


There is one relationship order.CustomerID to customer.ID and one relationship 

customer.RecruitID to customer.ID. 



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Simple Associations 

The definition of an association requires you to specify a name, which references two exposed entities and whose 

columns keep the relationship information. To distinguish the ends of the association, you must use the keywords 

principal and dependent. In addition, it is necessary to denote the multiplicity for each end of the 

association. 

Service definition: sample.odata:assocsimple.xsodata 

service { 

"sample.odata:customer.hdbtable" as "Customers"; 

"sample.odata:order.hdbtable" as "Orders"; 

association "Customer_Orders" principal "Customers"("ID") multiplicity 

"1" dependent "Orders"("CustomerID") multiplicity "*"; 

} 

The association in the example above with the name Customer_Orders defines a relationship between the 

table customer, identified by its EntitySet name Customers, on the principal end, and the table 

order, identified by its entity set name Orders, on the dependent end. Involved columns of both tables are 

denoted in braces ({}) after the name of the corresponding entity set. The multiplicity keyword on each end 

of the association specifies their cardinality - in this example, one-to-many. 

The number of columns involved in the relationship must be equal for both ends of the association, and their order 

in the list is important. The order specifies which column in one table is compared to which column in the other 

table. In this simple example, the column customer.ID is compared to order.CustomerID in the generated 

table join. 

As a result of the generation of the service definition above, an AssociationSet named Customer_Orders 

and an Association with name Customer_OrdersType are generated: 

http://localhost:8002/sample/odata/assocsimple.xsodata/$metadata 

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The second association is similar to the first one and is shown in the following listing: 

association "Customer_Recruit" principal "Customers"("ID") multiplicity 

"1" dependent "Customers"("RecruitID") multiplicity "*"; 

Complex Associations 

For the following example of a complex association, an additional table named knows is introduced that contains a 

relationship between customers. 

Table definition: sample.odata:knows.hdbtable 




{name = "KnowingCustomerID"; sqlType = INTEGER; nullable = false;}, 

{name = "KnownCustomerID"; sqlType = INTEGER; nullable = false;} 



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]; 

table.primaryKey.pkcolumns = ["KnowingCustomerID","KnownCustomerID"]; 

Relationships that are stored in association tables such as knows can be similarly defined as simple associations. 

Use the keyword over to specify the additional table and any required columns. 

Service definition: sample.odata:assoccomplex.xsodata 

service { 

"sample.odata:customer.hdbtable" as "Customers"; 


association "Customer_Orders" 

principal "Customers"("ID") multiplicity "*" 

dependent "Customers"("ID") multiplicity "*" 

over "sample.odata:knows.hdbtable" principal ("KnowingCustomerID") 

dependent ("KnownCustomerID"); 

} 

With the keywords principal and dependent after over you can specify which columns from the 

association table are joined with the principal respectively dependent columns of the related entities. The 

number of columns must be equal in pairs, and their order in the list is important. 

The generated Association in the metadata document is similar to the one created for a simple association 

except that the ReferentialConstraint is missing: 

tp://localhost:8002/sample/odata/assoccomplex.xsodata/$metadata 

Navigation Properties 

By only defining an association, it is not possible to navigate from one entity to another. Associations need to be 

bound to entities by an NavigationProperty. You can create them by using the keyword navigates: 

Service definition: sample.odata:assocnav.xsodata 

service { 

"sample.odata:customer.hdbtable" as "Customers" navigates 

("Customer_Orders" as "HisOrders"); 



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} 

The example above says that it is possible to navigate from Customers over the association 

Customer_Order via the NavigationProperty named "HisOrders". 

The right association end is determined automatically by the entity set name. But if both ends are bound to the 

same entity, it is necessary to specify the starting end for the navigation. This is done by specifying either from 

principal or from dependent which refer to the principal and dependent ends in the association. 

Service definition: sample.odata:assocnavself.xsodata 

service { 

"sample.odata:customer.hdbtable" as "Customers" 

navigates ("Customer_Orders" as "HisOrders","Customer_Recruit" as 

"Recruit" from principal); 




association "Customer_Recruit" principal "Customers"("ID") 

multiplicity "1" dependent "Customers"("RecruitID") multiplicity "*"; 

} 

In both cases a NavigationProperty is added to the EntityType. 

http://localhost:8002/sample/odata/assocnavself.xsodata/$metadata 

OData Aggregation 

The results of aggregations on columns change dynamically depending on the grouping conditions. This means 

that aggregation cannot be performed in SQL views; it needs to be specified in the OData service definition itself. 

Depending on the type of object to expose, you need to explicitly specify the columns to aggregate and the 

function to use or derived them from metadata in the database. 

In general, aggregations do not have consequences for the metadata document. It just effects the semantics of 

the concerning properties during runtime. The grouping condition for the aggregation contain all selected nonaggregated 

properties. Furthermore, aggregated columns cannot be used in $filter, and aggregation is only 

possible with generated keys. 



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Derived Aggregation 

The simplest way to define aggregations of columns in an object is to derive this information from metadata in the 

database. The only objects with this information are calculation views and analytic views. For all other object 

types, for example, tables and SQL views, the activation will not work. To cause the service to use derived 

information, you must specify the keywords aggregates always, as illustrated in the following example: 

service { 

"sample.odata:calc.calculationview" as "CalcView" 

keys generate local "ID" 

aggregates always; 

} 

Explicit Aggregation 

The example for the explicit aggregation is based on the following table definition: 

sample.odata:revenues.hdbtable 




{name = "Month"; sqlType = INTEGER; nullable = false;}, 

{name = "Year"; sqlType = INTEGER; nullable = false;}, 

{name = "Amount"; sqlType = INTEGER; nullable = true;} 

]; 

table.primaryKey.pkcolumns = ["Month","Year"]; 

You can aggregate the columns of objects (without metadata) that are necessary for the derivation of aggregation 

by explicitly denoting the column names and the functions to use, as illustrated in the following example of a 

service definition: sample.odata:aggrexpl.xsodata 

service { 

"sample.odata:revenues.hdbtable" as "Revenues" 


aggregates always (SUM of "Amount"); 

} 

The results of the entity set Revenues always contain the aggregated value of the column Amount. To extract 

the aggregated revenue amount per year, add $select=Year,Amount to your requested URI. 

OData Parameter Entity Sets 

SAP HANA calculation views and analytic views can interpret input parameters. For OData, these parameters can 

be entered by using a special parameter entity set. 

Parameter entity sets can be generated for both calculation views and analytic views by adding parameters via 

entity to the entity: 

service { 



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} 

parameters via entity; 

During activation, the parameters specified in sample.odata:calc.calculationview are retrieved from 

the metadata of the calculation view and exposed as a new EntitySet named after the entity set name and the 

suffix Parameters, for example, CalcViewParameters. A NavigationProperty named Results is 

generated to retrieve the results from the parameterized call. 

The name of the generated parameter entity set and the navigation property can be customized, as illustrated in 

the following example: 

service { 



parameters via entity "CVParams" results property "Execute"; 

} 

With the definition above, the name of the parameter entity set is CVParams, and the name of the 

NavigationProperty for the results is Execute. 

8.2 Data Access with XMLA in SAP HANA XS 

In SAP HANA Extended Application Services, the persistence model (for example, tables, views and stored 

procedures) is mapped to the consumption model that is exposed to clients - the applications you write to extract 

data from the SAP HANA database. 

You can map the persistence and consumption models with XML for Analysis (XMLA). With XMLA, you write 

multi-dimensional -expressions (MDX) queries wrapped in an XMLA document. An XML for Analysis (XMLA) 

application running in SAP HANA application services is used to provide the consumption model for client 

applications exchanging MDX queries (wrapped in XMLA documents) with the SAP HANA database. 

XMLA uses Web-based services to enable platform-independent access to XMLA-compliant data sources for 

Online Analytical Processing (OLAP). XMLA enables the exchange of analytical data between a client application 

and a multi-dimensional data provider working over the Web, using a Simple Object Access Protocol (SOAP)based 

XML communication application-programming interface (API). 

Applications running in SAP HANA XS enable very accurate control of the flow of data between the presentational 

layer, for example, in the Browser, and the data-processing layer in SAP HANA itself, where the calculations are 

performed, for example in SQL or SqlScript. If you develop and deploy an XMLA service running in SAP HANA XS, 

you can take advantage of the embedded access to SAP HANA that SAP HANA XS provides; the embedded 

access greatly improves end-to-end performance. 

8.2.1 XML for Analysis (XMLA) 

XML for Analysis (XMLA) uses Web-based services to enable platform-independent access to XMLA-compliant 

data sources for Online Analytical Processing (OLAP). 

XMLA enables the exchange of analytical data between a client application and a multi-dimensional data provider 

working over the Web, using a Simple Object Access Protocol (SOAP)-based XML communication applicationprogramming 

interface (API). 

Implementing XMLA in SAP HANA enables third-party reporting tools that are connected to the SAP HANA 

database to communicate directly with the MDX interface. The XMLA API provides universal data access to a 



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particular source over the Internet, without the client having to set up a special component. XML for Analysis is 

optimized for the Internet in the following ways: 

● Query performance 

Time spent on queries to the server is kept to a minimum 

● Query type 

Client queries are stateless by default; after the client has received the requested data, the client is 

disconnected from the Web server. 

In this way, tolerance to errors and the scalability of a source (the maximum permitted number of users) is 

maximized. 

XMLA Methods 

The specification defined in XML for Analysis Version 1.1 from Microsoft forms the basis for the implementation of 

XML for Analysis in SAP HANA. 

The following list describes the methods that determine the specification for a stateless data request and 

provides a brief explanation of the method's scope: 

● Discover 

Use this method to query metadata and master data; the result of the discover method is a rowset. You can 

specify options, for example, to define the query type, any data-filtering restrictions, and any required XMLA 

properties for data formatting. 

● Execute 

Use this method to execute MDX commands and receive the corresponding result set; the result of the 

Execute command could be a mult-idimensional dataset or a tabular rowset. You can set options to specify 

any required XMLA properties, for example, to define the format of the returned result set or any local 

properties to use to determine how to format the returned data. 

8.2.2 XMLA Service Definition 

The XMLA service definition is a file you use to specify which data is exposed as XMLA collections. Exposed data is 

available for analysis and display by client applications, for example, a browser that uses functions provided either 

by the XMLA service running in SAP HANA XS or by an XMLA client library running on the client system. 

To expose information via XMLA to applications using SAP HANA Extended Application Services (SAP HANA XS), 

you define database views that provide the data with the required granularity and you use the XMLA service 

definition to control access to the exposed data. 

Note: SAP HANA XS supports XMLA version 1.1, which you can use to send MDX queries. 

An XMLA service for SAP HANA XS is defined in a text file with the file suffix .xsxmla, for example, 

XMLASrvDef.xsxmla. The file must contain only the entry {*}, which would generate a completely 

operational XMLA service. 

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XMLA Service-Definition Keywords 

Currently, the XMLA service-definition file enables you to specify only that all authorized data is exposed to XMLA 

requests, as illustrated in the following example: 

Service {*} 

8.2.3 XMLA Security Considerations 

Enabling access to data by means of XMLA opens up some security considerations that you need to address, for 

example, the data you want to expose, who can start the XMLA service, and so on. 

If you want to use XMLA to expose data to users and clients in SAP HANA XS, you need to bear in mind the 

security considerations described in the following list: 

● Data Access 

● 

Restrict user select authorization for data exposed by the XMLA service 

● XMLA Statistical content 

Restrict access to the URL/Path used to expose XMLA content in the Web browser, for example, using the 

application-access file (.xsaccess) 

8.2.4 Multidimensional Expressions (MDX) 

Multidimensional Expressions (MDX) is a language you can use to query multidimensional data stored in OLAP 

cubes. 

MDX uses a multidimensional data model to enable navigation in multiple dimensions, levels, and up and down a 

hierarchy. With MDX, you can access pre-computed aggregates at specified positions (levels or members) in a 

hierarchy. 

Note: MDX is an open standard. However, SAP has developed extensions to MDX that are designed to 

enable faster and more efficient access to multidimensional data, for example, to serve specific SAP 

HANA application requirements and to optimize the resultset for SAP HANA clients. 

MDX is implicitly a hierarchy-based paradigm. All members of all dimensions must belong to a hierarchy. Even if 

you do not explicitly create hierarchies in your SAP HANA data model, the SAP HANA modeler implicitly 

generates default hierarchies for each dimension. All identifiers that are used to uniquely identify hierarchies, 

levels and members in MDX statements (and metadata requests) embed the hierarchy name within the identifier. 

In SAP HANA, the standard use of MDX is to access SAP HANA models (for example, analytical and attribute 

views) that have been designed, validated and activated in the modeler in the SAP HANA studio. The studio 

provides a graphical design environment that enables detailed control over all aspects of the model and its 

language-context-sensitive runtime representation to users. 

MDX in SAP HANA uses a runtime cube model, which usually consists of an analytical (or calculation) view that 

represents data in which dimensions are modeled as attribute views. You can use the analytical view to specify 

whether a given attribute is intended for display purposes only or for aggregation. The key attributes of attribute 

views are linked to private attributes in an analytical view in order to connect the entities. One benefit of MDX in 

SAP HANA is the native support of hierarchies defined for attribute views. 

Note: MDX in SAP HANA includes native support of hierarchies defined for attribute views. SAP HANA 

supports level-based and parent-child hierarchies and both types of hierarchies are accessible with MDX. 



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SAP HANA supports the use of variables in MDX queries; the variables are a SAP-specific enhancement to 

standard MDX syntax. You can specify values for all mandatory variables that are defined in SAP HANA studio to 

various modeling entities. The following example illustrates how to declare SAP HANA variables and their values: 

MDX 

Select 

From [MINI_C1_VAR] 

Where [Measures].[M2_1_M3_CONV] 

SAP VARIABLES [VAR_VAT] including 10, 

[VAR_K2] including 112, 

[VAR_TARGET_CURRENCY] including 'EUR', 

8.2.5 MDX Functions 

MDX in SAP HANA supports a variety of standard MDX functions. 

Table 9: Supported MDX Functions 

Function Description 

Aggregate Returns a calculated value using the appropriate aggregate function, based on the 

aggregation type of the member. 

Ancestor Returns the ancestor of a member at a specified level or at a specific distance away 

in the hierarchy. 

Ancestors Returns a set of all ancestors of a member at a specified level or at a specific 

distance away in the hierarchy. 

Ascendants Returns the set of the ascendants of the member. 

Avg Returns the average value of a numeric expression evaluated over a set. 

BottomCount Returns a specified number of items from the bottom of a set, optionally sorting 

the set first. 

Children Returns the children of a member. 

ClosingPeriod Returns the last sibling among the descendants of a member at a specified level. 

Count Counts the number of members in the tuple. 

Cousin Returns the child member with the same relative position under a parent member 

as the specified child member. 

Crossjoin Returns the cross product of two sets. 

CurrentMember Returns the current member along a hierarchy. 

DefaultMember Returns the default member of a hierarchy. 

Descendants Returns the set of descendants of a member at a specified level or at a specific 


Dimension Returns the hierarchy that contains a specified member or level. 

Dimensions Returns a hierarchy specified by a numeric or string expression. 

Distinct Returns a set, removing duplicate tuples from a specified set. 

DistinctCount Returns the number of distinct tuples in a set. 

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DrillDownLevel Drills down the members of a set one level below the lowest level represented in the 

set, or to one level below an optional level of a member represented in the set. 

DrillDownLevelBottom Drills down the members of a specified count of bottom members of a set, at a 

specified level, to one level below. 

DrillDownLevelTop Drills down a specified count of top members of a set, at a specified level, to one 

level below. 

DrillDownMember Drills down the members in a specified set that are present in a second specified 

set. 

DrillDownMemberBottom Drills down the members in a specified set that are present in a second specified 

set, limiting the result set to a specified number of bottommost members. 

DrillDownMemberTop Drills down the members in a specified set that are present in a second specified 

set, limiting the result set to a specified number of topmost members. 

DrillUpLevel Drills up the members of a set that are below a specified level. 

DrillUpmember Drills up the members in a specified set that are present in a second specified set. 

Except Finds the difference between two sets, optionally retaining duplicates. 

Filter Returns the set resulting from filtering a set based on a search condition. 

FirstChild Returns the first child of a specified member. 

FirstSibling Returns the first child of the parent of a specified member. 

Generate Applies a set to each member of another set, and then joins the resulting sets by 

union. Alternatively, this function returns a concatenated string created by 

evaluating a string expression over a set. 

Head Returns the first specified number of elements in a set. 

Hierarchize Orders the members of a specified set in a hierarchy in natural or, optionally, postnatural 

order. 

Hierarchy 

Instr The InStr function finds the starting location of a substring within a specified string. 

Intersect Returns the intersection of two sets, optionally retaining duplicates. 

IsAncestor Returns true if the first member specified is an ancestor of the second member 

specified, else returns false. 

IsGeneration Returns true if the member specified is a leaf, else returns false. 

IsLeaf Returns true if the first member specified is an ancestor of the second member 


IsSibling Returns true if the first member specified is an sibling of the second member 


Item If an integer is specified, the Item function returns the tuple that is in the zerobased 

position specified by Index. 

IIF Returns one of values determined by a logical test. 



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Lag Returns the member that is a specified number of positions prior to a specified 

member along the dimension of the member. 

LastChild Returns the last child of a specified member. 

LastPeriods Returns a set of members prior to and including a specified member. 

LastSibling Returns the last child of the parent of a specified member. 

Lead Returns the member that is a specified number of positions following a specified 


Leaves If a dimension name is specified, returns a set that contains the leaf members of 

the key attribute for the specified dimension.If a dimension name is not specified, 

the function returns a set that contains the leaf members of the entire cube. 

Left The Left function returns a string of a specified number of characters from the left 

side (beginning) of a specified string. 

Level Returns the level of a member. 

Levels Returns the level whose zero-based position in a dimension is specified by a 

numeric expression. 

Max Returns the maximum value of a numeric expression evaluated over a set. 

Member_caption Returns the caption of a member 

Members Returns the set of all members in a specified hierarchy. 

MembersAscendantsDesc 

endants 

Returns the set of specified members in a given hierarchy. 

Mid The Mid function returns a substring of a string argument. 

Min Returns the minimum value of a numeric expression evaluated over a set 

MTD Returns a set of members from the Month level in a Time dimension starting with 

the first period and ending with a specified member. 

Name Returns the name of a specified hierarchy or member. 

NextMember Returns the next member in the level that contains a specified member. 

NOT Performs a logical negation on a numeric expression. 

OpeningPeriod Returns the first sibling among the descendants of a specified level, optionally at a 

specified member. 

OR Performs a logical disjunction on two numeric expressions. 

Ordinal Returns the zero-based ordinal value associated with a specified level. 

ParallelPeriod Returns a member from a prior period in the same relative position as a specified 

member. 

Parent Returns the parent of a specified member. 

PeriodsToDate Returns a set of members (periods) from a specified level starting with the first 

member and ending with a specified member. 

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PrevMember Returns the previous member in the level that contains a specified member. 

Properties Returns a string containing the value of the specified member property. 

QTD Returns a set of members from the Quarter level in a Time dimension starting with 


Range Performs a set operation that returns a naturally ordered set, with the two 

specified members as endpoints, and all members between the two specified 

members included as members of the set 

Right The Right function returns a string of a specified number of characters from the 

right side (end) of a specified string. 

Siblings Returns the set of siblings of a specified member, including the member itself. 

StrToMember Returns a member from a string expression in MDX format. 

StrToSet Constructs a set from a specified string expression in MDX format. 

StrToTuple Constructs a tuple from a specified string expression in MDX format. 

StrToValue Returns a value from a string expression 

Subset Returns a subset of tuples from a specified set. 

Sum Returns the sum of a numeric expression evaluated over a specified set. 

Tail Returns the last specified number of elements in a set. 

TopCount Returns a specified number of items from the topmost members of a specified set, 

optionally ordering the set first. 

Union Performs a set operation that returns a union of two sets, removing duplicate 

members. 

UniqueName Returns the unique name of a specified hierarchy. 

WTD Returns a set of members from the Week level in a Time dimension starting with 


YTD Returns a set of members from the Year level in a Time dimension starting with the 

first period and ending with a specified member. 

8.2.6 MDX Extensions 

SAP HANA supports several extensions to the MDX language, for example, additional predefined functions and 

support for variables. 

Sibling_Ordinal Intrinsic Property 

The object Member includes a property called Sibling_Ordinal, that is equal to the 0-based position of the 

member within its siblings. 

WITH 

MEMBER [Measures].[Termination Rate] AS 

[Measures].[NET_SALES] / [Measures].[BILLED_QUANTITY] 

SELECT 

{ 

[Measures].[NET_SALES], 



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[Measures].[BILLED_QUANTITY], 

[Measures].[Termination Rate] 

} ON COLUMNS, 

Descendants 

( 

[MDX_TEST_10_DISTRIBUTION_CHANNEL]. 

[MDX_TEST_10_DISTRIBUTION_CHANNEL].[All].[(all)], 

1, 

SELF_AND_BEFORE 

) 

DIMENSION PROPERTIES SIBLING_ORDINAL ON ROWS 

FROM MDX_TEST_10_ITELO_SALES_DATA 

MembersAscendantsDescendants Function 

SAP HANA includes a new function called MembersAscendantsDescendants that enables you to get, for 

example, all ascendants and descendants of a specific member. This function improves on the standard MDX 

functions Ascendants and Descendants. 

The function can be called as follows: 

MembersAscendantsDescendants (, ) 

● set: A set of members from a single hierarchy 

● flag: Indicates which related members to return, and can be one of the following: 

○ MEMBERS_AND_ASCENDANTS_AND_DESCENDANTS 

○ MEMBERS_AND_ASCENDANTS 

○ MEMBERS_AND_DESCENDANTS 

○ ASCENDANTS_AND_DESCENDANTS 

○ ONLY_ASCENDANTS 

○ ONLY_DESCENDANTS 

SELECT 

{ [Measures].[SALES] } 

ON COLUMNS, 

NON EMPTY 

{ Hierarchize( MembersAscendantsDescendants([JUICE_TIME].[TimeHier]. 

[QUARTER].[3]:[JUICE_TIME].[TimeHier].[QUARTER].[4], 

MEMBERS_AND_ASCENDANTS_AND_DESCENDANTS )) } 

ON ROWS 

FROM [JUICE] 

SELECT 


ON COLUMNS, 

NON EMPTY 



ONLY_ASCENDANTS )) } 

ON ROWS 

FROM [JUICE] 

Variables 

An MDX SELECT statement in SAP HANA enables you to send values for variables defined within modeling views. 

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Analytic and calculation views can contain variables, that can be bound to specific attributes. When calling the 

view, you can send values for those variables. These variables can be used, for example, to filter the results. 

SAP HANA supports an extension to MDX whereby you can pass values for variables defined in views by adding a 

SAP Variables clause in your select statement. Here is the syntax for a Select statement: 

: [WITH ] 

SELECT [[,...]] 

FROM 

[WHERE 

SAP VARIABLES: [[,] …]] 

: [] 

: INCLUDING | EXCLUDING 

: = | > | >= | < |

8.2.7 Defining the Data an XMLA Service Exposes 

An XMLA service exposes data stored in database tables for analysis and display by client applications. However, 

first of all, you need to ensure that the tables and views to expose as an XMLA service actually exist and are 

accessible. 

To define the data to expose using an XMLA service, you must perform at least the following tasks: 

1. Create a simple database schema. 

2. Create a simple database table to expose with an XMLA service. 

3. If required, create a simple database view to expose with an XMLA service. 

4. Grant select privileges to the tables and views to be exposed with the XMLA service. 

8.2.8 Creating an XMLA Service Definition 

The XMLA service definition is a file you use to specify which data is exposed as XMLA/MDX collections for 

analysis and display by client applications. 

An XMLA service for SAP HANA XS is defined in a text file with the file suffix .xsxmla, for example, 

XMLASrvDef.xsxmla. The file resides in the package hierarchy of the XMLA application and must contain the 

entry service {*}, which generates an operational XMLA service. 

Prerequisities for the creation of an XMLA service definition: 

● SAP HANA studio and client installed and configured 

● SAP HANA database user available with repository privileges (for example, to add packages) 

● A SAP HANA development system added to (and available in) SAP HANA studio, for example, in either the 

Navigator view or the SAP HANA Repositories view 

● A working development environment including a repository workspace, a package structure for your XMLA 

application, and a shared project to enable you to synchronize changes to the XMLA project files in the local 

file system with the repository 

● Data is available to expose using the XMLA interface 

1. In the shared project you are using for your XMLA application, use the Project Explorer view to locate the 

package where you want to create the new XMLA service definition. 

Note: The file containing the XMLA service definition must be placed in the root package of the XMLA 

application for which the service is intended. 

2. Create the file that will contain your XMLA service definition. 

In the Project Explorer view, right-click the folder where you want to create the new XMLA service-definition 

file and choose New File in the context-sensitive popup menu displayed. 

3. Create the XMLA service definition. 

210 

The XMLA service definition is a configuration file that you use to specify which data is to be exposed as an 

XMLA collection. 

The following code is an example of a valid XMLA service definition, which exposes all authorized data to 

XMLA requests: 

{*} 

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4. Place the valid XMLA service definition in the root package of the XMLA application. 

5. Save, commit, and activate the XMLA service definition in the SAP HANA repository. 



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9 Writing Server-Side JavaScript 

Applications 

SAP HANA Extended Application Services (SAP HANA XS) provide applications and application developers with 

access to the SAP HANA database using a consumption model that is exposed via HTTP. 

In addition to providing application-specific consumption models, SAP HANA XS also host system services that 

are part of the SAP HANA database, for example: search services and a built-in Web server that provides access 

to static content stored in the SAP HANA repository. 

The consumption model provided by SAP HANA XS focuses on server-side applications written in JavaScript. The 

server-side JavaScript applications can make use of a powerful set of specially developed API functions, for 

example, to enable access to the current request session or the database. This section describes how to write a 

server-side JavaScript application that enables you to expose data, for example, using a Web Browser or any 

other HTTP client. 

9.1 Data Access with JavaScript in SAP HANA XS 

In SAP HANA Extended Application Services, the persistence model (for example, tables, views and stored 

procedures) is mapped to the consumption model that is exposed via HTTP to clients - the applications you write 

to extract data from SAP HANA. 

You can map the persistence and consumption models in the following way: 

● Application-specific code 

Write code that runs in SAP HANA application services. Application-specific code (for example, server-side 

JavaScript) is used in SAP HANA application services to provide the consumption model for client 

applications. 

Applications running in SAP HANA XS enable you to accurately control the flow of data between the 

presentational layer, for example, in the Browser, and the data-processing layer in SAP HANA itself, where the 

calculations are performed, for example in SQL or SQLScript. If you develop and deploy a server-side JavaScript 

application running in SAP HANA XS, you can take advantage of the embedded access to SAP HANA that SAP 

HANA XS provides; the embedded access greatly improves end-to-end performance. 

9.2 Writing JavaScript Code 

9.2.1 Server-Side JavaScript in SAP HANA XS 

SAP HANA application services (XS server) supports server-side application programming in JavaScript. The 

server-side application you develop can use a collection of JavaScript APIs to expose authorized data to client 

requests, for example, to be consumed by a client GUI such as a Web browser or any other HTTP client. 

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Writing Server-Side JavaScript Applications

The functions provided by the JavaScript APIs enable server-side JavaScript applications to perform the following 

actions: 

● Interact with the SAP HANA XS runtime environment 

● Directly access SAP HANA database capabilities 

Note: Unlike OData and XMLA, the JavaScript API enables you not only to expose data but to update, 

insert, and delete data, too. 

JavaScript programs are stored in the repository along with all the other development resources. When the 

programs are activated, the code is stored in the repository as a runtime object. 

9.2.2 JavaScript Editor 

You can write server-side JavaScript using the SAP HANA studio JavaScript editor, which provides syntax 

validation, code highlighting and code completion. 

When you edit a JavaScript file within an XS JavaScript project, the editor automatically has a reference to the XS 

JavaScript API. You can access the API’s objects by entering $, following by a period (.), and the objects are 

available, as in the following example. 

JSLint Validations 

The JavaScript editor includes the JSLint open-source library, which helps to validate JavaScript code. The editor 

highlights any code that does not conform to the JSLint standards. 

To configure the JSLint library and determine which validations are performed, go to: 

Windows Preferences JSLint 

In the preferences window, each JSLint setting is followed by the corresponding JSLint command name, which 

you can use to lookup more information on the JSLint Web site. 

Related Links 

JSLint Web Site 


Writing Server-Side JavaScript Applications 

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9.2.3 Writing Server-Side JavaScript Applications 

SAP HANA Extended Application Services (SAP HANA XS) supports server-side application programming in 

JavaScript. The server-side application you develop can use a collection of JavaScript APIs to expose authorized 

data to client requests, for example, to be consumed by a client GUI such as a Web browser including SAPUI5 

applications and mobile clients. 

Since JavaScript programs are stored in the SAP HANA repository, the steps in this task description assume that 

you have already created a workspace and a project (of type XS Project), and that you have shared the project 

with other members of the development team. To write a server-side JavaScript application, you must perform 

the following high-level steps. 

1. Create a root package for your application, for example, helloxsjs. 

2. Create an application descriptor for your application and place it in the root package you created in the 

previous step. 



the file extension .xsapp. 


3. Create an application-access file and place it in the package to which you want to grant access. 

The application-access file does not have a name; it only has the file extension .xsaccess. The contents of 

the .xsaccess file must be formatted according to JavaScript Object Notation (JSON) rules and associated 

with the package the file belongs to. The rules defined in the .xsaccess file apply to the package it resides in 

as well as any subpackages lower in the package hierarchy. 

4. If you used the authorization keyword in the application-access file (.xsaccess) file for your application, 

create an application-privileges file for the application and define the application privileges. 

The application-privileges file does not have a name; it only has the file extension .xsprivileges. The 

contents of the .xsprivileges file must be formatted according to JavaScript Object Notation (JSON) 

rules. Multiple .xsprivileges files are allowed, but only at different levels in the package hierarchy; you 

cannot place two .xsprivileges files in the same application package. The privileges defined in 

a .xsprivileges file are bound to the package to which the file belongs and can only be applied to this 

package and its subpackages. 

Note: The .xsprivileges file lists the authorization levels available for granting to an application 

package; the .xsaccess file defines which authorization level is assigned to which application 

package. 

5. Create the server-side JavaScript files that contain the application logic. 

214 

You can use the available JavaScript APIs (for example, the database or request-processing API) to expose 

authorized data to client requests. 

Server-side JavaScript files have the file suffix .xsjs, for example, hello.xsjs and contain the code that is 

executed when SAP HANA XS handles a URL request. 


$.response.setBody( "Hello, World!"); 

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6. Check the layout workspace. 

Your application package structure should have a structure that looks like the following example: 

. 

\ 

helloxsjs 

\.xsapp 

.xsaccess 

hello.xsjs 


8. View the results. 

The SAP HANA XS Web server enables you to view the results immediately after activation in the repository, 

for example: http://dbhost:80/helloxsjs/hello.xsjs 

9.3 Writing JavaScript Libraries 

9.3.1 Server-Side JavaScript Libraries 

The elements defined in normal server-side JavaScript programs cannot be accessed from other JavaScript 

programs. To enable the reuse of program elements, SAP HANA Extended Application Services support serverside 

JavaScript libraries. 

Server-side JavaScript libraries are a special type of JavaScript program that can be imported and called in other 

JavaScript programs. You can use JavaScript libraries to perform simple, repetitive tasks, for example, to handle 

forms and form date, to manipulate date and time strings, to parse URLs, and so on. 

Note: JavaScript libraries are internally developed extensions for SAP HANA. 

The following example shows how to import a JavaScript mathematics library using the import function: 

// import math lib 

$.import("sap.myapp.lib","math"); 

// use math lib 

var max_res = $.sap.myapp.lib.math.max(3, 7); 

The import function requires the following parameters: 

● Package name 

Full name of the package containing the library object you want to import, for example, sap.myapp.lib 

● Library name 

Name of the library object you want to import, for example, math 

9.3.2 Writing Server-Side JavaScript Libraries 


JavaScript programs. You can use JavaScript libraries to perform simple, repetitive tasks, for example, to handle 

forms and form date, to manipulate date and time strings, to parse URLs, and so on. 



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JavaScript libraries are internally developed extensions for SAP HANA. However, you can write your own libraries, 

too. JavaScript libraries exist in the context of a package, which is referenced when you import the library. To 

write a JavaScript library to use in your server-side JavaScript application, perform the following steps: 

1. Create the file that contains the JavaScript library you want to add to the package and make available for 

import. 

In SAP HANA XS, server-side JavaScript libraries have the file extension .xsjslib, for example 

greetLib.xsjslib. 

The following example creates a simple library that displays the word “Hello” along with a supplied name and 

adds an exclamation point (!) as a suffix. 

var greetingPrefix = "Hello, "; 

var greetingSuffix = "!"; 

function greet (name) { 

return greetingPrefix + name + greetingSuffix; 

} 

2. Save the new JavaScript library. 

It is important to remember where the JavaScript library is located; you have to reference the package path 

when you import the library. 

3. Activate your new library in the repository so that it is available for import by other JavaScript applications. 

9.3.3 Importing Server-Side JavaScript Libraries 


JavaScript programs. You can use JavaScript libraries to perform simple, repetitive tasks, for example: handle 

forms and form date, manipulate date and time strings, parse URLs, and so on. 

JavaScript libraries are internally developed extensions for SAP HANA. The libraries exist in the context of a 

package, which is referenced when you import the library. The following example of a JavaScript library displays 

the word "Hello" along with a name and an exclamation mark as a suffix. 

var greetingPrefix = "Hello, "; 

var greetingSuffix = "!"; 

function greet (name) { 

return greetingPrefix + name + greetingSuffix; 

} 

Note: This procedure uses the illustrated example JavaScript library to explain what happens when you 

import a JavaScript library, for example, which objects are created, when, and where. If you have your own 

library to import, substitute the library names and paths shown in the steps below as required. 

To import a JavaScript library for use in your server-side JavaScript application, perform the following tasks 

1. Import the JavaScript library into a JavaScript application. 

216 

Open the server-side JavaScript file into which you want to import the JavaScript library. 

Use the $.import function, as follows: 

$.import("","greetLib"); 

var greeting = $.path.to.your.library.filename.greet("World"); 

$.response.setBody(greeting); 

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2. Save and activate the changes to the JavaScript file. 

Although the operation is simple, bear in mind the following points: 

○ Additional objects in the package hierarchy 

The import operation generates a hierarchy of objects below $ that resemble the library's location in the 

repository, for example, for the library path/to/your/library/greetLib.xsjslib, you would see 

the following additional object: 

$.path.to.your.library.greetLib 

○ Additional properties for the newly generated library object: 

$.path.to.your.library.greetLib.greet() 

$.path.to.your.library.greetLib.greetingSuffix 

$.path.to.your.library.greetLib.greetingPrefix 

○ Pre-import checks: 

○ It is not possible to import the referenced library if the import operation would override any 

predefined runtime objects. 

○ Do not import the referenced library if it is already present in the package. 

○ Library context 

Imported libraries exist in the context defined by their repository location. 

9.4 Server-Side JavaScript APIs 

SAP HANA Extended Application Services (SAP HANA XS) provides a set of server-side JavaScript application 

programming interfaces (API) that enable you to configure your applications to interact with SAP HANA. 

The SAP HANA XS API Reference lists all the functions that are available for use when programing interaction 

between your application and SAP HANA. For example, you can use the database API to invoke SQL statements 

from inside your application, or access details of the current HTTP request for SAP HANA data with the requestprocessing 

API.SAP HANA XS includes the following set of server-side JavaScript APIs: 

● Request-Processing API 

Enables access to the context of the current HTTP request, for example, for read requests and write 

responses. You can use the functions provided by this API to manipulate the content of the request and the 

response. 

● Database API 

Enables access to the SAP HANA by means of SQL statements. For example, you can open a connection to 

commit or rollback changes in SAP HANA, to prepare stored procedures (or SQL statements) for execution or 

to return details of a result set or a result set's metadata. 



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Request-Processing API Example 

The following example shows how to use the request-processing API to display the message “Hello World” in a 

browser. 


$.response.setBody( "Hello, World !"); 

Database API Example 

The following example shows how to use the database API to prepare and execute an SQL statement. The 

response to the SQL query is then prepared and displayed in a Web browser. 


var pstmt = conn.prepareStatement( "select * from DUMMY" ); 

var rs = pstmt.executeQuery(); 


if (!rs.next()) { 

$.response.setBody( "Failed to retreive data" ); 


} else { 

$.response.setBody("Response: " + rs.getString(1)); 

} 

rs.close(); 

pstmt.close(); 

conn.close(); 

Related Links 

SAP HANA XS JavaScript Reference 

9.5 The SQL Connection Configuration File 

In SAP HANA Extended Application Services (SAP HANA XS), you use the SQL-connection configuration file to 

enable the execution of SQL statements from inside your server-side JavaScript application with credentials that 

are different to the credentials of the requesting user. 

In cases where it is necessary to execute SQL statements from inside your JavaScript application with credentials 

that are different to the credentials of the requesting user, SAP HANA XS enables you to define the configuration 

for individual SQL connections. Each connection configuration has a unique name, for example, Registration or 

AdminConn, which is generated from the name of the corresponding connection-configuration file 

(Registration.xssqlcc or AdminConn.xssqlcc) on activation in the repository. The administrator can 

assign specific, individual database users to this configuration, and you can use the configuration name to 

reference the unique SQL connection configuration from inside your JavaScript application code. 

If you want to create an SQL connection configuration, you must create the configuration as a flat file and save the 

file with the suffix .xssqlcc, for example, MYSQLconnection.xssqlcc. The new configuration file must be 

located in the same package as the application that references it. You can activate repository files at any point in 

time. 

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Note: A SQL connection configuration can only be accessed from a SAP HANA XS JavaScript application 

(.xsjs) file that is in the same package as the SQL connection configuration itself. Neither subpackages 

nor sibling packages are allowed to access an SQL connection configuration. 

The following example shows the composition and structure of a configuration file AdminConn.xssqlcc for an 

SAP HANA XS SQL connection called AdminConn. On activation of the SQL connection configuration file 

AdminConn.xssqlcc (for example, in the package sap.hana.sqlcon), an SQL connection configuration with 

the name sap.hana.sqlcon::AdminConn is created, which can be referenced in your JavaScript application. 

sap.hana.sqlcon:AdminConn.xssqlcc 

{ 

} 

"description" : "Admin SQL connection" 

To create a preconfigured SQL connection using the configuration object AdminConn, for example, from inside 

your JavaScript application code, you reference the object using the object name and full package path, as 

illustrated in the following code example. 

Calling the SAP HANA XS SQL-Connection Configuration File 

function test() { 

var body; 

var conn; 


try { 

conn = $.db.getConnection("sap.hana.sqlcon::AdminConn"); 

var pStmt = conn.prepareStatement("select CURRENT_USER from 

dummy"); 

var rs = pStmt.executeQuery(); 

if (rs.next()) { 

body = rs.getNString(1); 

} 

rs.close(); 

pStmt.close(); 

} catch (e) { 

body = "Error: exception caught"; 

$.response.status = $.net.http.BAD_REQUEST; 

} 

if (conn) { 

conn.close(); 

} 

$.response.setBody( body ); 

} 

test(); 

To use the SQL connection from your application during runtime, you must bind the SQL connection configuration 

to a database user. To maintain this user mapping, SAP HANA XS provides a dedicated application (the SQL 

Connection Configuration Application), which is pre-installed and accessible under the URL http:// 

:/sap/hana/xs/sqlcc/. You can grant one of the following roles for users who want to use the 

SQL Connection Configuration Application to view or maintain the available SQL connection configurations: 

● sap.hana.xs.sqlcc::Viewer 



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Required to display the available SQL Connections and the current user mapping 

● sap.hana.xs.sqlcc::Administrator 

Required to change the user mapping 

9.6 Tracing JavaScript 

9.6.1 Server-Side JavaScript Tracing 

The SAP HANA XS server-side JavaScript API provides tracing functions that enable your application to write 

predefined messages in the form of application-specific trace output in the xsengine trace files (xsengine*.trc) 

according to the trace level you specify, for example, “info”(information) or “error”. 

If you use the server-side JavaScript API to enable your application to write trace output, you can choose from the 

following trace levels: 

● debug 

● info 

● warning 

● error 

● fatal 

For example, to enable debug-level tracing for your JavaScript application: 

$.trace.debug("request path: " + $.request.path); 

Note: You can view the xsengine*.trace files in the Diagnosis Files tab page in the Administration 

perspective of the SAP HANA studio. 

9.6.2 Tracing Server-Side JavaScript Applications 

The server-side JavaScript API for SAP HANA XS enables you to activate the writing of trace messages into an 

application-specific trace file; the following trace levels are available: debug, error, fatal, info, and warning. 

By default, applications write messages of severity level error to the xsengine*.trc trace files; you can increase 

the trace level manually, for example, to fatal. In SAP HANA XS, the following steps are required to enable trace 

output for your server-side JavaScript application: 


2. In the Navigator view, double-click the SAP HANA instance to open the Administration view for the repository 

where your server-side JavaScript source files are located. 

3. Choose the Trace Configuration view. 

4. In the Global Database Trace screen area, choose Edit Configuration. 

The Edit Configuration icon is only visible if you have the required privileges on the selected SAP HANA 

system. 

5. Select the Show All Components checkbox. 

6. Enter the partial or full name of your application into the search box. 

7. Expand the GLOBAL node, if necessary, to view registered traces for the application name returned by the 

search operation. 

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8. Find the trace matching your application name and select the trace level you want to use to generate output. 

The application name is the location (package) of the .xsapp file associated with the application you are 

tracing. The trace topic is named xsa: . 

9. Choose Finish to activate the trace level changes. 

9.6.3 Viewing Server-Side JavaScript Application Trace Files 

The server-side JavaScript API for SAP HANA XS enables you to instruct your JavaScript applications to write 

application-specific trace messages in the xsengine*.trc trace files, which you can view in the Diagnosis Files 

tab page of the Administration perspective in the SAP HANA studio. The following trace levels are available: 

debug, error, fatal, info, and warning. 

To view trace output for your server-side JavaScript application, perform the following steps: 


2. In the Navigator view, double-click the SAP HANA instance to open the Administration view for the repository 

where your server-side JavaScript source files are located. 

3. Choose the Diagnosis Files tab page. 

4. In the Filter box, enter a string to filter the list of search files displayed, for example, xsengine*.trc. 

The timestamp displayed in the Modified column does not always reflect the precise time at which the trace 

file was written or most recently modified. 

5. Locate the trace file for your SAP HANA XS application and doubleclick the entry to display the contents of 

the selected trace-file in a separate tab page. 

9.7 Debugging JavaScript 

SAP HANA studio enables you to debug XS JavaScript files, including setting breakpoints and inspecting 

variables. 

Caution: A port must be opened to enable debugging. For security reasons, the debug port is turned off by 

default. 

1. In a browser, run the XS JavaScript source file that you want to debug. 

2. Create a debug configuration for debug sessions for a specific SAP HANA installation. 

a) Open the Debug perspective. 

b) Choose and select Debug Configurations. 

c) Create a new XS JavaScript configuration by double-click XS JavaScript. 

d) Enter a name for the configuration. 

e) Enter the host and debug port for your SAP HANA system. 

f) Select Apply. 



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g) Select Close. 

3. Set breakpoints in the JavaScript code by double-clicking on the left vertical ruler. 

4. Run your debug configuration for your server by choosing and selecting your debug configuration. 

5. In the Select Session window, select the SAP HANA XS session ID you are debugging, and then click Select. 

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The session ID is the value of the xsSessionId cookie in your browser session. 

6. Refresh the browser. The XS JavaScript is now running in debug mode. Your client is now attached to the 

session, and execution is suspended at the first breakpoint. 

You can now perform standard Eclipse debug tasks, such as resuming execution, stepping through execution, and 

adding breakpoints. The following debug views are available: 

● Debug 

● Breakpoints 

● Variables 

● Expressions, which you can use to inspect global variables, such as $.request and other SAP HANA XS 

JavaScript API objects 

Related Links 

Debug Perspective [page 30] 

The Debug perspective in the SAP HANA studio is the standard Eclipse Debug perspective, enabling you to 

start debug sessions, create breakpoints and watch variables. 

Opening a Port for JavaScript Debugging [page 223] 

9.7.1 Opening a Port for JavaScript Debugging 

To enable debugging of JavaScript code, you must open a debug port on SAP HANA. 

The debug port is unsecured, as anyone can attach a debug client without needing credentials. A connected client 

can attach to and debug any HTTP session, and can possibly run their own code. 



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Therefore, it is recommended that you enable this feature only in non-production or development environments 

that are accessible by a limited number of developers and that do not contain sensitive and confidential data. In 

production systems that contain sensitive or confidential data, it is recommended that you keep debugging 

disabled or enable it only temporarily. 

To increase security, customers should consider applying additional network-level security measures, for 

example, limiting network access to the debug port. 

1. In SAP HANA studio, open the Navigator view. 

2. Right-click on your system, and selct Administration. 

3. In the Configuration tab, add a section called xsengine.ini debugger (if it does not exist) and add the 

following parameters: 

224 

○ enabled = true 

○ listenport = 

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10 Building UIs With SAPUI5 

This section provides introductory information about UI development toolkit for HTML5. 

UI development toolkit for HTML5 (SAPUI5) is a user interface technology that is used to build and adapt client 

applications based on SAP HANA. You can install SAPUI5 in the SAP HANA studio to build user interfaces 

delivered by SAP HANA's Web server. 

SAPUI5 runtime is a client-side HTML5 rendering library with a rich set of standard and extension controls and a 

lightweight programming model. To support you in developing applications, SAPUI5 application development 

tools comes with a set of eclipse-based wizards and editors. SAPUI5 application development tools provides 

wizards to create application projects and views according to the model-view-controller concept and other 

features like JavaScript code completion, templates and snippets, and in-place application preview. 

SAPUI5 provides many features to enable you to easily create and extend state-of-the-art user interfaces. SAPUI5 

supports the following features: 

● RIA-like client-side features based on JavaScript. 

● CSS3, which allows you to adapt themes to your company's branding in an effective manner 

● Extensibility concept regarding custom controls, meaning that you can extend existing SAPUI5 controls as 

well as develop your own controls 

● Open source jQuery library used as foundation 

● Full support of the SAP product standard 

● Compliance to Open Ajax; can be used together with standard JavaScript libraries 

● Produced in a release independent code line to enable short shipment cycles 

SAPUI5 SDK 

The SAPUI5 SDK (Demo Kit) provides the following sections: 

● Developer Guide with additional information about SAPUI5, the used programming languages, open source 

technologies, development tools, and APIs 

● Controls containing running demo examples with descriptions and source codes 

● API reference with JavaScript documentation of Framework and Control API 

● Test Suite, which shows all controls running with different property settings where you can interactively adapt 

the controls you use for test purposes 

The Demo Kit is installed as a delivery unit. To directly access the Demo Kit, use the following link and replace the 

placeholders accordingly: ://:/sap/ui5/1/sdk/index.html. 

The following references to the sections of the Developer Guide in the Demo Kit base on this URL. 


Building UIs With SAPUI5 

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10.1 Installing SAPUI5 Application Development Tools 

This section provides a short description how to install SAPUI5 tools for SAP HANA. 

Before you start the installation of SAPUI5 application development tools, make sure that you comply with the 

following requirements: 

● SAP HANA studio is installed. 

● SAPUI5 application development tools are downloaded from the SAP Software Download Center on SAP 

Service Marketplace (http://service.sap.com/swdc) and search for SAPUI5 TOOLS IDE PLUGIN 1.00. 

For more information about the installation of SAPUI5 application development tools, see the SAPUI 5 Installation 

Guide for SAP HANA on SAP Service Marketplace or SAP Note 1747308. 

10.2 Creating an SAPUI5 Application 

This section provides an example how to create an SAPUI5 application. 

Prerequisites: You have installed the SAPUI5 application development tools in your SAP HANA studio. 

Using the tools SAPUI5 provides, you create application projects and views according to the model-view- 

controller concept with a clear separation between the user interface and the controller logic. 

The following steps describe the generic procedure to create an SAPUI5 application for SAP HANA XS: 

1. Create an SAPUI5 application project using SAPUI5 application development tools in Eclipse. 

2. Develop the client-side JavaScript script code. 

3. If the package that contains your SAPUI5 application project has not been exposed via HTTP already, you 

need to create .xsapp and .xsaccess files, see Creating the Application Descriptors. This is not necessary, if 

the project was created as a sub-package of an SAP HANA XS application. To make this project a valid SAP 

HANA application, add the .xsapp and .xsaccess files. 

4. Optional step (not part of the example below): Develop a server-side logic for the project by means of server- 

side JavaScript or OData service. 

5. Activate the project on SAP HANA's Web server. 

6. Execute the application on SAP HANA'S Web server. 

For SAPUI5 applications, the following view types are supported: 

● JavaScript: JSview (file extension: js) 

● XML: XMLview (file extension: xml) 

● JSON: JSONview (file extension: json) 

The following procedure gives an example for the creation of an SAPUI5 application: 

1. To open the wizard for creating an SAPUI5 application, choose File New Other SAPUI5 Application 

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Development Application Project . 

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Building UIs With SAPUI5

2. Specify the name, for example MyApplication, and location for your project. Select Desktop and Create an 

Initial View. 

You can also add a view later on by creating a separate SAPUI5 application view. If a new view has been 

created for an existing SAPUI5 application project, the view needs to be manually called either from the 

index.html page, or from another view via view nesting. For more information, see the Demo Kit - 

Developer Guide under Model View Controller Concept. 

3. Enter a name for the initial view in the Name field, for example, helloworld. Do not add a file extension. 

This is done automatically based on the respective view type. 

4. Choose JavaScript and finish the wizard. 

The following application parts are created: 

○ View file; in this example, a JSview file 

○ Controller file 

○ index.html file containing the references for the sap.ui.core and sap.ui.commons libraries, the 

theme (sap_goldreflection), and information about the script type and the script ID. In a second script 

block, the index file refers to the project name, view type, and name. A content default for placing the 

controls on the UI later on and the ARIA application role. 

5. Change the bootstrap tag (located in the index.html file) to enable the application to access the SAPUI5 

libraries on the xsengine as follows: src="resources/sap-ui-core.js" to src="/sap/ui5/1/ 

resources/sap-ui-core.js". 

6. Create a new folder i18n in the WebContent folder. Add a new file messagebundle.hdbtextbundle 

to the i18n folder with the following content: 

# TRANSLATE 

# XBUT,30 

MY_BUTTON_TEXT=Hello {0} button 

Note: A specific suffix .hdbtextbundle is needed for the resource bundles on SAP HANA (so 

called .properties file on other platforms). 

7. To add a control to your view (in this example to the helloworld.view.js), insert the following coding: 

createContent : function(oController) { 

// require the jQuery.sap.resources module 

jQuery.sap.require("jquery.sap.resources"); 

value 

} 



// load the resource bundle 

var oBundle = jQuery.sap.resources({ 

// specify url of the .hdbtextbundle 

url : "i18n/messagebundle.hdbtextbundle" 

}); 

var aControls = []; 

var oButton = new sap.ui.commons.Button({ 

id : this.createId("MyButton"), 

// access the text using the welcome key and pass the 

// for the placeholder ( {0} ) via an array 

text : oBundle.getText("MY_BUTTON_TEXT", [ "World" ]) 

}); 

aControls.push(oButton.attachPress(oController.doIt)); 

return aControls; 

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The coding is put into the createContent method, which creates the content of the view. The View 

wizard creates the body of the method. 

Note: In your SAPUI5 coding, refer to the resource bundle with the URL containing the file extension, 

for example: 

var oBundle = jQuery.sap.resources({ 

url : "i18n/messagebundle.hdbtextbundle", 

locale: sLocale}) 

var oResourceModel = new sap.ui.model.resource.ResourceModel({ 

bundleURL : "i18n/messagebundle.hdbtextbundle "}) 

8. To implement the doIt method for the button's press event, insert the following coding into the controller (in 

this example: helloworld.controller.js): 

doIt : function(oEvent) { alert(oEvent.getSource().getId() + 

"does it!"); } 

9. Create a .xsapp and a .xsaccess file. 

10. Share, commit, and activate your project to transfer the SAPUI5 application to the SAP HANA repository. 

11. To start the UI application on SAP HANA's Web server, use the following URL: ://:/MyApplication/WebContent/ 

index.html. Replace the placeholders accordingly; MyApplication refers to the name of your project 

according to Step 2. 

10.2.1 Local Testing of a SAPUI5 Application 

This section provides a description how local testing can be performed as an optional step. 

If you want to test the SAPUI5 application before you activate your project, you can test it within Eclipse on your 

local PC. This local testing is optional. If you perform a local test, note the following: 

● The src attribute in the bootstrap tag of the index.html file needs to have a different URL than the src 

attribute for execution on SAP HANA's Web server. This can be achieved by manually changing the URL 

before submitting to SAP HANA's Web server, or by using a code snippet, that detects if the application runs 

locally or not, and sets the URL accordingly. 

● If you call a data service in form of a server-side JavaScript or an OData service that resides in the SAP HANA 

box, it is necessary to use a URL that points to SAP HANA's Web server. It is usually also necessary to use the 

so-called proxy servlet to avoid cross-domain issues. In case of the bootstrap URL, for example, the URL for 

local execution differs from the URL for execution on SAP HANA's Web server. For more information, see the 

procedure below and the referenced section in the Demo Kit. 

For more information, see the Demo Kit - Developer Guide under Testing a SAPUI5 Application. 

To perform a local test, proceed as follows: 

1. Change the URL set as "src" in the bootstrap tag of the index.html file (see explanation above). To avoid 

228 

a manual change before submitting the application, use the following code snippet that detects the context 

automatically, in which the application runs, and sets the URL accordingly. 

 

 

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// use alternative bootstrap for testing locally in 

// Eclipse during development time 

// this is only a helper mechanism during development time 

if (!window.sap) { 

var oriTag = document.getElementById("sap-ui-bootstrap"); 

oriTag.id = "wrong"; 

oriTag.src = "wrong.js"; 

var script = " " + 

""; 

document.write(script); 

} 

 

2. If you use requests to backend services, you need to use a suitable URL that points to the backend server and, 

to avoid cross-domain issues, you need to use the so-called proxy servlet. Similar to the bootstrap tag, you 

can change the respective code manually before submitting, or you can use a code snippet that determines 

the URL automatically depending on the context, in which the application runs. 

Note: As the server-side logic of an SAPUI5 application cannot be executed locally on the developer's 

PC, it can only run on the server. Hence, this needs to be committed and activated before it can be 

tested. 

For more information, see the Demo Kit - Developer Guide under Testing a SAPUI5 Application Enabling 

Backend Access for Local Testing . 

3. To test your application, choose one of the following options: 

○ Open the context menu for the index.html file located in your project's WebContent folder and 

choose Run As Web App Preview . 

○ To run your application on a server, for example Tomcat, open the context menu of your project, choose 

Run As Run on Server and select the respective server. 

10.2.2 SAPUI5 Runtime Version Comparison 

This section describes how to compare the SAPUI5 runtime versions installed locally and on SAP HANA' Web 

server. 

It is possible that the SAPUI5 runtime version installed locally in your Eclipse differs from the SAPUI5 runtime 

version on SAP HANA's Web server. 

To verify, which version is installed locally, you can check the SAP HANA studio Eclipse version via Help About 

SAP HANA Studio Installation Details Features under "SAPUI5 Feature" 

(com.sap.ui5.uilib.feature). 

To find out the SAPUI5 runtime version on SAP HANA's Web server, open the SAP HANA modeler perspective in 

the SAP HANA studio Eclipse via Window Open Perspective Modeler . Choose Setup Delivery Units ... 

. The version, support package, and patch version of the SAPUI5 runtime libs are displayed there. You can also 

open the SAPUI5 runtime index page under ://:/sap/ui5/1/ 



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index.html and press CTRL-ALT-SHIFT-P. The SAPUI5 runtime version is displayed in the field. 

If the local version is, for example, newer than the version on SAP HANA's Web server and you use code 

completion or test the application locally in Eclipse, the results may differ or you may use features that are not 

available on the server. We recommend the following: 

● To detect new features, check the @since tags provided in the JSDoc. 

● Before deployment, test the application locally in Eclipse with the runtime resources from the server by 

configuring the resource servlet to fetch the runtime resources from the server. For more information, see the 

Demo Kit - Developer Guide under Testing an SAPUI5 Application UI5 Library Location Used for Testing . 

● After deployment, always test the application on the server. 

10.3 Supporting Translation 

This section provides a description of what needs to be done to support the translation of resource bundles. 

To enable the translation of the user interface, define a specific suffix for the resource bundles and use a specific 

first line in the resource bundle file. This is described in step 6 in the Creating an SAPUI5 Application topic. 

For more information, see the Demo Kit - Developer Guide under Localization. 

Related Links 

Creating an SAPUI5 Application [page 226] 

This section provides an example how to create an SAPUI5 application. 

230 

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11 Enabling Search 

With a SAP HANA database, your users will want to search tables and views much like they would when searching 

for information on the Internet. In SAP HANA, you can either directly query data using SQL queries or you can 

build search apps using a UI toolkit. 

Before enabling search, you must meet the following prerequisites: 

● Your SAP HANA database contains column-oriented tables. 

● A valid data type is assigned to each column. The data types of the columns determine how you can query 

your data. 

In SAP HANA, you can search on single or multiple columns of almost any visible data type. In addition to standard 

string search, SAP HANA also supports full text search. 

During a full text search, the SAP HANA search engine examines structured text, such as author and date 

attributes, as well as unstructured text, such as body text. Unlike a string search, for a text search, the sequence 

of words and characters is not critical for finding matches. A full text index enables this functionality by analyzing 

and preprocessing the available text semantically. This includes normalization, tokenization, word stemming, and 

parts of speech tagging. 

To enable search, proceed as follows: 

1. Create any required full text indexes for the columns in the table. 

○ For columns defined with the data type TEXT or SHORTTEXT(n), full text indexes are automatically 

generated. For columns of any other data type, you must manually create any required full text indexes. 

○ When you create a full text index, you can also define synchronization and trigger text analysis. 

2. Build SQL search queries. 

○ Search queries use the SQL SELECT statement. 

○ For searches on large object types or text, the queries must include the CONTAINS predicate. 

3. Optionally, build search apps using the UI toolkit for SAP HANA Info Access . 

○ The UI toolkit provides UI building blocks for developing browser-based search apps for end users. 

○ The UI toolkit is based on HTML5 and JavaScript libraries. 

○ The UI toolkit connects to the database using the SAP HANA Info Access service that wraps search and 

analytic SQL queries and exposes them through an HTTP interface. 

11.1 Creating Full Text Indexes 

When you create a TEXT or SHORTTEXT column in a table, SAP HANA automatically creates a corresponding full 

text index. However, for columns of other data types, you must manually create and define any necessary full text 

indexes. 


Enabling Search 

P U B L I C 


A full text index is an additional data structure that is created to enable text search features on a specific column 

in a table. Conceptually, full text indexes support searching on columns in the same way that indexes support 

searching through books. 

To create a full text index, proceed as follows: 

1. Determine the columns for which you require an index. 

2. Use the CREATE FULLTEXT INDEX statement to create an index with the specified index name. 

CREATE FULLTEXT INDEX ON '(' ')' 

[] 

3. Specify any of the following additional parameters for the full text index: 

LANGUAGE COLUMN 

LANGUAGE DETECTION '(' ')' 

MIME TYPE COLUMN 

FUZZY SEARCH INDEX 

PHRASE INDEX RATIO 

CONFIGURATION 

SEARCH ONLY 

FAST PREPROCESS 


TEXT_ANALYSIS 

SYNC 

|ASYNC 

|ASYNC FLUSH [QUEUE] EVERY n MINUTES 

|ASYNC FLUSH [QUEUE] AFTER n DOCUMENTS 

|ASYNC FLUSH [QUEUE] EVERY n MINUTES OR AFTER m DOCUMENTS 

If you do not specify any parameters, the default values are used. 

The system creates a separate hidden full text index column for each source column that you have specified. 

You can now create queries to search those columns. 

You can check the parameters of an existing full text index by using the SYS.FULLTEXT_INDEXES monitoring 

view. 

Related Links 

You want to create a full text index i1 for table A, column C, with the following characteristics: 

● Synchronous processing 

● Fuzzy search index disabled 

● Languages for language detection: English, German, and South Korean 

To create the index, you use the following syntax: 

CREATE FULLTEXT INDEX i1 ON A(C) FUZZY SEARCH INDEX OFF 

SYNC 

LANGUAGE DETECTION 

('EN','DE','KR') 

Full Text Index Types [page 233] 

SAP HANA automatically creates full text indexes for columns of type TEXT and SHORTTEXT(n). For other 

column types, you must manually create any required full text indexes. 

232 

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Enabling Search

Synchronization [page 236] 

Full text indexes in a SAP HANA database must be created and updated in synchronization with the 

corresponding columns. This synchronization can be either synchronous or asynchronous. 

Full Text Index Parameters [page 243] 

The content and behavior of a full text index is configured by the use of both default and user-specified 

parameters. To view the configuration of a full text index, you use the SYS.FULLTEXT_INDEXES view. 

11.1.1 Full Text Index Types 

SAP HANA automatically creates full text indexes for columns of type TEXT and SHORTTEXT(n). For other 

column types, you must manually create any required full text indexes. 

Characteristic TEXT SHORTTEXT (n) Manually Created 

SQL data type exposed to 

user 

Data returned by SELECT Original data (returns 

normalized data if the 

SEARCH_ONLY parameter 

is ON) 

NCLOB NVARCHAR(n) Original data type 

Original data Original data 

SQL insertion mode SYNC SYNC SYNC or ASYNC 

Drop index Yes (via drop column) Yes (via drop column) Yes 

Text search via CONTAINS Yes Yes Yes 

SQL string search Not possible Possible Depends on underlying 

data type 

Change parameters of full 

text index 

Partially Partially All (with rebuild) 

Rebuild index No No Yes 

Base type can be changed No No No (no dependency 

between base-column and 

index available) 

TEXT Indexes 

In a SAP HANA database, when you create a table that contains large text documents, you can define the columns 

with the TEXT data type. This data type allows you to query large text documents and present content excerpts in 

search hit lists. You can also reconstruct the document and display it in its original formatting. 

When you create a TEXT column and insert content, SAP HANA extracts and processes the text from the original 

document and then automatically generates a full text index for the column. To create this full text index, SAP 

HANA replaces the original data in the column with the processed text. This text is then returned with the data 

type NCLOB. The original data is no longer available. 

If you insert new entries in the TEXT column, the full text index is automatically and synchronously updated. 

CREATE COLUMN TABLE 

( 

k int primary key, 

content TEXT 



FAST PREPROCESS OFF 

PHRASE INDEX RATIO 

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0.77 

) 

Limitations 

The TEXT data type has the following search-relevant limitations: 

● SQL string searches are not supported. 

● The SQL functions CONCAT and JOIN are not supported. 

● TEXT columns cannot be converted to other data types. 

● Text analysis is not supported. 

For TEXT columns, SAP HANA does not support the following SQL expressions: 

● HAVING 

● WHERE with strings or non-alphanumeric characters 

● ORDER BY 

● GROUP BY 

● Aggregate expressions (COUNT, MIN, MAX, etc.) 

● JOIN ON 

Changes to TEXT Indexes 

TEXT full text indexes are automatically generated and you do not specify names for them; therefore, you cannot 

directly manipulate them. However, when you create, alter, or drop a table column, the same change is 

automatically applied to the full text index for that column. 

By using the ALTER TABLE statement to affect changes on the index, you can alter the following parameters: 

● PHRASE INDEX RATIO 

● FUZZY SEARCH INDEX 

SHORTTEXT(n) Indexes 

If the tables in your SAP HANA database contain columns with text strings that are relatively short in length, you 

can define those columns with the SHORTTEXT(n) data type. The SHORTTEXT(n) data type enables both SQL 

string search and full text search capabilities. 

SAP HANA preprocesses the text in the column and stores that preprocessed text as a full text index in a hidden 

column attached to the original column. When queried, the text in the full text index returns with the NVARCHAR 

data type. The original text is still available; however, search queries are performed, by default, on the text in the 

index. 

When you create a column table and define a column with the data type SHORTTEXT(n), as in the following 

example, a full text index is automatically generated. Whenever new entries are then inserted in the column, the 

full text index is automatically and synchronously updated. 

234 

CREATE COLUMN TABLE 

( 

k int primary key, 

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Enabling Search

) 

content SHORTTEXT(100) 

Changes to SHORTTEXT(n) Indexes 

FAST PREPROCESS OFF 

SEARCH ONLY ON 

SHORTTEXT(n) full text indexes are automatically generated and you do not specify names for them; therefore, 

you cannot directly manipulate them. However, when you create, alter, or drop a table column, the same change 

is automatically applied to the index for that column. 

When using the ALTER TABLE statement to affect changes on the index, you can only alter the following 

parameters: 

● PHRASE INDEX RATIO 

● FUZZY SEARCH INDEX 

Note: You cannot change the length of the original text and you cannot convert SHORTTEXT(n) to another 

data type. 

Manually Created Indexes 

If the tables in your SAP HANA database contain extensive columns that are frequently queried but do not have 

automatically generated full text indexes, meaning they are not TEXT or SHORTTEXT(n) type columns, you can 

improve search performance by manually creating full text indexes. 

To manually create a full text index, the column must have one of the following SQL data types: 

● VARCHAR 

● NVARCHAR 

● ALPHANUM 

● CLOB 

● NCLOB 

● BLOB 

When you manually create an index, the system attaches a hidden column to the specified column. This hidden 

column contains textual data that SAP HANA Preprocessor has extracted from the text in the source column. The 

original text in the source column remains unchanged. Search queries are then performed on the hidden column; 

however, they always return the original text. Depending on the data type that is assigned to a source column, 

string search may be possible. 

You can manually create an index directly after creating a table or you can create the index later. Once you create 

an index for a column, the system automatically processes any text that is inserted into this column and adds the 

processed text to the index. Processing for manually created indexes can be performed synchronously or 

asynchronously. 

You can specify different parameters when you create a full text index. If parameter changes are required later, 

you can change the values for the existing index directly or re-create the index with the parameters that you want 

to change. 

Related Links 

Creating Full Text Indexes [page 231] 



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When you create a TEXT or SHORTTEXT column in a table, SAP HANA automatically creates a corresponding 

full text index. However, for columns of other data types, you must manually create and define any necessary 

full text indexes. 

Altering Full Text Index Parameters [page 242] 

You can alter a full text index after it is created. Altering an index includes changing the values of the 

parameters and altering the parameters by replacing the index. 







11.1.2 Synchronization 



Synchronous 

In SAP HANA, indexes of the type TEXT and SHORTTEXT(n) are synchronous. Text preprocessing is 

automatically performed when a column is created or new text is inserted and the full text index is then 

automatically updated. The system cannot transport any data to the proper database tables until text 

preprocessing is complete. 

Asynchronous 

If you manually create a full text index, you can specify whether the index is synchronous or asynchronous. By 

default, manually created indexes are asynchronous. Text preprocessing is not initially performed when the table 

or column is created or whenever new text is inserted. In this case, inserting the results of the text preprocessing 

and writing the original data do not occur at the same time. Therefore, the full text information may not be 

immediately available for searching. 

To handle asynchronous processing of text, SAP HANA uses queues. 

Queues 

The queue is a mechanism used to enable a full text index to operate asynchronously. This means that when you 

insert new entries into the column, the text is not made available in the column until it is preprocessed. 

When you insert new entries, the queue sends the text to the preprocessor for analysis. It returns a serialized 

instance of a DAF (document analysis format) object, which is then processed further by the HANA column store. 

The result is stored in the full text index. 

The SAP HANA queue manager automatically creates a queue when you create an asynchronous full text index or 

when the index server is started and the queue manager finds the information that a specific queue is needed. The 

queues are always created on the server on which the table is stored. 

Every entry in the queue has one of the following processing states: 

● New 

236 

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Enabling Search

● Preprocessing 

● Preprocessed 

● Indexing 

● Error 

If the original column entry is modified or deleted during text processing, the queue is notified and, if necessary, 

the entry is preprocessed again. 

Note: The content of the queue is not made persistent at any stage. If the HANA index server process fails, 

the queue data is lost and the queue manager automatically restarts the process for those entries that 

were not already processed. Any incomplete text preprocessing is restarted from the beginning. 

Flush Scheduling 

When you create an asynchronous full text index, you can specify when documents are removed from the queue 

after they are preprocessed and inserted into the full text index; this is called flushing. You can schedule flushing 

based on either time or the number of documents. To do this, when you create the full text index, define one of the 

following clauses with the ASYNC parameter: 

● FLUSH EVERY (n) MINUTES 

● FLUSH AFTER (n) DOCUMENTS 

● FLUSH EVERY (n) MINUTES OR AFTER (m) DOCUMENTS 

Note: You cannot specify negatives values for minutes or documents. 

To determine when the queue of an existing full text index is flushed, see the FLUSH_EVERY_MINUTES and 

FLUSH_AFTER_ROWS attributes in the view FULLTEXT_INDEXES. 

Related Links 

Manipulating Queue Processing [page 237] 

By default, queues are active initially and run automatically based on the parameters you specify when 

creating the full text index. However, if necessary, you can manually manipulate the processing of an existing 

queue. 

Manipulating Queue Processing 

By default, queues are active initially and run automatically based on the parameters you specify when creating 

the full text index. However, if necessary, you can manually manipulate the processing of an existing queue. 

To manipulate the processing of a queue, the following commands are available: 

● FLUSH 

Updates the full text index with the documents in the queue which have already been processed and removes 

them from the queue. 

● SUSPEND 

Suspends the full text index processing queue 

● ACTIVATE 



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Activates the full text index processing queue if it has been suspended 

To manipulate the processing of a queue: 

1. Identify which queue process you want to manipulate by using the monitoring view M_FULLTEXT_QUEUES. 

For information about the specific content of the view, see SAP HANA System Tables and Monitoring Views. 

2. Use the ALTER FULLTEXT INDEX statement to flush, suspend, or reactivate the queue. 

Use the following syntax: 

ALTER FULLTEXT INDEX FLUSH|SUSPEND|ACTIVATE QUEUE 

Related Links 

SAP HANA System Tables and Monitoring Views: M_FULLTEXT_QUEUES 

11.1.3 Text Analysis 

The text analysis provides a vast number of possible entity types and analysis rules for many industries in 20 

languages. However, you do not have to deal with this complexity when analyzing your individual set of 

documents. The language modules included with the software contain system dictionaries and provide an 

extensive set of predefined entity types. The extraction process can extract entities using these lists of specific 

entities. It can also discover new entities using linguistic models. Extraction classifies each extracted entity by 

entity type and presents this metadata in a standardized format. 

The following data types are enabled for text analysis: NVARCHAR, VARCHAR, and STRING. 

The following text analysis options are delivered by SAP: 

Table 10: Options 

Name of Option Description 

LINGANALYSIS_BASIC This option provides the following language processing 

capabilities for linguistic analysis of unstructured data: 

● Segmentation - the separation of input text into its elements 

LINGANALYSIS_STEMS This option provides the following language processing 



● Stemming - the identification of word stems, or dictionary 

forms 

LINGANALYSIS_FULL This option provides the following language processing 



● Stemming - the identification of word stems, or dictionary 

forms 

● Tagging - the labeling of words' parts of speech 

EXTRACTION_CORE This option extracts entities of interest from unstructured text, 

e.g. people, organizations, places, and other parties described in 

the document. 

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Enabling Search

Name of Option Description 

In most use cases, this option is sufficient. 

EXTRACTION_CORE_VOICEOFCUSTOMER Voice of the customer content includes a set of entity types and 

rules that address requirements for extracting customer 

sentiments and requests. You can use this content to retrieve 

specific information about your customers' needs and 

perceptions when processing and analyzing text. The option 

involves complex linguistic analysis and pattern matching that 

includes processing parts of speech, syntactic patterns, negation, 

and so on, to identify the patterns to be extracted. 

Voice of the customer content is supported for these languages: 

● English 

● French 

● German 

● Spanish 

To use the text analyzing function, create a full text index on the column which contains your texts with the 

following parameters: 

TEXT_ANALYSIS ON 

CONFIGURATION '' 

Note: 

Technical names of the options are case-sensitive. 

If your tables contain a language indicator, you should enter the name of the column: 

LANGUAGE_COLUMN 

If no language is specified, EN will be used by default. 

Once the indexing is started, the text analysis runs in the background. Depending on the number and size of the 

texts, one analysis can take hours. To check the status of the text analysis, you can use the default monitoring 

view FULLTEXT_INDEXES. 

For each full text index, the system creates an additional table with the naming $TA_ within the 

same schema which contains the source table. 

This table stores the extracted entities and the analysis results. You can use this table to build joins with other 

search enabled views, for example to use it for interactive navigation or auto-completion in search input fields. 

You can find detailed information on this table under Structure of the $TA Table. 

To keep track of deletions in the source table, the keys in the $TA table need to be aligned to the keys of the 

source table. To do this, use the following SQL statement: 

ALTER TABLE ""."$TA_INDEX_NAME" ADD CONSTRAINT COMMAND 

FOREIGN KEY("key_1", "key_2", "key_n") REFERENCES "".""("key_1","key_2","key_n") ON DELETE CASCADE 



P U B L I C 


Related Links 

For triggering the text analysis using the option EXTRACTION_CORE, specify the following additional 

parameters for the full text index: 

TEXT_ANALYSIS ON 

CONFIGURATION 'EXTRACTION_CORE' 

LANGUAGE_COLUMN LANG 

ALTER TABLE "MY_SCHEMA"."$TA_CUSTOMER_INDEX" ADD CONSTRAINT ALTER_COMMAND 

FOREIGN KEY("KEY_1", "KEY_2") REFERENCES 

"MY_SCHEMA"."CUSTOMERS"("KEY_1","KEY_2") ON DELETE CASCADE 

Text Data Processing Language Reference Guide 

This guide describes in detail the standard extraction content and the linguistic analysis 

Structure of the $TA Table 

The table $TA_ is generated automatically after triggering the index creation. The table is built 

from the key fields of the source table, additional key fields TA_RULE and TA_COUNTER, and 8 additional fields. 

● Key fields of the source table 

● Name of the analyzed column 

● Entity type, for example DATE or NOUN_GROUP 

● Entity value, for example October 29, 2010 or horizontal stabilizer 

● Normalized entity value, if available, for example 2010-10-29 

Table 11: Structure of TA table 

Column ID Key Description Data Type 

 

Yes In order to support a foreign key definition 

linking from the $TA table to its source table, 

the $TA table has to use exactly the same key 

columns of its source table (in data type and 

ID). 

The $TA table includes all keys from the 

source table. 

TA_RULE Yes Stores the rule package that yielded the 

token. This is also required to distinguish 

between LXP output and output from the 

entity extraction. 

TA_COUNTER Yes The token counter counts all tokens across 

240 

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the document. The order is only unique for a 

same as in source table 

NVARCHAR(200) 

BIGINT 


Enabling Search

Column ID Key Description Data Type 

given processing type (hence the previous 

attribute as key). 

TA_TOKEN - Term or entity - depending on processing 

type. 

TA_LANGUAGE - Usually, the document's language is stated in 

the source table. In rare cases where this is 

not true, the language code is stored here. As 

there is no support for multi-language 

documents, the language code is identical for 

all result records of a document. 

TA_TYPE - The token type contains the linguistic or 

semantic type of the token; for instance 

"noun" (if option = LINGANALYSIS_*) or 

"company" (if option = EXTRACTION_*). 

TA_NORMALIZED - Stores a normalized representation of the 

token. This becomes relevant e.g. for German 

with umlauts, or ß/ss. Normalization with 

regards to capitalization would not be as 

important as to justify this column. 

TA_STEM - Stores the linguistic stemming information, 

e.g. the singular nominative for nouns, or the 

indicative for verbs. If text analysis yields 

several stems, only the first stem will be 

stored, assuming this to be the best match. 

TA_PARAGRAPH - Stores the number of all paragraphs in the 


TA_SENTENCE - Stores the number of all sentences in a 


TA_CREATED_AT - Stores the creation time. Used for mere 

administrative information; e.g. for 

reorganizing purposes. 

The $TA table can be modified like any other table, but it cannot be partitioned. 

You can add additional columns to this table, e.g. with a statement like ALTER TABLE 

NVARCHAR(250) 

NVARCHAR(2) 

NVARCHAR(100) 

NVARCHAR(250) 

NVARCHAR(300) 

INTEGER 

INTEGER 

TIMESTAMP 

"TA"."$TA_SOURCE_TEXT_TA" ADD(C INTEGER GENERATED ALWAYS AS 1). In this example, the value 1 will be 

written to only existing rows in the new column C. The new column will not be filled automatically in delta updates. 



P U B L I C 


Note: 

If the source table has a field name identical to one of the default fields from the $TA table, you will receive 

an error message after the CREATE FULTTEXT INDEX statement informing you to rename the field of the 

source table. After you rename the corresponding field, you can execute the CREATE FULLTEXT INDEX 

statement again. 

11.1.4 Dropping Full Text Indexes 

If you want to delete a full text index that you manually created, for example, because it is referenced only rarely 

or preprocessing is too time-consuming, you can drop the full text index. For TEXT or SHORTTEXT full text 

indexes, you cannot drop the full text index; instead, you must delete the related column in the table. 

You also need to drop full text indexes when adding or removing index parameters. As parameters cannot be 

added to or removed from an existing full text index, if you want to change parameters, you must first drop the full 

text index and then create a new index with the new parameters. 

To drop a full text index, you use the DROP FULLTEXT INDEX statement: 

DROP FULLTEXT INDEX 

Related Links 

Note: Before you can drop a full text index, you must remove the relationship between the source table 

and any existing $TA tables (for text analysis). To do so, use the following statement: 

ALTER TABLE SCHEMA DROP 

The name constraint must be the same as originally used when adding the constraint. For more 

information, see Text Analysis. 

Altering Full Text Index Parameters [page 242] 

You can alter a full text index after it is created. Altering an index includes changing the values of the 

parameters and altering the parameters by replacing the index. 

Text Analysis [page 238] 

11.1.5 Altering Full Text Index Parameters 

You can alter a full text index after it is created. Altering an index includes changing the values of the parameters 

and altering the parameters by replacing the index. 

● To alter the parameters of a full text index, use the ALTER FULLTEXT INDEX statement. 

You can only use this statement to alter the following parameters: 

○ Fuzzy search index 

○ Phrase index ratio 

Example syntax: 

ALTER FULLTEXT INDEX 

PHRASE INDEX RATIO 


● To alter any other parameter, you must replace the existing full text index as follows: 

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Enabling Search

a) Delete the existing full text index by using the DROP FULLTEXT INDEX statement. 

b) Create a new index using the new parameter values. 

Related Links 








Queues [page 236] 

The queue is a mechanism used to enable a full text index to operate asynchronously. This means that when 

you insert new entries into the column, the text is not made available in the column until it is preprocessed. 




11.1.6 Full Text Index Parameters 



In SAP HANA, full text indexes are configured using the following parameters: 

Parameter Data 

Type 

SCHEMA_NAM 

E 

NVARCH 

AR(256) 

TABLE_NAME NVARCH 

AR(256) 

TABLE_OID BIGINT 

INDEX_NAME NVARCH 

AR(256) 

INDEX_OID BIGINT 

LANGUAGE_C 

OLUMN 



NVARCH 

AR(256) 

Default 

(TEXT) 

Default 

(SHORTTEXT) 

None None None 

Default (Manually 

Created) 

Description 

Specifies the schema name 

Specifies the table name 

Specifies the object ID of the 

table 

Specifies the name of the full 

text index 

Specifies the object ID of the 

full text index 

Specifies the language used for 

analyzing the document. If no 

language is specified, 

automatic language detection is 

performed. The detected 

language is stored with the 

TEXT_AE attribute. 

With this option, you can refer 

to a column of the same 

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Type 

MIME_TYPE_ 

COLUMN 

LANGUAGE_D 

ETECTION 

FAST_PREPR 

OCESS 

244 

NVARCH 

AR(256) 

NVARCH 

AR(5000 

) 

Default 

(TEXT) 

Default 

(SHORTTEXT) 


EN EN EN 

TINYINT ON ON ON 

P U B L I C 



Created) 

Description 

database table in which the 

language for the document is 

stored. The column is read by 

the queue. 

languageColumn in basetable 

should be of type NVARCHAR/ 

VARCHAR(m) where m>=2 

when not NULL: 

table(tableoid).hasColumn(lang 

uageColumn) 

This column holds a format/ 

mimetype indicator (for plain 

text, the encoding can also be 

specified), e.g. ('text/ 

plain:CP-1252','PDF','MS_WOR 

D 3.0',..). 

'FORMAT' is handled in the 

same way as 'LANGUAGE'. 

when not NULL: 

table(tableoid).hasColumn(mi 

meTypeColumn) 

Specifies the set of languages 

to be considered for automatic 

language detection. If reliable 

language detection cannot be 

performed, the first language in 

the list will be used as the 

default language. 

This option is used to limit the 

languages for text analysis. The 

parameter is currently ignored 

by text analysis. when not 

NULL: for each language L in 

languageDetection: L in (select 

language from 

SYS.M_TEXT_ANALYSIS_LANG 

UAGES) 

Specifies if fast preprocessing 

should be performed. With fast 

preprocessing the detected 

language is always the default 

language. 


Enabling Search


Type 

FUZZY_SEAR 

CH_INDEX 

SEARCH_ONL 

Y 

IS_EXPLICI 

T 

FLUSH_AFTE 

R_DOCUMENT 

S 

FLUSH_EVER 

Y_MINUTES 



Default 

(TEXT) 

Default 

(SHORTTEXT) 

TINYINT OFF OFF OFF 


Created) 

TINYINT OFF ON for LOB-types 

OFF, otherwise ON 

TINYINT 0 0 1 

INTEGER N/A N/A 

INTEGER N/A N/A 

Description 

If this option is activated, 

linguisitic analysis is skipped. 

Only a simple tokenizer is used. 

This does not work for 

languages which do not use 

spaces as word separators. The 

fast analyzer cannot handle 

binary documents. 

If this option is enabled, a 

special index is created for the 

fuzzy search. This index 

accelerates the fuzzy search 

but uses additional memory. 

If set to ON, you cannot 

reconstruct original content or 

show the document in its 

original formatting when using 

the highlight function. With this 

setting, the text attributes do 

not store any DAFs, that 

means, it is not possible to 

retrieve the HTML-converted or 

original data from the text 

attribute. The document will, 

however, use less memory. 

If the text attribute is created 

via a manually created full text 

index, the source attribute that 

contains the original data is not 

affected by this setting. 

Specifies whether the full text 

index was manually created 

(also known as explicit). By 

default, manually created full 

text indexes use ASYNC 

synchronization. 

Specifies when asynchronous 

full text indexes are flushed. 

The specified value cannot be 

negative. 

Specifies when asynchronous 

full text indexes are flushed. 

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Type 

CONFIGURAT 

ION 

INTERNAL_C 

OLUMN_NAME 

PHRASE_IND 

EX_RATIO 

TEXT_ANALY 

SIS 

246 

NVARCH 

AR(5000 

) 

NVARCH 

AR(512) 

Default 

(TEXT) 

Default 

(SHORTTEXT) 


FLOAT 0.0 0.0 (0.2 if 

length


Type 

Default 

(TEXT) 

Default 

(SHORTTEXT) 


Created) 

Description 

parameter is automatically set 

to OFF. 

Text analysis can extract 

entities such as persons, 

products, or places, from 

documents and thus enrich the 

set of structured information in 

SAP HANA. You can use these 

additional attributes, which are 

stored in a new table, when 

creating models (views) for 

analytics and search scenarios 

to enable improved analytics 

and search in SAP HANA. 

For more information, see Text 

Analysis [page 238]. 

Memory Consumption of Full Text Index Parameters 

In SAP HANA, certain full text index parameters can have a significant impact on memory consumption based on 

how they are defined. 

The following full text index parameters can have a significant impact on memory consumption: 

Parameter Memory Impact Details 

PHRASE_INDEX_RATIO If the value is greater than 0.0, then there is additional 

memory overhead. The maximum memory 

consumption is the memory consumption of the full 

text index multiplied by the parameter value. 

FUZZY_SEARCH_INDEX To increase response times for fuzzy search, when 

enabled, this parameter creates additional in-memory 

structures. For text-type columns, fuzzy search 

indexes require approx. 10% of the memory size of the 

column. 

TEXT_ANALYSIS If set to ON, an additional table is created for storing 



structured data extracted from the source text for text 

analysis. The amount of extracted data depends on the 

data in the source column, the text analysis rules, and 

the structure of the results. In certain cases, the 

memory consumption of the extracted data could 

exceed the memory consumption of the source data. 

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11.2 Building SQL Search Queries 

In column-oriented tables, you can perform searches using the SQL SELECT statement. 

Before building SQL search queries, the following prerequisites must be met: 

● The tables you want to search are column-oriented. 

● You have created any required views for the tables you want to search. 

● You have created any required full text indexes for the columns you want to search. 

SAP HANA supports the standard SQL search syntax and functions for search queries on nearly all visible data 

types. You build SQL queries using the SELECT statement, as in the following example: 

SELECT * FROM Contacts WHERE ID=1 

However, in SAP HANA, columns of large object types and text have additional requirements. To enable search on 

columns of these types, you must ensure the following requirements are met: 

● Full text indexes have been created for the search-relevant columns. For columns of type TEXT and 

SHORTTEXT, this is done automatically. 

● Search queries on the columns use the CONTAINS predicate. 

For large object types and text, you build SQL queries using the SELECT statement and CONTAINS predicate, as 

in the following example: 

SELECT * FROM Documents WHERE CONTAINS (*,'Comment') 

To build a search query, proceed as follows: 

1. Use the SQL SELECT statement and specify the table or view and column you want to search. If required, 

include the CONTAINS predicate. 

2. If required, specify scalar functions for the search. 

3. Specify the search terms and, optionally, the search type (EXACT, LINGUISTIC, or FUZZY). 

Note: If you do not specify a search type, by default, the search query is performed as an exact 

search. 

For further examples of the syntax used with the SELECT statement, see SAP HANA SQL Reference 

Manual. 

Related Links 

SAP HANA SQL Reference Manual: SELECT 

11.2.1 Search Queries with CONTAINS 

In SAP HANA, you can search one or multiple columns by creating a query that includes the CONTAINS predicate. 

In SAP HANA, a search query with CONTAINS has a look and feel similar to common Internet search engines. 

248 

P U B L I C 



Enabling Search

The CONTAINS predicate is optional for search queries on columns of most data types; however, for large object 

types and text, this predicate is mandatory. You can build a search query with the CONTAINS predicate as 

follows: 

SELECT * FROM 

WHERE CONTAINS ((, , ), ) 

When you specify the CONTAINS predicate, SAP HANA runs the following internal checks: 

● SAP HANA checks if the query contains one or more terms. If the query contains multiple terms, the terms 

are tokenized and concatenated. 

● SAP HANA checks whether the query is to be run on one or more columns. If you only specify one column, to 

optimize the search, additional processes are skipped and the query is run on the single column. If you specify 

a wildcard, and therefore possibly numerous columns, SAP HANA automatically determines which columns 

are relevant for the search query. 

After the checks are performed, SAP HANA builds and runs an internal query on the relevant columns only. 

Note: 

If a column has a full text index assigned, SAP HANA will automatically search on the index rather than on 

the original column. 

Determination of Search-Relevant Columns 

You can specify the search-relevant columns either at the creation of the view or directly for the query. SAP HANA 

determines which relevant columns to search based on the following hierarchy: 

1. You specify a list of columns within the CONTAINS predicate. Even if a list of columns has been defined for 

the view, it is overridden by the columns stated in the query. 

2. If you enter an asterisk (*) instead of a column list but you specified a list of relevant columns when creating 

the view, this list is used for the query. 

3. If you enter an asterisk (*) and no list was provided when the view was created, all visible columns of the view 

or table are considered as search-relevant. 

For information about creating views, see Creating Views in the SAP HANA Administration Guide. 

Search Operators and Syntax 

With the CONTAINS predicate, SAP HANA supports the following search operators: 

● OR 

Matches are returned that contain at least one of the terms joined by the OR operator. 

● - (minus) 

With a minus sign, SAP HANA searches in columns for matches that do not contain the term immediately 

following the minus sign. 

● " " (quotation marks) 



P U B L I C 


Terms within the quotation marks are not tokenized and are handled as a string. Therefore, all search 

matches must be exact. 

Note: If you enter multiple search terms, the AND operator is automatically interpreted. Therefore, you do 

not need to specify it. 

For more information about the unique syntax requirements of the CONTAINS predicate, see the SAP HANA SQL 

Reference. 

Scalar Functions 

For search queries using the CONTAINS predicate, you can use different scalar functions to either return 

additional information about the results of your search queries or enhance how the results are displayed. These 

functions include SNIPPET, HIGHLIGHTED, and SCORE. 

Limitations 

The following limitations apply to search queries using the CONTAINS predicate: 

● You cannot search on more than one table or view at a time. If more than one table is joined in the SELECT 

statement, then all columns mentioned in the CONTAINS predicate must come from only one of the tables. 

● You cannot enter a minus (-) search operator directly after OR. 

● Brackets are not supported as search operators. 

● Searches using the CONTAINS predicate do not consider non-physical columns, such as calculated columns, 

as search-relevant because these columns are created during the search and, therefore, are not available 

when SAP HANA internally checks the CONTAINS search query. 

● The CONTAINS predicate only works on column-oriented tables. 

● If you specify multiple CONTAINS predicates in the WHERE clause of the SELECT statement, only one of the 

predicates is allowed to consist of more than one column in the list of . 

Related Links 

SAP HANA SQL Reference: CONTAINS Predicate 

SAP HANA Administration Guide 

SNIPPET Function 

For search queries using the CONTAINS predicate, you can use the function SNIPPET to return search results 

with an excerpt of the text with your search term highlighted in bold. This short text excerpt provides some 

context for you to see where and how the term is used in the document. 

This function uses the following syntax: 

SELECT *, SNIPPET () FROM 

WHERE CONTAINS () 

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P U B L I C 



Enabling Search

Limitations 

The SNIPPET function has the following limitations: 

● Only the first search term specified with the CONTAINS predicate is highlighted in the returned text. 

● The query result contains only the first hit of the first search term. 

● The text excerpt that is displayed with the search term is limited to a string of 12 tokens. 

● This function only works on columns of the TEXT data type or columns with a full text index. 

HIGHLIGHTED Function 

For search queries using the CONTAINS predicate, you can use the function HIGHLIGHTED to return the 

content of the found document with your search term highlighted in bold. 

Search queries using the HIGHLIGHTED function return the data type NCLOB. 


SELECT *, HIGHLIGHTED () FROM 


Limitations 

The HIGHLIGHTED function has the following limitations: 

● Only the first search term specified with the CONTAINS predicate is highlighted in the returned text. 

● The query result contains all hits of the first search term. 

● This function only works on columns of the TEXT data type or columns with a full text index. 

SCORE Function 

For search queries using the CONTAINS predicate, you can use the function SCORE to get the score, that means 

the relevance, of a record found. 

SAP HANA calculates a score based on the following information: 

● The relevance or weighting of attributes in a search using the CONTAINS predicate. The relevance of a hit 

depends on the weight of the column that caused the hit. You can specify weights when you create the view or 

in the CONTAINS predicate. 

● Fuzziness in fuzzy search. The more exact a hit is, the higher the score is. 

● Text ranking (TF-IDF). 


SELECT SCORE (),* FROM 


11.2.2 EXACT Search 

An exact search returns records only if the search term or search phrase is contained in the table column exactly 

as specified. In the SELECT statement of the search query, you can specify the EXACT search type. 

In an exact search, the search engine uses the word dictionary and the phrase index to detect the possible 

matches. The search engine then checks whether the words appear and use exactly the same spelling. 



P U B L I C 


● For text columns, the search term must match at least one of the tokenized terms to return a column entry as 

a match. 

● For string columns, the search term must match the entire string to return a column entry as a match. 

Note: For more flexibility in a search query, you can use the supported wildcards % and *. Wildcards are 

supported for both text and string columns. 

You can perform an exact search by using the CONTAINS predicate with the EXACT option in the WHERE clause 

of a SELECT statement. The exact search is the default search type. If you do not specify any search type in the 

search query, an exact search will be executed automatically. 


WHERE CONTAINS (, , EXACT) 


WHERE CONTAINS (, ) 

--- Exact search will be executed implicitly. 


WHERE CONTAINS (, '"cats and dogs"') 

--- Phrase search. 

11.2.3 LINGUISTIC Search 

A linguistic search finds all words that have the same word stem as the search term. It also finds all words for 

which the search term is the word stem. In the SELECT statement of the full text search query, you can specify 

the LINGUISTIC search type. 

When you execute a linguistic search, the system has to determine the stems of the searched terms. It will look up 

the stems in the stem dictionary. The hits in the stem dictionary point to all words in the word dictionary that have 

this stem 

You can call the linguistic search by using the CONTAINS predicate with the LINGUISTIC option in the WHERE 

clause of a SELECT statement. 

A linguistic search for produced will also find producing and produce. 

Limitations 


WHERE CONTAINS (

Fuzzy search can be used in various applications, for example: 

● Fault-tolerant search in text columns (for example, html or pdf): Search for documents on 'Driethanolamyn' 

and find all documents that contain the term 'Triethanolamine'. 

● Fault-tolerant search in structured database content: Search for a product called 'coffe krisp biscuit' and find 

'Toffee Crisp Biscuits'. 

● Fault-tolerant check for duplicate records: Before creating a new customer record in a CRM system, search for 

similar customer records and verify that there are no duplicates already stored in the system. When, for 

example, creating a new record 'SAB Aktiengesellschaft & Co KG Deutschl.' in 'Wahldorf', the system shall 

bring up 'SAP Deutschland AG & Co. KG' in 'Walldorf' as a possible duplicate. 

You can call the fuzzy search by using the CONTAINS predicate with the FUZZY option in the WHERE clause of a 

SELECT statement. 

Fuzzy Score 


WHERE CONTAINS (, , FUZZY (0.8)) 

Note: You can improve the performance of a fuzzy search on a text column by defining a fuzzy 

index at the column. You can define a fuzzy index with the option FUZZY SEARCH INDEX ON in 

the CREATE FULLTEXT INDEX statement or in the definition of data type TEXT. 

The fuzzy search algorithm calculates a fuzzy score for each string comparison. The higher the score, the more 

similar the strings are. A score of 1.0 means the strings are identical. A score of 0.0 means the strings have 

nothing in common. 

You can request the score in the SELECT statement by using the SCORE() function. You can sort the results of a 

query by score in descending order to get the best records first (the best record is the record that is most similar 

to the user input). When a fuzzy search of multiple columns is used in a SELECT statement, the score is returned 

as an average of the scores of all columns used. 

When searching text columns, a TF/IDF (term frequency/inverse document frequency) score is returned by 

default instead of the fuzzy score. The fuzzy score influences the TF/IDF calculation, but it is important to keep in 

mind that, with TF/IDF, the range of the score values returned is normed to the interval between 0.0 and 1.0, and 

the best record always gets a score of 1.0, regardless of its fuzzy score. 

The TF/IDF calculation can be disabled so that you get the fuzzy score instead. In particular, this makes sense for 

short-text columns containing data such as product names or company names. On the other hand, you should 

use TF/IDF for long-text columns containing data such as product descriptions, HTML data, or Word and PDF 

documents. 

Option spellCheckFactor 

There are two use cases for the option spellCheckFactor. 

● A) This option allows you to set the score for terms that are not fully equal but that would be a 100% match 

because of the internal character standardization used by the fuzzy search. 

For example, the terms 'Café' and 'cafe' give a score of 1.0 although the terms are not equal. For some users it 

may be necessary to distinguish between both terms. 



P U B L I C 


The decision if two terms are equal is based on the term representation stored in the column dictionary. 

Therefore the spellCheckFactor option works differently on string and text columns, as described in the 

following sections. 

● B) The fuzzy search can return a 100% match for terms that are not identical but can't be differentiated by 

the fuzzy-string-compare algorithm. 

For example, fuzzy search can't differentiate between terms 'abaca' and 'acaba', for example. In this case, the 

spellCheckFactor can be used to avoid a score of 1.0. 

When A) and B) are not needed by an application, you can set the spellCheckFactor to 1.0 to disable the feature. 

Standardization of Letters and Terms 

All characters are replaced by a lowercase character without any diacritics before the fuzzy comparison takes 

place. This is called standardization. So it is possible to get a 100% match when comparing two unequal terms, 

because the standardization process returned two identical terms. 

Standardization Examples 

Original Letter Standardized Letter 

E e 

e e 

É e 

é e 

Ė e 

ė e 

The letter i is treated differently as it is not standardized to an ı as would be the 'standard' rule. 


I i 

İ i 

i i 

ı i 

German umlauts are replaced by two characters. 


Ä ae 

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P U B L I C 



Enabling Search


ä ae 

Ö oe 

ö oe 

Ü ue 

ü ue 

ß ss 

Because of this standardization we get high fuzzy scores for common differences in the spelling of words. 

Original term Standardized term 

müller mueller 

Mueller mueller 

Cafe cafe 

Café cafe 

Search on a String Column (VARCHAR, NVARCHAR) 

The decision if two strings are the same is based on the string representation that is stored in the dictionary for 

that column. The contents of a string column are converted to lowercase characters before they are stored in the 

dictionary. Other standardizations are not done. 

So it is possible to use the spellCheckFactor option to, for example, distinguish between 'café' and 'cafe'. 

CREATE COLUMN TABLE test_spell_check_factor 

( 

id INTEGER PRIMARY KEY, 

s NVARCHAR(255) 

); 

INSERT INTO test_spell_check_factor VALUES ('1','Muller'); 

INSERT INTO test_spell_check_factor VALUES ('2','Mueller'); 

INSERT INTO test_spell_check_factor VALUES ('3','Müller'); 

INSERT INTO test_spell_check_factor VALUES ('4','Möller'); 

SELECT SCORE() AS score, id, s 

FROM test_spell_check_factor 

WHERE CONTAINS(s, 'Müller', FUZZY(0.5, 'spellCheckFactor=0.9')) 

ORDER BY score DESC; 

DROP TABLE test_spell_check_factor; 



P U B L I C 


SCORE ID T Description 

1.0 3 Müller 

0.9 2 Mueller

Option similarCalculationMode 

The option similarCalculationMode controls how the similarity of two strings (or, for TEXT attributes, terms) is 

calculated. 

Score calculation modes 

Basically, the similarity of two strings is defined by the number of common characters, wrong characters, 

additional characters in the search string and additional characters in the reference string. 

There are the following calculation modes: 

Table 12: Modes 

Mode Impact on wrong 

characters 

Impact on additional 

characters in search 

search high high low 

compare (default) moderate high high 

symmetricsearch high moderate moderate 

Note that high impact results in a lower score. 

Table 13: Examples with score 

Request Reference Compa 

re 

Search Symmetricsearch 

search searching 0.76 0.96 0.86 

search search 0.85 0.75 0.75 

search searchingforextrater 

searchingforextrater 

restriallife 


restriallife 


restriallife 

SQL Examples 

Preparations 

restriallife 

0.0 0.91 0.87 

searching 0.0 0.35 0.84 

search 0.0 0.24 0.79 

searchingforthemea 

ningoflife 

0.6 0.57 0.6 

OP TABLE test_similar_calculation_mode; 

CREATE COLUMN TABLE test_similar_calculation_mode 

( 



Impact on additional 

characters in table 

P U B L I C 


); 


s NVARCHAR(255) 

INSERT INTO test_similar_calculation_mode VALUES ('1','stringg'); 

INSERT INTO test_similar_calculation_mode VALUES ('2','string theory'); 

INSERT INTO test_similar_calculation_mode VALUES ('3','this is a very very 

very long string'); 

INSERT INTO test_similar_calculation_mode VALUES ('4','this is another 

very long string'); 

similarCalculationMode compare 

SELECT TO_INT(SCORE()*100)/100 AS score, id, s 

FROM test_similar_calculation_mode 

WHERE CONTAINS(s, 'explain string theory', FUZZY(0.5, 

'similarCalculationMode=compare')) 


Score ID S 

0.69 2 string theory 

similarCalculationMode search 




'similarCalculationMode=search')) 


Score ID S 

0.68 4 this is another very long string 

0.66 3 this is a very very very long string 


similarCalculationMode symmetricsearch 




'similarCalculationMode=symmetricsearch')) 


Score ID S 


0.71 1 stringg 

0.61 4 this is another very long string 

0.58 3 this is a very very very long string 

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P U B L I C 



Enabling Search

Supported Data Types 

Fuzzy search works out-of-the-box on the following column-store data types: 

● TEXT 

● SHORTTEXT 

● VARCHAR, NVARCHAR 

● DATE 

● All data types with a full-text index 

String Types 

String types support a basic fuzzy string search. The values of a column are compared with the user input, using 

the fault-tolerant fuzzy string comparison. 

When working with string types, the fuzzy string comparison always compares the full strings. If searching with 

'SAP', for example, a record such as 'SAP Deutschland AG & Co. KG' gets a very low score, because only a very 

small part of the string is equal (3 of 27 characters match). 

A fuzzy search on string types is an alternative to a non-fault-tolerant SQL statement such as 

SELECT ... FROM products WHERE product_name = 'coffe krisp biscuit' ... 

which would not return any results because of the spelling errors. 

Supported SQL data types are 

● VARCHAR 

● NVARCHAR 

It is possible to speed up the fuzzy search by creating additional data structures, which are used for faster 

calculation of the fuzzy score. These data structures exist in the memory only, so no additional disk space is 

required. 

To get the best response times possible, you should enable the fast fuzzy search structures for all database 

columns that have a high load of fuzzy searches, and for all database columns that are used in performance- 

critical queries. 

Text Types 

Text types support a more sophisticated kind of fuzzy search. Texts are tokenized (split into terms) and the fuzzy 

comparison is done term by term. 

For example, when searching with 'SAP', a record such as 'SAP Deutschland AG & Co. KG' gets a high score, 

because the term 'SAP' exists in both texts. A record such as 'SAPPHIRE NOW Orlando' gets a lower score, 

because 'SAP' is only a part of the longer term 'SAPPHIRE' (3 of 8 characters match). 

A fuzzy search in text columns replaces non-fault-tolerant statements such as 



P U B L I C 


SELECT ... FROM documents WHERE doc_content LIKE '% Driethanolamyn %' ... 

Supported SQL data types are 

● TEXT 

● SHORTTEXT 

● Full-text index 

A full-text index is an additional index structure that can be defined for non-text columns to add text search 

features. Supported column types are, for example, NCLOB and NVARCHAR. 

It is possible to speed up the fuzzy search by creating additional data structures, which are used for faster 

calculation of the fuzzy score. These data structures exist in the memory only, so no additional disk space is 

required. To create the additional structures, use the flag 'fast_fuzzy_search' when creating a TEXT or 

SHORTTEXT column or when creating a full-text index. 

To get the best response times possible, you should enable the fast fuzzy search structures for all database 

columns that have a high load of fuzzy searches and for all database columns that are used in performance- 

critical queries. 

Other Types 

Fuzzy search is available for the SQL type DATE. A fuzzy search on date values checks for date-specific errors 

such as dates that lie within a given range of days, or dates where the month and day have been interchanged (for 

example, American versus British date format). 

It is not possible to create additional data structures for date types to speed up the search. The queries run with 

optimal performance without any database tuning. 

Syntax 

You can call the fuzzy search by using the CONTAINS() function with the FUZZY() option in the WHERE clause of a 

SELECT statement. 

Basic example without additional search options 

SELECT SCORE() AS score, * 

FROM documents 

WHERE CONTAINS(doc_content, 'Driethanolamyn', FUZZY(0.8)) 


Example with additional search options 

Additional search options that change the default behavior of the fuzzy search can be specified as additional 

string parameters in the FUZZY() function. 

SELECT SCORE() AS score, * 

FROM documents 

WHERE CONTAINS(doc_content, 'Driethanolamyn', FUZZY(0.8, 'option1=value1, 

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P U B L I C 



Enabling Search

option2=value2')) 


The search options are specified as a comma-separated list of key-value pairs. 

Available Fuzzy Search Options 

Note that some data types in the table below are data-type combinations. 

● Text: SQL types TEXT and SHORTTEXT and any columns that have an additional full-text index 

● String: SQL types VARCHAR and NVARCHAR 

● Date: SQL type DATE 

Table 14: Available Fuzzy Search Options 

Name of Option Short 

Name 

textSearch ts fulltext, 

Range Defa 

ult 

compare 

fullte 

emptyScore es 0.0..1.0 not 

similarCalculatio 

nMode 

spellCheckFacto 

r 

abbreviationSimi 

larity 

bestMatchingTo 

kenWeight 



scm search, 

compare, 

symmetri 

csearch 

xt 

set 

comp 

are 

Applies to 

Types 

Text, String, 

Date 

Text, String, 

Date 

Description 

Switches between full-text search with TF/IDF 

score and duplicate search with fuzzy score. 

For more information, see Option textSearch 

[page 285]. 

Defines how an empty and a non-empty value 

shall match. 

Text, String Defines how the score is calculated for a 

comparison of strings (or terms in a Text 

column). 

For more information, see Option 

similarCalculationMode [page 257] . 

scf 0.0..1.0 0.9 Text, String Sets the score for strings that get a fuzzy score of 

abs 0.0..1.0 0.0 Text 

bmtw 0.0..1.0 0 Text 

1.0 but are not fully equal. 


spellCheckFactor [page 253]. 

Activates abbreviation similarity and sets the 

score. 


abbreviationSimilarity [page 283]. 

Influences the score, shifts total score value 

between best token score values and root mean 

square of score values. 

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Name 

considerNonMat 

chingTokens 

Range Defa 

ult 

cnmt max, min, 

all, input, 

table 

max Text 

minTextScore mts 0.0..1.0 0.0 Text 

andSymmetric as on,off off Text 

andThreshold at 0.0..1.0 1.0 Text 

termMappingTa 

ble 

termMappingLis 

tId 

tmt not 

set 

Applies to 

Types 

Text 

tmli Text 

stopwordTable st not 

set 

Text 

stopwordListId sli Text 

262 

P U B L I C 


Description 

For more information, see Fuzzy Multi-Token 

Search on Text Columns [page 278]. 

Influences the score, defines the number of 

terms used for score calculation. 


Search on Text Columns [page 278]. 

Minimum score of a TEXT field; if not reached, 

the record will not be part of the result. 

For more information, see Option minTextScore 

[page 284]. 

Activates a symmetric AND content search. 


Search with Soft AND [page 281]. 

Activates a 'soft AND' and determines the 

percentage of the tokens that need to match. 



Activates the term mappings. 

For more information, see Fuzzy Search with 

Term Mappings [page 291]. 

Activates the term mappings. 



Activates the stopwords. 


Stopwords. 

Activates the stopwords. 


Stopwords. 


Enabling Search


Name 

maxDateDistanc 

e 

Range Defa 

ult 

mdd 0..100 0 Date 

Applies to 

Types 

Description 

Specifies the allowed date distance when using 

fuzzy search on dates. 

For more information, see Fuzzy Search on DATE 

Columns [page 294]. 

For a list of all allowed search parameter combinations, see Option textSearch [page 285]. 

Support Information 

Memory Usage 

Currently, all data structures for the fuzzy search share a common 'Pool/FuzzySearch' allocator. 

Statistics can be obtained through the system view M_HEAP_MEMORY. 

SELECT * FROM sys.m_heap_memory WHERE category LIKE '%FuzzySearch%' 

Activating the Trace in the SAP HANA Studio 

1. In the SAP HANA studio, open the Administration perspective by double-clicking your system name in the 

navigation pane. 

2. Select the Diagnosis Files tab and choose Configure in the right corner, as shown below. 

3. To configure the trace targets, choose Show All Components and filter for fuzzysearch, as shown below. 



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To get basic tracing data with information for every search, set the trace level to INFO. 

To get detailed information for every search, set the trace level to DEBUG. 

Note: Note that DEBUG information cannot be read by end users and should be used for support 

issues only. 

The default name for the trace file is indexserver_$host_$port.000.trc. 

Basic Examples 

Speeding Up the Fuzzy Search 

You can speed up the fuzzy search for all SQL types except DATE by creating a special data structure called fuzzy 

search index. The additional data structures increase the total memory footprint of the loaded table. In 

unfavorable cases, the memory footprint of the column can double. 

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P U B L I C 



Enabling Search

TEXT and SHORTTEXT 

TEXT and SHORTTEXT columns offer the option 'FUZZY SEARCH INDEX' to enable and disable the additional data 

structures. 

When creating a table: 

CREATE COLUMN TABLE mytable 

( 


col1 TEXT FUZZY SEARCH INDEX ON FAST PREPROCESS ON, 

col2 SHORTTEXT(100) FUZZY SEARCH INDEX ON 

); 

Full-Text Index 

A full-text index offers the option 'FUZZY SEARCH INDEX' to enable and disable the additional data structures. 

When creating a full-text index: 


( 

col1 NVARCHAR(2000) 

); 

CREATE FULLTEXT INDEX myindex ON mytable(col1) 

FUZZY SEARCH INDEX ON 

FAST PREPROCESS ON; 

This can be changed at a later point in time by using the ALTER FULLTEXT INDEX command: 

ALTER FULLTEXT INDEX myindex FUZZY SEARCH INDEX OFF; 

VARCHAR and NVARCHAR 

VARCHAR and NVARCHAR columns also offer the option 'FUZZY SEARCH INDEX' to enable and disable the 

additional data structures. 

When creating a table: 


( 


col1 VARCHAR(100) FUZZY SEARCH INDEX ON, 

col2 NVARCHAR(100) FUZZY SEARCH INDEX ON 

); 

Additional performance improvements are possible when creating database indexes on the columns. 

CREATE INDEX myindex1 ON mytable(col1); 

CREATE INDEX myindex2 ON mytable(col2); 

The state of the fuzzy search index can be changed at a later point in time by using the ALTER TABLE statement. 

ALTER TABLE mytable ALTER 

( 



P U B L I C 


col1 VARCHAR(100) FUZZY SEARCH INDEX OFF, 


); 

The view SYS.TABLE_COLUMNS shows the current state of the fuzzy search index. When working with attribute 

views, this information is also visible in SYS.VIEW_COLUMNS. 

SELECT column_name, data_type_name, fuzzy_search_index 

FROM table_columns 

WHERE table_name = 'MYTABLE'; 

Fuzzy Search on One Column 

1. Create the data. 

CREATE COLUMN TABLE companies 

( 


companyname SHORTTEXT(200) FUZZY SEARCH INDEX ON 

); 

INSERT INTO companies VALUES (1, 'SAP Corp'); 

INSERT INTO companies VALUES (2, 'SAP in Walldorf Corp'); 

INSERT INTO companies VALUES (3, 'ASAP'); 

INSERT INTO companies VALUES (4, 'ASAP Corp'); 

INSERT INTO companies VALUES (5, 'BSAP orp'); 

INSERT INTO companies VALUES (6, 'IBM Corp'); 

2. Perform the search on one column. 

SELECT SCORE() AS score, * FROM companies 

WHERE CONTAINS(companyname,'xSAP Corp Walldorf', 

FUZZY(0.7,'textSearch=compare,bestMatchingTokenWeight=0.7')) 


SCORE ID COMPANYNAME 

0.94 2 SAP in Walldorf Corp 

Fuzzy Search on Two Columns 

1. Create the data. 

266 

CREATE COLUMN TABLE companies2 

( 


companyname SHORTTEXT(200) FUZZY SEARCH INDEX ON, 

contact SHORTTEXT(100) FUZZY SEARCH INDEX ON 

); 

INSERT INTO companies2 VALUES (1, 'SAP Corp', 'Mister Master'); 

INSERT INTO companies2 VALUES (2, 'SAP in Walldorf Corp', 'Master 

Mister'); 

INSERT INTO companies2 VALUES (3, 'ASAP', 'Nister Naster'); 

INSERT INTO companies2 VALUES (4, 'ASAP Corp', 'Mixter Maxter'); 

INSERT INTO companies2 VALUES (5, 'BSAP orp', 'Imster Marter'); 

INSERT INTO companies2 VALUES (6, 'IBM Corp', 'M. Master'); 

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Enabling Search

2. Perform the search on two columns. 

SELECT SCORE() AS score, * FROM companies2 

WHERE CONTAINS(companyname, 'IBM', 


AND CONTAINS(contact, 'Master', 



SCORE ID COMPANYNAME CONTACT 

0.91 6 IBM Corp M. Master 

3. Perform a freestyle search. 

SELECT SCORE() AS score, * FROM companies2 

WHERE CONTAINS((companyname,contact), 'IBM Master', FUZZY(0.7)) 


SCORE ID COMPANYNAME CONTACT 

0.8 6 IBM Corp M. Master 

Note: Freestyle search always uses TF/IDF to calculate the score and does not support parameters 

such as 'textSearch=compare' or 'bestMatchingTokenWeight=0.7' that influence score calculation. 

Therefore, we get a different score for the same record. 

Fuzzy Search on String Columns 

String types support a basic fuzzy string search. The values of a column are compared with the user input using 

the fault-tolerant fuzzy string comparison. 

When working with string types, the fuzzy string compare always compares the full strings. When, for example, 

searching with 'SAP', a record such as 'SAP Deutschland AG & Co. KG' gets a very low score, because only a very 

small part of the string is equal (3 of 27 characters match). 

A fuzzy search on string types is a replacement for a non-fault-tolerant SQL statement such as 

SELECT ... FROM products WHERE product_name = 'coffe krisp biscuit' ... 

that would not return any results because of the spelling errors. 

Supported SQL data types are VARCHAR and NVARCHAR. 

It is possible to speed up the fuzzy search by creating additional data structures called 'fuzzy search indexes', 

which are used for a faster calculation of the fuzzy score. These indexes exist in the memory only, so no additional 

disk space is needed. 

To get the best response times possible, you should enable the fuzzy search indexes for all database columns that 

have a high load of fuzzy searches and for all database columns that are used in performance-critical queries. 



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Use Case Fuzzy Search - House Numbers 

Score Calculation 

The house number comparison aims for a 'simple' solution that is easy to understand, gives good results, and 

works for most countries. The limitations of the algorithm are: 

● The algorithm focuses on numeric values - either a single number ('8') or a range of numbers ('8 - 12'). 

● House number additions (for example, the 'a' in '8a') are either equal or not equal. 

When comparing two strings containing house numbers with each other, the score is calculated according to the 

rules described below. 

House number addition. A house number addition in terms of this backlog item is any additional text that is 

written before or after the numeric value of a house number. 

House number ranges. When a string contains at least two numbers and there is a dash between the first and 

second number, this is treated as a house number range. The first number is the lower bound of the range, the last 

number is the upper bound. 

Multiple numbers. When multiple numbers are part of a house number string that does not define a house 

number range, the first number is the house number used for the comparison. All remaining information is used 

as a house number addition. 

Whitespace characters. For all rules, whitespace characters are ignored when comparing the house numbers. 

For the score calculation it does not matter if a house number is given as '8a' or '8 a' or if it is '8-10' or '8 - 10'. 

Symmetry. In all examples, the score calculation is symmetric. This means that either string 1 or string 2 can be 

the user input and the other string is stored in the database table. 

Rule 1 - House Numbers or House Number Ranges Are Identical 

For identical house numbers, a score of 1.0 is returned. Identical house numbers are house number strings that 

are equal when whitespace characters are ignored. 

Examples: 

String 1 String 2 Score 

5 5 1.0 

5a 5 a 1.0 

8-12 8-12 1.0 

9 in the backyard 9 in the backyard 0.9 

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Enabling Search

Rule 2 - House Numbers or House Number Ranges Are Very Similar (House 

Number Additions Are Different) 

House numbers or house number ranges are considered very similar when the numeric values are identical but 

the additional information differs. 

Examples: 


5 5 a 0.9 

5a 5 b 0.9 

5 Nr. 5 0.9 

8-12 8 - 12a 0.9 

8-12 8 - 12/5 0.9 

8 this is a long text -12 8 - 12a 0.9 

7 below 7 0.9 

9 9 in the backyard 0.9 

9 in the backyard 9 in the backyard 0.9 

Rule 3 - House Numbers or House Number Ranges Are Less Similar 

House numbers and house number ranges are considered less similar in the following cases: 

1. A house number is compared to a house number range and the numeric value of the house number equals the 

lower or upper bound of the range. 

2. Two house number ranges are compared and the numeric value of either the lower or upper bound are equal. 


8 8-12 0.8 

12a 8-12 0.8 

8-10 8-12 0.8 

8-10 8-10/12 0.8 

10-12a 8-12 0.8 

8 in the backyard 8-12 0.8 

Rule 4 - Overlapping House Number Ranges 

House numbers and house number ranges overlap in the following cases: 



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1. A house number is compared to a house number range and the numeric value of the house number lies within 

the range. 

2. Two house number ranges are compared and the ranges overlap. 

Examples: 


10 8-12 0.7 

10a 8-12 0.7 

9 8-12 0.7 

8-12 10-14 0.7 

8-12a 10b-14 0.7 

Last Rule - House Numbers Are Not Equal 

Examples: 


5 6 0.0 

8a 9a 0.0 

6 8-12 0.0 

8-10 12-14 0.0 

House Number Columns and Other String Search Options 

The following search options available for string column types are not valid for house number columns. 

SpellCheckFactor 

When comparing house numbers, the search option 'spellCheckFactor' is ignored. So for house numbers, the 

results are always the same as with 'spellCheckFactor=1.0'. 

SimilarCalculationMode 

When comparing house numbers, the search option 'similarCalculationMode' is ignored and has no effect on the 

search result. Both options are ignored, no error is returned when any of the options is given. 

SQL Syntax 

To enable the search for house numbers on an (N)VARCHAR column, the FUZZY SEARCH MODE clause is used in 

a CREATE TABLE statement. 

CREATE COLUMN TABLE tab 

( 


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P U B L I C 



Enabling Search

col1 NVARCHAR(20) FUZZY SEARCH MODE 'housenumber' 

); 

To enable or disable the house number search mode at a later point in time, you use the ALTER TABLE statement. 

The fuzzy search mode is not changed if the FUZZY SEARCH MODE clause is omitted. 

-- enable housenumber search 

ALTER TABLE tab ALTER 

( 

col1 VARCHAR(20) FUZZY SEARCH MODE 'housenumber' 

); 

-- disable housenumber search 


( 

col1 VARCHAR(20) FUZZY SEARCH MODE NULL 

); 

-- do not change the status of the search mode 


( 

col1 VARCHAR(20) 

); 

You can query the state of the fuzzy search mode by using the system view TABLE_COLUMNS. 

SELECT column_name, data_type_name, fuzzy_search_mode 


WHERE table_name = 'TAB'; 

Example 

Note: You cannot use a fuzzy search index in combination with the house number search mode. 

The following example creates a table that contains a single house number column only and executes some 

searches on this column. 

CREATE COLUMN TABLE housenumbers 

( 

housenumber NVARCHAR(50) FUZZY SEARCH MODE 'housenumber' 

); 

INSERT INTO housenumbers VALUES ('5'); 

INSERT INTO housenumbers VALUES ('5a'); 

INSERT INTO housenumbers VALUES ('5 a'); 

INSERT INTO housenumbers VALUES ('Nr. 5'); 

INSERT INTO housenumbers VALUES ('8-12'); 

INSERT INTO housenumbers VALUES ('8 - 12'); 

INSERT INTO housenumbers VALUES ('8 - 12a'); 

INSERT INTO housenumbers VALUES ('Nr. 8-12'); 

INSERT INTO housenumbers VALUES ('8 - 12/5'); 






P U B L I C 


INSERT INTO housenumbers VALUES ('10-12a'); 




SELECT TO_DECIMAL(SCORE(),3,2), * 

FROM housenumbers 

WHERE CONTAINS(housenumber, '5', FUZZY(0.8)) 

ORDER BY TO_DECIMAL(SCORE(),3,2) DESC; 



WHERE CONTAINS(housenumber, 'Nr. 5', FUZZY(0.8)) 




WHERE CONTAINS(housenumber, '8a-12', FUZZY(0.8)) 




WHERE CONTAINS(housenumber, '10-12', FUZZY(0.8)) 




WHERE CONTAINS(housenumber, '9 in the BACKYARD', FUZZY(0.8)) 


Use Case Fuzzy Search - Postcodes 

Postcodes in almost all countries are ordered by region. This means that if the leading characters of the 

postcodes of two different addresses are the same, the addresses are near to each other. In Germany, for 

example, addresses within large cities share the first or even the first two digits of their postcode. 

The only exception known to the development team is Cambodia, where postcodes are not ordered by region. 

When doing a fuzzy search on addresses, it makes sense to return a higher score for postcodes that are 'near' to a 

given user input than for postcodes that are 'far away' from the user input. It makes sense to give a higher weight 

to the leading characters and a lower weight to the trailing characters of the postcode. 

Valid addresses may contain a country code in front of the postcode (for example, 'D-12345' or 'DE-12345' for a 

German address). This is also supported by the fuzzy postcode search. 

Score Calculation 

Before the fuzzy score is calculated, the postcode strings are standardized. 

1. Country codes are separated from the postcode strings. Country codes in this case consist of one to three 

272 

letters (a-z only, no numbers) at the beginning of the postcode, followed by a minus sign. Longer words are 

not considered a country code because postal standards do not allow country names in front of the postcode. 

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Enabling Search

2. Country codes are standardized to enable a comparison of different codes for the same country, for example, 

'D-', 'DE-' and 'DEU-' for German postcodes. All unknown/invalid country codes are standardized to one 

special 'dummy' country code. 

3. Spaces and dashes are removed from the remaining postcode. 

4. All letters are standardized to uppercase. 

User Input Country Code Remaining Postcode 

71691 71691 

716 91 71691 

D-71691 D 71691 

DE-71 691 DE 71691 

D 71691 D71691 

Germany-71691 GERMANY71691 

GB-A1H 2ZU GB A1H2ZU 

A1H-2ZU A1H2ZU 

gb-A1h 2zu GB A1H2ZU 

XY-12345 XX 12345 

zz-12345 XX 12345 

AI-2640 AI 2640 

The last example is the only known example where the country code is part of the postcode (AI = Anguilla). The 

algorithm works here as well, as the country code is also compared. The two examples directly above the AI 

example show invalid country codes. Both are standardized to the same non-existent 'dummy' country code. 

Postcode Comparison 

The standardized postcodes are compared using a variation of the fuzzy string comparison. This variation gives a 

higher weight to the first two characters of the postcode. 

Country codes are given the same weight as a single character at the end of the postcode. 

● Only postcodes with the same country code can get a score of 1.0. 

● If one country code is given and the second country code is empty, the score of the postcode comparison is 

less than 1.0. 

● If both country codes are given and are different, the score of the postcode comparison is also less than 1.0. 



P U B L I C 


Parameter similarCalculationMode 

The search option 'similarCalculationMode' with options 'search' and 'symmetricsearch' is available for postcode 

columns. 

When using the search option 'similarCalculationMode', a postcode search with a postcode prefix will find all 

addresses in a given area. 

● A search with '71' returns all postcodes beginning with '71'. 

● A search with '1234' returns all postcodes starting with a sequence similar to '1234' and, with a lower score, all 

postcodes that contain a '1234'. 

Parameter spellCheckFactor 

Two postcodes may be considered identical by the fuzzy string comparison, but may still be different. In this case, 

the value of the parameter 'spellCheckFactor' is applied and the score is multiplied by the spellCheckFactor. 

Examples for non-equal postcodes that get a score of 1.0 are: 

● '123456' and '12 34 56' 

● '7070717' and '7071707' 

The default value of the search option spellCheckFactor is 0.9. To disable this feature, set 'spellCheckFactor=1.0'. 

Example 

The following example uses a spellCheckFactor of 1.0, which is not the default value. 

Postcode 1 Postcode 2 Score Remarks 

71691 71691 1.0 

71691 71 691 1.0 

71691 81691 0.51 Highest weight on the 

first digit 

71691 72691 0.7 High weight on the 

second digit 

71691 71692 0.96 Lower weight on all 

other digits 

71691 D-71691 0.96 Country code missing 

in one column 

D-71691 A-71691 0.96 Country codes are 

71691 D-71692 0.92 

D-71691 A-71692 0.92 

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different 


Enabling Search

Postcode 1 Postcode 2 Score Remarks 

GB-A1H 2ZU Gb-a1h2zu 1.0 

XX-12345 YY-12345 1.0 Invalid country codes 

are 'equal' 

D-12345 YY-12345 0.96 Valid and invalid 

SQL Syntax 

country code 

(N)VARCHAR columns have to be defined as postcode columns to enable the fuzzy postcode search. You do this 

by using the FUZZY SEARCH MODE clause. 

In addition, it is also possible to increase the performance of the postcode search by activating a fuzzy search 

index and by creating a database index on the postcode column. 

CREATE COLUMN TABLE tab 

( 


postcode NVARCHAR(20) FUZZY SEARCH INDEX ON FUZZY SEARCH MODE 

'postcode' 

); 

CREATE INDEX myindex1 ON tab(postcode); 

The postcode search can be enabled or disabled at a later point in time with the ALTER TABLE statement. Do not 

specify the FUZZY SEARCH MODE clause to disable the postcode search. 

-- enable postcode search 


( 

postcode NVARCHAR(100) FUZZY SEARCH MODE 'postcode' 

); 

-- disable postcode search 


( 

postcode NVARCHAR(100) FUZZY SEARCH MODE NULL 

); 

-- do not change the status of the search mode 


( 

postcode NVARCHAR(100) 

); 



P U B L I C 


You can query the status of the fuzzy search index and the fuzzy search mode from the system view 

TABLE_COLUMNS. 

SELECT column_name, data_type_name, fuzzy_search_index, fuzzy_search_mode 


WHERE table_name = 'TAB'; 

Example 

CREATE COLUMN TABLE postcodes 

( 

postcode NVARCHAR(50) FUZZY SEARCH INDEX ON FUZZY SEARCH MODE 'postcode' 

); 

INSERT INTO postcodes VALUES ('71691'); 




INSERT INTO postcodes VALUES ('716 91'); 

INSERT INTO postcodes VALUES ('A1H 2ZU'); 

INSERT INTO postcodes VALUES ('A1H2ZU'); 

INSERT INTO postcodes VALUES ('D-71691'); 


INSERT INTO postcodes VALUES ('A-71691'); 

INSERT INTO postcodes VALUES ('A-71692'); 

INSERT INTO postcodes VALUES ('DE-71 691'); 

INSERT INTO postcodes VALUES ('D 71691'); 

INSERT INTO postcodes VALUES ('GB-A1H 2ZU'); 

INSERT INTO postcodes VALUES ('XX-12345'); 




FROM postcodes 

WHERE CONTAINS(postcode, '71691', FUZZY(0.5, 'spellCheckFactor=1.0')) 

ORDER BY SCORE() DESC; 



WHERE CONTAINS(postcode, 'D-71691', FUZZY(0.5, 'spellCheckFactor=1.0')) 




WHERE CONTAINS(postcode, 'Gb-a1h2zu', FUZZY(0.5, 'spellCheckFactor=1.0')) 




WHERE CONTAINS(postcode, 'YY-12345', FUZZY(0.5, 'spellCheckFactor=1.0')) 


SELECT TO_DECIMAL(SCORE(),3,2), *FROM postcodes 





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Fuzzy Search on Text Columns 

Text types support a more sophisticated kind of fuzzy search. Texts are tokenized (split into terms) and the fuzzy 

comparison is done term by term. For example, when searching with 'SAP', a record such as 'SAP Deutschland AG 

& Co. KG' gets a high score, because the term 'SAP' exists in both texts. A record such as 'SAPPHIRE NOW 

Orlando' gets a lower score, because 'SAP' is only a part of the longer term 'SAPPHIRE' (3 of 8 characters match). 

Fuzzy search on text columns replaces non-fault-tolerant statements such as 

SELECT ... FROM documents WHERE doc_content LIKE '% Driethanolamyn %' ... 

The following SQL data types are supported: 

● TEXT 

● SHORTTEXT 

● fulltext index 

A fulltext index is an additional index structure that can be defined for non-text columns to add text search 

features. Supported column types are, for example, NCLOB and NVARCHAR. 

It is possible to speed up the fuzzy search by creating data structures called 'fuzzy search indexes', which are 

used for a faster calculation of the fuzzy score. These indexes exist in the memory only, so no additional disk 

space is needed. 

To get the best response times possible, you should enable the fuzzy search indexes for all database columns that 

have a high load of fuzzy searches and for all database columns that are used in performance-critical queries. 

Fuzzy Search on SQL Type TEXT 

A call to contains that references a TEXT column is automatically processed as a text search. In this case, the 

mode textsearch=compare and all fuzzy search options are allowed: 


( 

col1 TEXT 

); 

SELECT score() AS score, * FROM mytable WHERE contains(col1, 'a b', 

fuzzy(0.8, 'textsearch=compare')); 

Fuzzy Search on SQL Type SHORTTEXT 

When a SHORTTEXT column is created, a column of column store type cs_string and a second hidden text 

column are created. A call to contains that references the SHORTTEXT column is automatically redirected by the 



P U B L I C 


freestyler to the additional hidden TEXT column. In this case, the mode textsearch=compare and all fuzzy search 

options are allowed: 


( 

col1 SHORTTEXT(200) 

); 



Fuzzy Search on a FULLTEXT INDEX 

When a full text index is created on a column that is not of type TEXT (e.g. NVARCHAR, NCLOB, ...) a hidden text 

column is added to the table. A call to contains that references the non-TEXT column is automatically redirected 

by the freestyler to the additional text column. In this case, the mode textsearch=compare and all fuzzy search 

options are allowed: 


( 


); 

CREATE FULLTEXT INDEX myindex ON mytable(col1); 



Merge Delta for Better Performance 

When inserting or loading a large number of rows in a table that has a TEXT or SHORTTEXT column or that uses a 

FULLTEXT INDEX, it is important to merge the delta part of the table to get a good search performance. 

A delta merge can be started manually with the following SQL statement: 

MERGE DELTA OF mytable; 

Alternatively, a delta merge can be triggered automatically by the mergedog process. 

Fuzzy Multi-Token Search on Text Columns 

Content Types 

When using more than one token within a query, the default content type is AND (for example, ... WHERE 

CONTAINS (mycolumn, 'software firm', FUZZY(0.5)) ... will return entries that contain a token similar to 'software' 

and a token similar to 'firm'). 

Alternatively, you can use OR by adding the key word between the tokens (for example, ... WHERE CONTAINS 

(mycolumn, 'apple OR 'banana', FUZZY(0.5)) ... will return entries that contain a token similar to 'apple' and 

entries that contain a token similar to 'banana'). 

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Enabling Search

PHRASE is similar to AND but restricts hits to those that contain the tokens as a phrase, that is, in the same order 

and with nothing between them. A PHRASE is indicated by adding double quotes around the tokens, within the 

single quotes (for example, ... WHERE CONTAINS (mycolumn, '"day dream"', FUZZY(0.5)) ... will not return an 

entry containing 'I dream of a day'). 

The content type AND that is used for a full-text search (default behavior: textSearch=fulltext) is implemented as 

a logical AND to achieve better performance. For example, a search for 'Miller & Miller AG' with content type AND 

matches 'Miller AG'. 

textSearch=compare should be used for duplicate detection and for comparing company names, product names, 

and so on. Here, search results are better because of the strict AND comparison that is used. In other words, if 

you search for 'Miller & Miller' with content type AND, only records that contain the term 'Miller' at least twice are 

returned. 

A strict AND assigns terms from the user input to terms in the database entry only once (and vice versa). For 

more information, see Fuzzy Multi-Token Search with Soft AND [page 281]. 

Parameters Influencing the Score 

Name of Option Range Default Applies to Types 

bestMatchingTokenWeigh 

t 

considerNonMatchingTok 

ens 

Formula for score calculation: 

0.0..1.0 not set TEXT 

max, min, all, input, table max TEXT 

score = bestMatchingTokenWeight x max(tokenScores) + (1-bestMatchingTokenWeight) x √(Σ(tokenScore²)/ 

tokenCount) 

tokenCount is determined according to the parameter considerNonMatchingTokens as follows: 

● input: Use search term token count 

● table: Use column value token count 

● all: Use sum of search and column value token count (where the numerator is multiplied by 2) 

● min: Use smaller value of token counts 

● max: Use larger value of token counts (default) 

Recommendations for specific search content types 

If you are using an "OR" search (searching for "this or that"), you should set considerNonMatchingTokens to table 

to get a useful score assessment. 



P U B L I C 


Example 

DROP TABLE test_table; 

CREATE COLUMN TABLE test_table 

( 


t SHORTTEXT(200) FUZZY SEARCH INDEX ON 

); 

INSERT INTO test_table VALUES ('1','eins'); 

INSERT INTO test_table VALUES ('2','eins zwei'); 

INSERT INTO test_table VALUES ('3','eins zwei drei'); 

INSERT INTO test_table VALUES ('4','eins zwei drei vier'); 

INSERT INTO test_table VALUES ('5','eins zwei drei vier funf'); 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM test_table 

WHERE CONTAINS(t, 'eins zwoi drei', 


ORDER BY score DESC, id; 

SCORE ID T 

1 3 eins zwei drei 

1 4 eins zwei drei vier 

1 5 eins zwei drei vier funf 



FUZZY(0.5,'textSearch=compare,bestMatchingTokenWeight=0')) 


SCORE ID T 

0.92 3 eins zwei drei 

0.8 4 eins zwei drei vier 

0.71 5 eins zwei drei vier funf 



FUZZY(0.5,'textSearch=compare,bestMatchingTokenWeight=0,considerNonMatching 

Tokens=all')) 


SCORE ID T 






FUZZY(0.5,'textSearch=compare,bestMatchingTokenWeight=0,considerNonMatching 

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P U B L I C 



Enabling Search

Tokens=input')) 


SCORE ID T 




Parameters Influencing the Result Set 

Option Range Default Applies to Types 

andSymmetric on,off off TEXT 

andThreshold 0.0..1.0 1.0 TEXT 

For examples, see Fuzzy Multi-Token Search with Soft AND [page 281] . 

Fuzzy Multi-Token Search with Soft AND 

A fuzzy search on one text column can also use a softer AND, so that not all tokens used in the search term have 

to match the result. 

There are two parameters that control this behavior: 

Option Name Range Default Applies to Types Short Description 

andSymmetric on,off off TEXT Activates a 

symmetric AND 

content search 

andThreshold 0.0..1.0 1.0 TEXT Determines the 

Creating example data: 

DROP TABLE test_soft_and; 

CREATE COLUMN TABLE test_soft_and 

( 


t SHORTTEXT(200) FUZZY SEARCH INDEX ON 

); 

INSERT INTO test_soft_and VALUES ('1','eins'); 

INSERT INTO test_soft_and VALUES ('2','eins zwei'); 

INSERT INTO test_soft_and VALUES ('3','eins zwei drei'); 



percentage of 

tokens that need to 

match 

P U B L I C 


INSERT INTO test_soft_and VALUES ('4','eins zwei drei vier'); 

INSERT INTO test_soft_and VALUES ('5','eins zwei drei vier funf'); 

Search with andSymmetric=off 

SELECT SCORE() AS score, * FROM test_soft_and 

WHERE CONTAINS(T, 'eins zwei drei', FUZZY(0.5, 

'andSymmetric=off,bestMatchingTokenWeight=0.5,textSearch=compare')) 


SCORE ID T 




Search with andSymmetric=on 


WHERE CONTAINS(T, 'eins zwei drei', 

FUZZY(0.5,'andSymmetric=on,bestMatchingTokenWeight=0.5,textSearch=compare') 

) 


SCORE ID T 



0.90824830532074 2 eins zwei 


0.788675129413605 1 eins 

Search with andThreshold 


WHERE CONTAINS(T, 'eins XXX drei vier', 

FUZZY(0.5,'andThreshold=0.75,bestMatchingTokenWeight=0.5,textSearch=compare 

')) 


SCORE ID T 




WHERE CONTAINS(T, 'eins XXX drei vier', 

FUZZY(0.5,'andThreshold=0.5,bestMatchingTokenWeight=0.5,textSearch=compare' 

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Enabling Search

)) 


SCORE ID T 



0.853553414344788 3 eins zwei drei 

Option abbreviationSimilarity 

The option abbreviationSimilarity is used to search for and find a word using its first character and vice versa with 

a given score. With abbreviationSimilarity = 0.9, a SELECT retrieves “word” with SCORE = 0.9 when you search 

with “w” (and vice versa). 

CREATE COLUMN TABLE abbrev 

( 


name SHORTTEXT(200) FUZZY SEARCH INDEX ON 

); 

INSERT INTO abbrev VALUES ('1','Peter'); 

INSERT INTO abbrev VALUES ('2','Hans'); 

INSERT INTO abbrev VALUES ('3','H.'); 

INSERT INTO abbrev VALUES ('4','P.'); 

INSERT INTO abbrev VALUES ('5','Hans-Peter'); 

INSERT INTO abbrev VALUES ('6','H.-P.'); 

INSERT INTO abbrev VALUES ('7','HP'); 

INSERT INTO abbrev VALUES ('8','G Gerd'); 

INSERT INTO abbrev VALUES ('9','G'); 

INSERT INTO abbrev VALUES ('10','Gerd'); 

Search one token with abbreviationSimilarity 

SELECT SCORE() AS score, id, name FROM abbrev 

WHERE CONTAINS(name, 'HP', FUZZY(0.5, 

'abbreviationSimilarity=0.80,textSearch=compare')) 


SCORE ID NAME 

1 7 HP 

0.800000011920929 3 H. 

0.565685451030731 6 H.-P. 

Search two tokens with abbreviationSimilarity 


WHERE CONTAINS(name, 'Hans Peter',FUZZY(0.5, 



P U B L I C 




SCORE ID NAME 

1 5 Hans-Peter 

0.800000011920929 6 H.-P. 

Search two tokens with abbreviationSimilarity 


WHERE CONTAINS(name, 'Go Gerd',FUZZY(0.5, 



SCORE ID NAME 

0.905538558959961 8 G Gerd 

Option minTextScore 

The minTextScore option allows you to set the score a text field has to reach to be a match. 

Note: If you use a fuzzySimilarity of 0.0, the parameter minTextScore will be redundant. 

DROP TABLE tab_mintextscore; 

CREATE COLUMN TABLE tab_mintextscore 

( 


t TEXT FAST PREPROCESS ON FUZZY SEARCH INDEX ON 

); 

INSERT INTO tab_mintextscore VALUES ('1','Bert'); 

INSERT INTO tab_mintextscore VALUES ('2','Berta'); 

INSERT INTO tab_mintextscore VALUES ('3','Bart'); 

Search on a text column 

SELECT SCORE() AS score, id, t FROM tab_mintextscore 

WHERE CONTAINS(t, 'Ernie OR Bert', FUZZY(0.100, 'textSearch=compare, 

bestMatchingTokenWeight=0,minTextScore=0.70')) 


SCORE ID T Description 

0.7 1 Bert

Option textSearch 

The textSearch option is used to select the search algorithm for TEXT columns: 

● textSearch=fulltext (default value): A full-text search is done on a TEXT column. IDF calculation or 

specialOrRanking (depending on search flags) is used. This is the 'old' NewDB behavior. 

● textSearch=compare: A search similar to a Fuzzy Double search is done. Additional search options are 

enabled. 

Allowed search options and error handling 

Depending on the data type of a column and the type of the search (freestyle or attribute search) of a query entry, 

some of the searchOptions parameters are not allowed because they do not make sense. 

If the user sets an option that is not allowed, a SQL error is thrown and the SELECT aborts. 

textSearch=compar 

e 

FUZZY-Double-like 

search on TEXT 

attribute search and 

textSearch= 

compare and 

datatype= TEXT 

Full-text search on 

TEXT 


textSearch= fulltext 

and datatype= TEXT 

Freestyle full-text 

search 

freestyle search and 

textSearch= fulltext 

YES n/a n/a NO 

textSearch=fulltext n/a YES n/a (default mode) NO 

similarCalculationM 

ode 

YES YES YES YES 

spellCheckFactor YES YES YES YES 

fuzzySimilarity > 0 YES YES YES YES 

fuzzySimilarity = 0 YES NO NO YES 

Search on types 

other than TEXT 


datatype TEXT 

emptyScore YES NO NO YES (Only valid for 

abbreviationSimilarit 

y 

YES NO NO NO 

text, string and date 

types. Numeric 

types are not 

supported.) 

maxDateDistance NO NO YES YES (Only valid for 



date types. Other 

P U B L I C 


termMappingTable/ 

ListId 

stopwordTable/ 

ListId 

FUZZY-Double-like 

search on TEXT 

Full-text search on 

TEXT 

Freestyle full-text 

search 

YES YES YES NO 

YES NO NO NO 

andThreshold YES NO NO NO 

andSymmetric YES NO NO NO 

bestMatchingToken 

Weight 

considerNonMatchin 

gTokens 

YES NO NO NO 

YES NO NO NO 

minTextScore YES NO NO NO 

Rank Calculation fuzzy score IDF IDF (TEXT) or fuzzy 

Legend 

YES - The parameter is allowed. 

score (other types) 

NO - The parameter is not allowed and an error message is returned if the user sets this option. 

Search on types 

other than TEXT 

types are not 

supported.) 

fuzzy score 

ignored - The parameter is ignored and no error message is returned to the user. This is necessary because the 

freestyler passes all search options to the generated search on single columns. 

Rank calculation 

When 'fulltext' is specified, the search is done using IDF or specialOrRanking (depending on the search flags). The 

fuzzy score is not calculated. 

When 'compare' is specified, the fuzzy score is calculated using bestMatchingTokenWeight and 

considerNonMatchingTokens. The user does not have to set these options. In this case, the default values are 

used. 

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Enabling Search

Fuzzy Search with Stopwords 

Usage 

Stopwords are terms that are less significant for a search and are therefore not used to generate the result set. In 

other words, the search is carried out as if the stopwords are not present (either in the user input or in the 

database column). 

However, stopwords influence the score that is calculated. A record with stopwords identical to the user input 

gets a higher score than a record with differing or missing stopwords. 

Stopwords can be defined either as single terms or as stopword phrases consisting of multiple terms. Stopword 

phrases are only applied when all terms of the stopword appear in exactly the given order. 

Use case example: When searching for company names, the legal form (Ltd, SA, AG, and so on) is less significant 

and less selective than the other parts of the name. 

Stopwords are stored in a column-store table with the following format: 

CREATE COLUMN TABLE mystopwords 

( 

stopword_id VARCHAR(32) PRIMARY KEY, 

list_id VARCHAR(32) NOT NULL, 

language_code CHAR(2), 

term NVARCHAR(200) NOT NULL 

); 

Stopwords are language dependent. It is possible to define the language that a stopword is valid for. You can also 

define stopwords for all languages by not setting a language. 

(It makes sense to add the language information now so that you can make use of the feature when it is available, 

without having to change the stopword definitions.) 

As with term mappings, stopwords can be grouped together in multiple groups. Groups of stopwords are 

identified by the value of the list_id column that is part of the stopword table. 

INSERT INTO mystopwords VALUES (1, 'legalform', '', 'Ltd'); 

INSERT INTO mystopwords VALUES (2, 'legalform', 'de', 'GmbH'); 

INSERT INTO mystopwords VALUES (3, 'legalform', 'de', 'Gesellschaft mit 

beschränkter Haftung'); 

INSERT INTO mystopwords VALUES (4, 'legalform', 'de', 'AG'); 

INSERT INTO mystopwords VALUES (5, 'legalform', 'de', 

'Aktiengesellschaft'); 

To activate stopwords for a search on a TEXT column, you need to provide two search options (similar to the 

options used for term mappings): 

● stopwordListId=mylist1,mylist2,mylist3 



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● stopwordTable=[.] 

SELECT TO_DECIMAL(SCORE(),3,2) as score, company FROM mydata 

WHERE CONTAINS(company, 'xy gmbh', FUZZY(0.7, 'textsearch=compare, 

stopwordTable=MYSTOPWORDS, stopwordListId=legalform')) 


To activate language-specific stopwords, you must provide the language parameter: 

SELECT TO_DECIMAL(SCORE(),3,2) as score, company FROM mydata 

WHERE CONTAINS(company, 'xy gmbh', FUZZY(0.7, 'textsearch=compare, 

stopwordTable=MYSTOPWORDS, stopwordListId=legalform'), language('de')) 


Note: In this case, all stopwords where language_code is set to 'de' or empty will be used. Any stopwords 

with other language codes will be ignored. 

Stopwords are removed from the search term first. In this example, the result set of the search is the same as for 

the search '... WHERE CONTAINS(company, 'xy', ...'. 

When calculating the score, the fuzzy scores of the non-stopword terms have the biggest influence on the 

resulting score. Stopwords in the user input and in the database records are also given less weight than the non- 

stopword terms, so records with matching stopwords get a higher score than records with differing or missing 

stopwords. 

The result of the above example is as follows: 

Score Company Comment 

1.00 XY GmbH 

0.95 XY Missing stopword 

0.95 XY Aktiengesellschaft Differing stopword 

0.92 XY Gesellschaft mit beschränkter 

Haftung 

Many differing stopwords 

0.78 XY Company Additional non-matching term, no 

stopword 

The value given for stopwordTable can be any valid SQL identifier as defined in the SQL reference manual. If 

schema is omitted, the current schema is used. The following examples all reference the same stopword table. 

SET SCHEMA schema1; 

SELECT ... WHERE CONTAINS(c, 'xy', FUZZY(0.7, 

'stopwordTable=schema1.mystopwords, ...'))...; 


'stopwordTable="SCHEMA1"."MYSTOPWORDS", ...'))...; 


'stopwordTable=mystopwords, ...'))...; 

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Enabling Search

Stopword Example 

CREATE COLUMN TABLE stopwords 

( 

stopword_id VARCHAR(32) PRIMARY KEY, 

list_id VARCHAR(32) NOT NULL, 

language_code CHAR(2) NOT NULL, 

term NVARCHAR(200) NOT NULL 

); 


( 



); 

INSERT INTO companies VALUES ('1', 'SAP AG'); 

INSERT INTO companies VALUES ('2', 'SAP Aktiengesellschaft'); 

INSERT INTO stopwords VALUES ('1', '01', 'de', 'AG'); 

INSERT INTO stopwords VALUES ('2', '01', 'de', 'Aktiengesellschaft'); 

INSERT INTO stopwords VALUES ('3', '01', 'de', 'blub'); 

Query 1: User input without stopwords. Stopwords in the database table only. 

SELECT TO_DECIMAL(SCORE(), 3, 2) AS score, * 

FROM companies 

WHERE CONTAINS(companyname, 'sap', FUZZY(0.8, 'stopwordTable=stopwords, 

stopwordListId=01, textSearch=compare')) 

ORDER BY score DESC, ID; 


0.95 1 SAP AG 

0.95 2 SAP Aktiengesellschaft 

Query 2: User input with stopword. Other stopwords in the database table. 



WHERE CONTAINS (companyname, 'sap blub', FUZZY(0.8, 

'stopwordTable=stopwords, stopwordListId=01, textSearch=compare')) 



0.95 1 SAP AG 


Query 3: User input with stopword. One record with matching stopword, one record with differing stopword. 



WHERE CONTAINS (companyname, 'sap aktiengesellschaft', FUZZY(0.8, 





P U B L I C 



1 2 SAP Aktiengesellschaft 

0.95 1 SAP AG 

Query 4: User input with two stopwords. Database records with one matching stopword. 



WHERE CONTAINS (companyname, 'sap ag aktiengesellschaft', FUZZY(0.8, 




0.97 1 SAP AG 


Stopwords Combined With Term Mappings 

When stopwords and term mappings are combined in a single query, term mappings are applied first. Stopwords 

are then applied to all variations of the search term created by the term mappings. 

Example 

Let us assume that you have defined the following term mapping: 

Term 1 Term 2 

Incredible Busy Machines IBM 

Ltd Limited 

Now you search for "Incredible Busy Machines Ltd". 

The search would be carried out for all possible search terms: 

Search Terms 

Incredible Busy Machines Ltd 

Incredible Busy Machines Limited 

IBM Ltd 

IBM Limited 

Let us assume that you have defined the following stopwords: 

Stopword 

busy machines 

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Enabling Search

Stopword 

ltd 

The stopwords will not be searched, so the resulting search terms would be: 

Search Terms 

Incredible Busy Machines Ltd 

Incredible Busy Machines Limited 

IBM Ltd 

IBM Limited 

Fuzzy Search with Term Mappings 

Facts About Term Mappings 

Term mappings have the following characteristics: 

● Term mappings can be used to extend the search by adding additional search terms to the user input. 

Whenever the user enters a search term, the search term is expanded and synonyms, hypernyms, hyponyms, 

and so on are added. The result that is returned to the user contains additional records or documents related 

to the search term that may be useful to the user. 

● Term mappings are defined in a column table and can be changed at any time. 

The current term-mapping definition is applied when a search is started. The definition of term mappings 

does not change the data that is stored in the database tables (in contrast to the definition of synonyms in 

Text Analysis, where a change of synonyms requires a reload or reindexing of the text data). 

● Term mappings can be grouped. 

Each group of term mappings is identified by a list_id that is stored in the term-mapping table. By grouping 

term mappings it is possible to apply different sets of term mappings to different columns of a table. For 

example, you may want to use some term mappings when searching company names and other term 

mappings when searching documents. When starting a search, it is possible to specify the term-mapping 

list_ids that shall be applied to each column. 

● Term mappings can be assigned a weight. 

In this case, records that are found because of a term mapping will get a lower score than records found with 

the original user input. From the user's view, the result list is sorted in a more useful way. 

● Term mappings are defined as a unidirectional replacement. 

For a term-mapping definition of 'term1' -> 'term2', 'term1' is replaced with 'term2', but 'term2' is not replaced 

with 'term1'. This is helpful if you want a search with a hypernym to find all hyponyms, but not the other way 

round. If a bidirectional replacement is needed (as for synonyms), both directions have to be added to the 

term-mapping table. 



P U B L I C 


● Term mappings are language dependent. 

It is possible to define the language that a term mapping is valid for. You can also define term mappings for all 

languages by not setting a language. 

Use Cases 

Synonyms 

If you have a large database of company names, you might want to map the companies' legal forms. 

For example: 

Searching for You would also like to find With a weight of 

AG Aktiengesellschaft 1.0 

Ltd Limited 1.0 

As these are synonyms, the term mappings have to be added to the term-mapping table in both directions, as 

shown in the example below. 

Usually, synonym definitions get a weight of 1.0, because records found when the term mapping is applied are as 

good as records found with the original user input. 

Hypernyms, Hyponyms 

If you search with a hypernym, you might also find other documents related to this topic. 

For example: 

Searching for You would also like to find With a weight of 

car VW Golf 0.8 

As these are not synonyms, and a search with 'VW Golf' shall not return all documents about cars, the term 

mapping is added to the term-mapping table in this direction only. 

Format of the Term-Mapping Table 

Column Name Type Primary Key Description Comment 

MAPPING_ID VARCHAR(32) x Primary key For example, a GUID 

LIST_ID VARCHAR(32) Term-mapping list ID Used to group term 

LANGUAGE_CODE CHAR(2) Language code 

292 

P U B L I C 


(ISO2) 

mappings 

NULL: term mapping 

is valid for all 

languages 


Enabling Search

Column Name Type Primary Key Description Comment 

TERM_1 NVARCHAR(200) Term 1, the term to 

be replaced 

TERM_2 NVARCHAR(200) Term 2, the term 

that replaces term 1 

WEIGHT DECIMAL Weight, 0.0

FUZZY(0.8, 

'termMappingTable=termmappings,termMappingListId=01,textSearch=compare')) 




0.9 1 SAP AG 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM companies 

WHERE CONTAINS(companyname, 'sap ag', 

FUZZY(0.8,'termMappingTable=TERMMAPPINGS,termMappingListId=01,textSearch=co 

mpare')) 



1.0 1 SAP AG 


To activate language-specific term mappings, you must provide the language parameter: 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM companies 

WHERE CONTAINS(companyname, 'sap ag', 

FUZZY(0.8,'termMappingTable=TERMMAPPINGS,termMappingListId=01,textSearch=co 

mpare'), language('de')) 


Note: In this case, all term mappings where language_code is set to 'de' or empty will be used. Any term 

mappings with other language codes will be ignored. 

Fuzzy Search on DATE Columns 

A fuzzy search on DATE columns supports two types of error: 

● Date-specific typos 

● Dates lying within a user-defined maximum distance 

Score Calculation for Typos 

Instead of using Levenshtein distance or other string-compare algorithms, the following date-specific typos and 

errors are defined as similar: 

1. One wrong digit at any position (for example, 2011-08-15 instead of 2011-08-25). This type of error gets a 

score of 0.90. 

2. Two digits interchanged within one component (day, month, or year) (for example, 2001-01-12, 2010-10-12, or 

2010-01-21 instead of 2010-01-12). This type of error gets a score of 0.85. 

3. Month and day interchanged (US versus European date format) (for example, 2010-10-12 instead of 

294 

2010-12-10). This type of error gets a score of 0.80. 

P U B L I C 



Enabling Search

Only one of these errors is allowed. Dates with more than one error are not considered similar, so the score is 0.0. 

Dates with a score less than the fuzzySimilarity parameter are not returned. 

Example: 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM dates 

WHERE CONTAINS(dateofbirth, '2000-01-10', FUZZY(0.8)) 


For this example we get: 

2000-01-09 -> 0.00 (not returned to the user) 

2000-01-10 -> 1.00 

2000-01-11 -> 0.90 

2000-01-12 -> 0.90 

... 

2000-01-21 -> 0.00 (not returned to the user) 

... 

2000-10-01 -> 0.80 

Score Calculation for Date Distance 

The maximum allowed distance between dates can be defined using the search option 'maxDateDistance', which 

defines a number of days. 

The default for this option is 0, that is, the feature is disabled. This is shown in the following example: 


WHERE CONTAINS(dateofbirth, '2000-01-10', FUZZY(0.95, 'maxDateDistance=5')) 


This query returns all dates between 2000-01-05 and 2000-01-15. 

The fuzzy score for dates is calculated as follows: 

The identical date gets a score of 1.0. 

The date that is maxDateDistance days away from the search input gets a score that equals the fuzzySimilarity 

parameter (0.95 in the example above). 

The score of dates between the identical date and maxDateDistance is calculated as a linear function between the 

two dates defined above. In other words, for each day the score is reduced by ((1-fuzzySimilarity) / 

maxDateDistance). 

For dates outside the range of maxDateDistance, the score is 0.0. 



P U B L I C 


Therefore, for the example above we get: 

2000-01-04 -> 0.00 

2000-01-05 -> 0.95 

2000-01-06 -> 0.96 

... 

2000-01-09 -> 0.99 

2000-01-10 -> 1.0 

2000-01-11 -> 0.99 

2000-01-12 -> 0.98 

... 

2000-01-15 -> 0.95 

2000-01-16 -> 0.00 

The distance between dates is calculated following the rules of the Gregorian calendar. 

The special case 'fuzzySimilarity = 1.0' and maxDateDistance=n is allowed and returns all dates within a range of n 

days with a rank of 1.0. 

Dates That Meet Both Conditions 

If a date meets the conditions of a typo and also the conditions of the maxDateDistance parameter, two scores 

are calculated for the same date. In this case, the score() function returns the highest of both scores. This is 

shown in the following example: 


WHERE CONTAINS(dateofbirth, '2000-01-10', FUZZY(0.8, 'maxDateDistance=5')) 


This query returns the following: 

2000-01-04 -> 0.00 

2000-01-05 -> 0.80 

2000-01-06 -> 0.84 

2000-01-07 -> 0.88 

2000-01-08 -> 0.92 

2000-01-09 -> 0.96 

2000-01-10 -> 1.0 

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Enabling Search

2000-01-11 -> 0.96 

2000-01-12 -> 0.92 

2000-01-13 -> 0.90 

2000-01-14 -> 0.90 

2000-01-15 -> 0.90 

2000-01-16 -> 0.90 

Search Rules 

Overview 

With fuzzy search in SAP HANA, you can search for structured database content that is similar to the user input. 

In this case, the user input and the records in the database are nearly the same but differ in their spelling (for 

example, typing errors) or contain additional information (for example, additional or missing terms). 

Among the use cases of fuzzy search on structured data, there is the prevention of duplicate records. New 

database records can be checked for similar and already existing records in real time, just before the new record 

is saved. 

For example, before saving a new customer to the database, the application checks for similar customers that 

may be duplicates of the newly entered customer. The application does some searches and then presents to the 

user any existing customers that are similar to the user input. The user then decides whether to create a new 

customer (because the records presented are similar, but not really duplicates) or to accept one of the existing 

customers and continue with this customer record. 

The searches performed by the application are defined by business rules that define when two customers are 

similar. For example, two customers may be considered similar by the application as soon as one of the following 

conditions is true: 

1. The customers' names and addresses are similar. 

2. The customers' last names and addresses are identical but the first names are different (may be persons 

living in the same household). 

3. The customers' names are similar and the dates of birth are identical. 

These rules can be hardcoded in the application by writing three SELECT statements that do the three searches 

defined above. Whenever the requirements for the search rules change, the application code has to be changed, 

tested and deployed to the productive system. This may be costly in terms of time and development resources 

needed. 

Alternatively, the application can use search rules to store the rules as a configuration object in the SAP HANA 

database. Instead of embedding the rules in SELECT statements that are part of the application code, the 

application has to call a database procedure only to process all rules defined in the configuration object. 



P U B L I C 


When the business requirements change, only the search rule definition in the configuration object has to be 

changed, tested, and deployed. The interface to the database procedure that is called by the application stays 

unchanged. So without any change to the application code, the definition of the search rules is changed and the 

user immediately gets search results according to the new requirements. This results in much less effort and 

more flexibility when changing search rules. 

Supported Database Objects 

You can search on attribute views. The views have to be modeled using the SAP HANA studio and have to be 

stored as objects in the SAP HANA repository. 

Other database objects, such as row tables, column tables, calculation views, or analytic views, are not supported. 

Important Terms 

A search rule set is the configuration object that is stored in the SAP HANA repository and that contains the 

definition of the search rules. When the database procedure is called to do a search, a search rule set is executed. 

This means that all rules that are defined in the search rule set are executed. 

A search rule defines a condition when two records – the user input and a record in the database – are 

considered similar. Each rule in a search rule set is converted to a SELECT statement and is executed when the 

search rule set is processed. 

Creating Search Rule Sets 

You created a workspace and a project in the SAP HANA studio. In this workspace, you created a package that will 

contain your rule set. 

1. In the SAP HANA modeler, open the Project Explorer view and navigate to your package. 

2. From the context menu of your package, select New Other Search Rule Set . 

3. Enter a file name for your rule set. The file has to have the extension .searchruleset. 

4. Open and edit the search rule set in the search rule set editor. See Working with the Search Rule Set Editor 

[page 298] 

5. Define the attribute view, key columns, score selection parameter, stopwords, and term mappings. See 

Configuring Search Rule Sets [page 299] 

6. From the context menu of your package or search rule, choose Team Activate . 

You can now execute a search with the rule set. See Executing a Search With a Rule Set [page 300] 

Working with the Search Rule Set Editor 

● To open a rule set in the editor, double-click a rule set file or, from the context menu, select Open With 

Search Rule Set Editor . 

● To add new nodes, children or siblings, you can use the context menu of each node. 

For example, you can a new key column node in the following ways: 

○ Select the attribute view node and, in the context menu, choose New Key Column. 

○ Select a key column node and, in the context menu, choose New Key Column. 

● To delete a node from the search rule set, select the node and, from the context menu, select Delete. 

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Enabling Search

This deletes the node and all its child nodes. 

● To change the order of nodes or to move nodes to other parent nodes, you can drag and drop the nodes. 

With the SAP HANA studio running on Microsoft Windows, you can copy nodes below the same parent node 

or even to another parent node by pressing CTRL while dragging. 

● To change properties, click on the value of the property in the Properties view and enter the new value. 

Each node contains a set of properties that define the behavior of the search rules. Node properties are 

displayed in the Properties view of the SAP HANA studio when a node is selected in the tree. If the Properties 

view is not displayed, you can open it by choosing Window Show View Properties . 

Note: Some node properties refer to database objects or to column names. These properties are 

case-sensitive so you have to enter all names in the correct notation. 

Configuring Search Rule Sets 

● Define the attribute view. 

The search rule set searches on an attribute view that is modeled using the SAP HANA studio. The attribute 

view to be used is defined in the attribute view node of the search rule set. The name property contains the 

name of the attribute view. The FQN notation (fully qualified name) is used to specify the view. 

● Define the key columns and the score selection parameter. 

A search may return the same record more than once because it matches more than one rule. 

To enable the search to return each record only once, key columns must be defined in a way that makes 

records in the result set unique. For an attribute view, there is no definition of key columns available, so the 

key columns have to be defined for each search rule set. 

The key columns are a set of one or more columns of the attribute view that clearly identify a record in the 

view. So the key columns are similar to the primary key columns of a database table. 

As for primary keys, LOB types (BLOB, CLOB, NCLOB, TEXT) are not allowed as key columns. 

Note: It is possible to create an invalid key column definition that does not make the result set unique. 

In this case, when running a search, an error is raised when records returned by a single rule are not 

unique. 

By default, each search rule set contains one key column node below the attribute view node. If more columns 

are needed to make records unique, more key column nodes can be added below the attribute view node. 

In each key column node enter the name of the attribute view column in the properties panel. 

In addition to the key columns, you have to define how the result set shall be made unique. Records returned 

by more than one rule usually have different scores assigned. Only one combination of score and rule name 

can be returned in the result set. 

The score selection parameter defines whether the values with the highest score or the values found with the 

first matching rule are returned. 

The score selection parameter is defined in the properties panel of the rule set node. 

● Define stopwords and term mappings. 

To use stopwords and term mappings in a search rule set, the configuration options have to be added to the 

rule set. 



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First, open the context menu of the Search Rule Set node and select New Stopwords (table-based) or New 

Term Mappings (table based). 

In the properties of the new nodes, you can define the stopword table and term mapping table that is used. 

On the Stopwords (table-based) or Term Mappings (table-based) node, select New Column to enable the 

stopwords or term mappings on a column. In the properties panel, you can define the name of the column 

where stopwords and term mappings shall be applied. 

Below the Column nodes, create new List ID nodes (open the context menu and select New List ID). In each 

list ID node, you can configure a stopword or term mapping list that is applied on the column. 

The stopword and term mapping settings are valid for a given column in all rules. 

Executing a Search With a Rule Set 

HANA exports a new built-in function: SYS.EXECUTE_SEARCH_RULE_SET, with which you can execute a 

previously defined search rule set. 

The function has one parameter, which is an XML string to run the search. Within this XML, you have to specify: 

● The ruleset that should be executed 

● The way the result will be returned 

● The limitation of the result 

● The input values 

The EXECUTE_SEARCH_RULE_SET method returns by default a ResultSet object. This object contains all the 

columns from the referenced attribute view plus additional columns _SCORE and _RULE_ID. Alternatively, the 

EXECUTE_SEARCH_RULE_SET can write the result into a results table that needs to be created by the user. 

For code samples of SYS.EXECUTE_SEARCH_RULE_SET calls, see Search with a Rule Set - Code Samples [page 

300]. 

Transaction Isolation Level 

The EXECUTE_SEARCH_RULE_SET function creates one SELECT statement for each of the rules and runs the 

statements independent of each other. The statements are executed in the transaction context of the calling 

application and use the same isolation level as the application. The isolation level has an influence on the results of 

the EXECUTE_SEARCH_RULE_SET function when there are other transactions running in parallel that change the 

contents of the database tables. 

When the isolation level 'READ COMMITTED' is used, each of the SELECT statements of the search rule set sees 

all changes that have been committed at the time the execution of the SELECT statement begins. So, for example, 

the second rule of a rule set may see a new record that was not committed when the first rule has been executed. 

In this case, the new record may be returned by the 'wrong' rule and the user gets an incorrect result. 

When the isolation levels 'REPEATABLE READ' or 'SERIALIZABLE' are used, all SELECT statements see the same 

state of the database. So the results returned by EXECUTE_SEARCH_RULE_SET are always correct. 

Search with a Rule Set - Code Samples 

Executing a search and returning the result as a ResultSet: 

CALL SYS.EXECUTE_SEARCH_RULE_SET(' 

 

 

-- specifies the SearchRuleSet 

Herbert -- specifies the input value 

for column FIRSTNAME 

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Enabling Search

Hofmann -- specifies the input value 

for column LASTNAME 

 

'); 

Executing a search and writing the result to a column table provided by the user: 

--First create the result table 

set schema MY_SCHEMA; 

CREATE COLUMN TABLE MY_RESULT_TABLE ( 

_SCORE FLOAT, 

_RULE_ID VARCHAR(255), 

"FIRSTNAME" TEXT FUZZY SEARCH INDEX ON FAST PREPROCESS ON, 

"LASTNAME" TEXT FUZZY SEARCH INDEX ON FAST PREPROCESS ON 

}; 

-- Afterwards you can execute the search using the created result table. 


 

 

-- specifies the SearchRuleSet 

-- specifies the schema of 

the result table 

-- specifies the name of the 

result table 

Herbert -- specifies the input value 

for column FIRSTNAME 

Hofmann -- specifies the input value 

for column LASTNAME 

 

'); 

-- get the result 

select * from MY_RESULT_TABLE; 

Limiting the number of rows returned by a search: 

Note: When calling the system procedure EXECUTE_SEARCH_RULE_SET, the application can define the 

maximum number of rows that are returned by setting a limit parameter. By default, this parameter is 

undefined, which means that an unlimited number of rows is returned. The limitation takes place after 

each rule and in the end when all rules are performed. In the following example, a maximum number of 

100 rows will be returned. You can use this parameter with the ResultSet object and with the custom 

result table. 

-- run the search 


 

 

billy 

smith 

 

'); 



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Frequently Asked Questions 

Why are there results with a score lower than the requested fuzzySimilarity? 

In text fields, the parameter fuzzySimilarity sets the minimum similarity that a token has to match to be included 

in the search result. All other fuzzy search operations (for example, applying term mappings, considering 

stopwords, abbreviationSimilarity) can influence the score that you will see. 

How many misspellings are allowed with a particular fuzzySimilarity? 

This question is not easy to answer. The scoring algorithm is not linear to the number of misspellings; the position 

of the misspelling is also important. You can use the following example to familiarize yourself with it. 

DROP TABLE test; 

CREATE COLUMN TABLE test 

( 



); 

INSERT INTO test VALUES ('1','abc'); 

INSERT INTO test VALUES ('2','abx'); 

INSERT INTO test VALUES ('3','xbc'); 

INSERT INTO test VALUES ('4','axc'); 

INSERT INTO test VALUES ('5','abcx'); 

INSERT INTO test VALUES ('6','xabc'); 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM test 

WHERE CONTAINS(companyname, 'abc', 




1 1 abc 

0.89 5 abcx 

0.82 2 abx 

0.75 6 xabc 

0.61 3 xbc 

0.61 4 axc 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, * FROM test 

WHERE CONTAINS(companyname, 'abcx', 




1 5 abcx 

0.89 1 abc 

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0.88 6 xabc 

0.75 3 abx 

0.59 3 xbc 

0.59 4 axc 

How do I find out if the fuzzy search index is enabled for column x? 

See Basic Examples. 

How do I enable the fuzzy search index for a particular column? 

See Basic Examples. 

The additional data structures will increase the total memory footprint of the loaded table. In unfavorable cases 

the memory footprint of the column can double. 

How can I see how much memory is used for a fuzzy search index? 

See Memory Usage [page 263]. 

Is the score between request and result always stable for TEXT columns? 

It depends on how you look at the topic. The algorithm is indeed deterministic, but you need to take all parameters 

into account. Cases can be constructed where a small change in the fuzzySimilarity will change the rank between 

the same strings. 

Why is this? The fuzzySimilarity is the minimum score that tokens need to reach to be considered for the result. If 

you use andThreshold or the keyword "OR" in your search, not all tokens have to reach the fuzzySimilarity to be 

part of the result. This can lead to a change in the total score if you change the fuzzySimilarity. Let us look at an 

example: 

DROP TABLE companies; 


( 


companyname SHORTTEXT(200) 

); 

INSERT INTO companies VALUES(1, 'aktien gesellschaft'); 

INSERT INTO companies VALUES(2, 'aktiv gesellschaft'); 

Important: The similarity between "aktien" and "aktiv" is 0.77. 



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If the fuzzySimilarity is lower than 0.77, the token scoring will be part of the result score. If the fuzzySimilarity is 

higher than 0.77, the token scoring will not be considered, so the total scoring will be lower. 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, id, companyname 


WHERE CONTAINS(companyname, 'aktiv OR gesellschaft', FUZZY(0.75, 

'textSearch=compare')) 



1 2 aktiv gesellschaft 

0.89 1 aktien gesellschaft 

SELECT TO_DECIMAL(SCORE(),3,2) AS score, id, companyname 


WHERE CONTAINS(companyname, 'aktiv OR gesellschaft', FUZZY(0.80, 

'textSearch=compare')) 



1 2 aktiv gesellschaft 

0.71 1 aktien gesellschaft 

11.3 Building Search Apps 

11.3.1 Introduction to the UI Toolkit for Info Access 

The UI toolkit for SAP HANA Info Access provides UI building blocks for developing browser-based search apps on 

SAP HANA. Such applications provide real-time information access and faceted search features for huge volumes 

of structured and unstructured text data. 

The toolkit enables a freestyle search of a SAP HANA attribute view, displaying and analyzing the result set. The 

toolkit provides UI elements (widgets) such as a search box, a result list with a detailed view, and charts for basic 

analytics on the result set. The widgets are interconnected and adapt in real-time to user entries and mouse-over 

(hover) selections. 

The toolkit is based on HTML5 and JavaScript libraries such as JQuery/JQueryUI, d3 (Data Driven Documents), 

and Tempo. The widgets use the SAP HANA Info Access HTTP service. You do not need an additional layer to run 

the UI; SAP HANA and a Web browser are sufficient. The toolkit is tested on Mozilla Firefox 17. It also runs on 

Microsoft Internet Explorer 9 in standard mode and Google Chrome. 

Along with the actual toolkit (the widgets), we deliver a fully operational demo Web app built using this toolkit. The 

demo app enables you to explore a search application dealing with a set of sample data for electronic products. 

You can use the demo app as a template or for reference when you start developing your own app. 

You can, for example, use the demo site to easily connect your own data and compose your Web site. To create a 

search application this way, it is sufficient to have experience in HTML and to have read this documentation. For 

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Enabling Search

advanced customizing and layout of the site, more in-depth knowledge of CSS and the above-mentioned 

JavaScript libraries is required. 

What is the SAP HANA Info Access HTTP Service? 

In the first place, SAP HANA is a database. It stores any type of raw data in its tables: master data, transactional 

data, numbers, texts, and so on. But SAP HANA can do more than a classic database. SAP HANA also enables you 

to turn raw data into meaningful information. 

For the world of numbers, there are the analytics features of SAP HANA. By joining, aggregating, and calculating, 

they can turn raw facts and numbers into meaningful measures and key figures. 

For the world of texts, there are the full text search and text analysis features of SAP HANA. By tokenizing, 

stemming, normalizing, and analyzing semantically, they can turn a set of strings into a structured and searchable 

text corpus. 

So there is meaningful information in SAP HANA. But it is still not instantly available to business end users. SQL is 

a very powerful tool for accessing and processing SAP HANA information. However, it operates on a very 

technical level deep down in the stack and far from an end user UI. 

This is where the info access service of SAP HANA steps in. As long as you only need read-access, meaning 

search or basic analytics, the service provides shortcuts to Web and mobile UIs. 

SAP HANA Info Access Architecture 

The SAP HANA info access HTTP service wraps search and analytic SQL queries and exposes them through an 

HTTP interface. On the UI layer, Info Access offers the HTML5 development kit including UI widgets and Web site 

templates. No intermediate layer is required. To provide Info Access apps to your users, you only need SAP HANA 

and a Web browser. 

11.3.2 Installing the Service and the Toolkit 

The UI toolkit and the service are part of the default SAP HANA shipment, but they are not installed automatically. 

They are shipped as separate delivery units that you can import and activate quickly as described below. 

Importing the Delivery Units 

● SAP HANA Appliance Software, support package stack (SPS) 05 or higher, running on a server. 



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● SAP HANA studio and SAP HANA client installed on your local machine. 

1. To import the UI toolkit and the service, in the SAP HANA studio, choose the Modeler perspective and select 

your database instance. 

2. From the menu, choose File Import . 

3. Select HANA Content Delivery Unit and choose Next. 

4. Select Client and browse for the HCO_INA_UITOOLKIT.tgz delivery unit. 

The delivery units can be found on the SAP HANA host under SYS/global/hdb/content. 

5. Select both actions and choose Finish. 

6. Perform the same import procedure for the HCO_INA_SERVICE.tgz delivery unit. 

7. In the Navigator pane, under Content, check that the following packages are available: 

sap\bc\ina\uitoolkit 

sap\bc\ina\demos\epm 

sap\bc\ina\service\v2 

8. To get started developing apps using the toolkit, set up an application project. 

Related Links 

i031349364909774.ditamap 

Registering and Activating the Info Access Service 

1. To register the service, switch to the Lifecycle Management perspective of the SAP HANA studio and select 

your database instance. 

2. Choose the Configuration tab page and expand xsengine.ini\application_container. 

3. Double-click the application_list line and, under the System column, add the entry 

InformationAccess. 

Caution: Once InformationAccess is running, SAP HANA data is exposed by an HTTP service (port 

80). 

4. To restart SAP HANA XS, choose the Landscape tab page. 

5. From the context menu of the xsengine service, choose Kill... 

The service stops completely and restarts automatically. 

Importing the Demo Data 

1. Go to the SAP Code Exchange Web page of the UI toolkit. 

2. From the Documents tab page, download the epm_data.zip archive. 

3. Follow the instructions in the readme.txt file contained in the archive. 

Related Links 

SAP Code Exchange Web page of the UI toolkit 

11.3.3 Getting to Know the Demo App 

You can now explore what an app built using the UI toolkit looks and feels like. Start the sample UI in a Web 

browser by opening the following URL: 

http://:80/sap/bc/ina/demos/epm/search.html 

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Enabling Search

Example: http://hana1.acme.corp:8001/sap/bc/ina/demos/epm/search.html 

Start exploring the UI. 

The demo app consists of a header row, a column on the left, and a large content area on the right. The column on 

the left contains some widgets; the search box and some charts. The charts are used for displaying the count of 

result items with distinct values. In the EPM example, it is the count of sold products by category and by currency. 

The content area on the right is for displaying an enlarged view of one of the widgets, the result list is enlarged at 

page load. 

The app starts with a search for all. By typing in the search box or filtering in the charts, you can refine the result 

set. The results are displayed in the list ranked by relevancy. 

From the right margin of the page, you can pull in the facet repository containing all configured facets that are not 

displayed in the column and the content pane. Facets are the widgets, such as the results list and charts, that 

display the dimensions of the result set. 

You can drag and drop all facets to any position on the UI, be it the column, the content area or the facet 

repository. When a chart is enlarged in the content pane, you can change the chart type with a click. 

11.3.4 Getting to Know the Demo HTML 

The structure and content of the UI are defined in the search.html file. Open the search.html file using the 

HTML editor. Familiarize yourself with the structure of the HTML. 

Partly collapsed, search.html looks like this: 



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In the head area and at the end of the HTML, there is meta data and references to the various JavaScript libraries 

and CSS used by the UI. 

The body of the HTML contains the UI's header bar with the title text and the alert bar for displaying 

messages. The rest of the body is the workarea. A workarea connects to a SAP HANA attribute view and 

serves as a container for all other widgets on the page. The workarea is divided into the facetPane, the 

contentPane, and the facetrepository. 

The facetPane starts with the searchbox followed by a facetcolumn and the facetpane. The 

workareaitem widgets inside the column and the pane are only placeholders for facets of the repository that 

the user can shuffle around at runtime. 

Inside the facetrepository, there are the actual workareaitem widgets. For switching between different 

chart types, there are the switchbox widgets. The last widget in the repository is the resultlist. 

11.3.5 Preparing Your Source Data 

Before you start to build your information access application, you need to have a clear understanding of who will 

use it and for what purpose. Once you are sure which content you need to enable for access, prepare this data as 

described here. Then you define how the content is to be displayed and which interactive navigation attributes are 

to be provided. 

Ensuring Full Text Indexing 

Make sure that a full-text index is created for each of your table columns that contains human-readable text data 

that is suitable for a freestyle search. The index structure is attached to the column and is leveraged to identify 

texts that contain the search terms. The full text index is automatically updated when new records are entered in 

the table. 

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Enabling Search

Along with the full text index, you can also trigger a text analysis that extracts entities, such as dates or people, 

from the text and, therefore, enriches the set of attributes. 

Related Links 





Text Analysis [page 238] 

Checking the Settings in SAP HANA Studio 

Technical search in SAP HANA may not be enabled. To check if it is enabled, proceed as follows: 

1. In the SAP HANA studio menu, choose Window Preferences Modeler Search Options . 

2. Check if the Enable Search Attributes option is selected. If not, select it and choose Apply and OK. 

Note: You must make this setting in every SAP HANA studio that you use to model views for search. 

Modeling Your Search Content 

For each app user, you have created a named database user with the following authorizations: 

● Object privileges: SELECT on database schemas and . 

● Analytic privileges: For and for the attribute view you want to visualize in the app. 

In the SAP HANA modeler, create an attribute view of type standard using the tables that you want to enable for 

the search. Create joins and add the attributes you want to use for searching and displaying. 

Note: You can also join additional attributes derived from the text analysis. 

To enable certain attributes for the search, proceed as follows: 

1. In the Output view, select the attributes. 

Note: The searchable attributes must not be calculated attributes nor have lower case letters in their 

names. 

2. In the lower area of the Properties tab, select the Information Access category. 

3. Set the Freestyle Search property to true. 

In the Information Access category, you can make additional search-specific settings. 

The Weights for Ranking setting (between 0.0 and 1.0, default 0.5) influences the ranking of items in the results 

list. The higher the weight of the attribute, the higher up in the list an item with a hit in this attribute is positioned. 

The Fuzziness Threshold setting (between 0.0 and 1.0, default 0.8) defines the grade of error tolerance for a 

search on this attribute. The higher the threshold, the more exact the search terms must hit the text to produce a 

result. 

Note: Do not forget to activate the attribute view. 



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Related Links 

SAP HANA Modeling Views 

FUZZY Search [page 252] 

Fuzzy Search is a fast and fault-tolerant search feature for SAP HANA. A fuzzy search returns records even if 

the search term contains additional or missing characters or other types of spelling errors. 

11.3.6 Connecting Your Source Data 

You can connect any search-enabled SAP HANA attribute view to the app by referencing the view and its 

attributes directly in your HTML file. 

To reference the attribute view and its schema in the HTML, enter their names in the workarea widget: 

 

data-entityset is the view name. data-schema is the database schema (catalog) in which the activated 

attribute view resides. The data-aggregationdimension is used as basis for counting items with distinct 

values. Enter an attribute that has unique values, for example, the primary key. 

For chart facets that display the aggregates of attribute values, for example the grouped bar chart, enter the 

attribute names here: 

 

In the grouped bar chart example, data-dimension-line is the attribute whose distinct value count is to be 

displayed as the bars. The data-dimension-x attribute is displayed as an additional dimension inside the 

chart as a group of bars. data-dimension-y is the measurement that is displayed on the y-axis defining the 

height of the single bars. In the search app, the only measurement available is the distinct values count ($count) 

of the attribute defined in data-dimension-line. 

In a simple bar or pie chart, the data-dimension parameter contains the attribute whose distinct value count 

is to be displayed 

To define the attributes to be displayed in a result list entry, enter the attribute names here: 

11.3.7 Defining the Page Layout 

Now that your source data is prepared and connected, you can form your UI using the search.html template. 

You may want to start by arranging the available widgets on your site. To place the column, the panes, and the 

facets within them, copy, move, or remove the corresponding HTML blocks. 

First, place the facet pane and its column(s) as well as the content pane. The panes and the columns inside are 

displayed from left to right on the UI in the same order as in the HTML. Only one content pane is allowed. 

Typically, a maximum of three facet columns are used. The facet repository is always last in the HTML. 

The search box and the facets inside the facet columns are next. The search box can span the entire pane across 

multiple columns. Place as many placeholder work area items as you want to have slots in a column. Inside the 

content pane, only one placeholder is allowed. Make sure that the data-target-position count is 

continuously set across the facet columns and the content pane. 

The facet repository holds the actual facets, meaning the chart switch boxes and the result list. The datasource-position 

parameter defines their position inside the facet repository as well as inside the columns 

and the content pane at page load. 

If the source position equals the target position, the respective facet replaces the placeholder in the columns and 

pane. If there are two or more facets with the same source position number, only the first one in the HTML 

replaces the placeholder. In the facet repository, all defined facets are available in the order of the source position 

or their appearance in the HTML. At runtime, the user can drag and drop the facets. 

At least one facet pane and content pane are required for the facet repository and free drag-and-drop. However, 

you could also build a minimal static UI with a workarea containing just a search box and a result list, for example. 

You can even integrate single widgets into other sites. 

Related Links 

workareaitem [page 312] 

11.3.8 Configuring the Widgets 

The widgets are based on jQuery UI. In the HTML, you can customize the single widgets to a certain degree using 

parameters. The common parameter data-sap-widget defines the type of the widget. 

Each widget type has its own set of parameters. The widgets and their parameters are listed in the order of 

appearance in the demo HTML file. 

header 

Parameter Name Default Value Description 

data-title none Title text in the header bar of the UI. 

data-helphref none Reference to the documentation for the users of your application. 

workarea 

Parameter Name Default 

Value 

Description 

data-title none This title is not displayed on the UI. 

data-packagename none Name of the database package in which the attribute view was created. 



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Parameter Name Default 

Value 

Description 

data-entityset none Name of the attribute view. 

data-schema _SYS_BIC Name of the database schema (catalog) in which the activated attribute 

view resides. The schema _SYS_BIC is default because your activated 

dataaggregationdimen 

sion 

dataaggregationsorto 

rder 

Related Links 

Connecting Your Source Data [page 310] 

searchbox 

attribute views usually end up in this schema. 

none Primary key attribute of the items you want to search and display. The 

unique key is used to identify items for the result list and to count items 

with distinct values for the charts. 

DESC Descending or ascending (ASC) order for sorting the counts in the 


charts. This setting is inherited by all charts if you do not set a sort order 

there. 

data-maxinputlength 255 Maximum number of characters that users can enter in the 

search box. 

workareaitem 


data-title none This title is displayed on the UI as the facet headline. If the 

workareaitem is a placeholder, the title is used as 

alternative text. The alternative is displayed if the 

placeholder is not replaced by an actual workareaitem 

at runtime. 

data-target-position 0 Position of a placeholder workareaitem on the UI in the 

facet or content pane. The count starts on the upper left of 

the UI. 

data-source-position 0 Position of the actual workareaitem on the UI in the 

facetrepository 


data-children-draghandle 

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facet repository on the right. On page load, the 

workareaitem placeholders are replaced by the actual 

workarea items whose source positions match the target 

positions. 

body Defines the area where a user can grab a facet for drag and drop. 

body means the complete facet, header means the facet's 

header bar only. 


Enabling Search

switchbox 


data-activeindex 0 Defines which chart contained in the switchbox is displayed on page 

load. 0 means the first one, 1 the second, and so on. 

chart 


data-toplarge none Defines how many bars or pie segments are displayed when the 

chart is enlarged. 

data-dimension none Attribute whose distinct value count is to be displayed in a 

simple bar or pie chart. 

data-charttype none Type of the chart (bar, pie, groupbar, or line). 

data-color none Color of the chart as hex triplet, for example #FFFFFF for 

white, or as standard HTML names, for example blue or 

black. 

data-dimension-line none Attribute whose distinct value count is to be displayed in 

grouped bar or line chart. 

data-dimension-x none Attribute that is displayed as additional dimension inside the 

chart as group of bars or different lines. 

data-dimension-y none Measurement that is displayed on the y-axis. In a search 

scenario, the only measurement available is the distinct value 

count ($count) of the attribute defined in data- 

dataaggregationsortorde 

r 

dimension-line. 

ASC Descending (DESC) or ascending order for sorting the counts 

in the charts. Here you can override the sort order defined 

centrally in the workarea widget. 

data-topsmall none Defines how many bars or pie segments are displayed when the 

chart is small. 

dataanimationduration 

Related Links 


inaresultlist 

1000 Duration of the animation, in milliseconds, when a chart adapts 

(default 1000). 0 means that animation is switched off. 


data-maxresultslarge 10 Maximum number of result items displayed on one 

page if the list is enlarged in the content pane. 

data-maxresultssmall 5 Maximum number of result items displayed on one 

page if the list is small in the facet column. 



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data-responseattributes none Attributes to be displayed in a result list entry. The 

actual scope and layout of the response attributes on 

the result list and details pane are defined in the files 

referenced in the data-resulttemplate 

parameters. 

Note: 

Do not leave the dataresponseattributes 

parameter empty. 

Only use attributes from the main table of the 

view or attributes that are joined in 1:1 from 

other tables. 

Attributes with data type blob are not 

supported by the HTTP service. 

data-detailwidth 600 Width of the details pop-up in pixels. 

data-detailheight 800 Height of the details pop-up in pixels. 

data-resulttemplate none Reference to HTML and CSS files defining the layouts 

data-resulttemplate-css none 

of the result lists (small and large) and of the details 

pop-up. 

data-resulttemplate-small none 

data-resulttemplatesmall-css 

data-resulttemplatedetail 

data-resulttemplatedetail-css 

none 

none 

none 

data-scoresortorder DESC By default, the result list is sorted according to the 

ranking by relevancy for the search term(s). Leave the 

default sort order unchanged. 

data-orderby none Attribute by whose values the list is sorted 

alphabetically. First choice for sorting is always the 

ranking by relevancy for the search term(s). The 

data-orderby setting only steps in if there is no 

relevancy ranking available, for example before the 

first search, or if there are equal ranking values. 

data-sortorder ASC Ascending or descending (DESC) order for the dataorderby 

parameter. 

Related Links 


Defining the Layout of Result Lists and Details [page 315] 

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Enabling Search

11.3.9 Defining the Layout of Result Lists and Details 

You can select which attributes are displayed and how they are displayed in the result lists (small or centered) and 

on the details pop-up. In the search HTML file, the result templates are referenced in the inaresultlist 

widget using the data-resulttemplate parameters. 

The templates folder contains the HTML and CSS templates of the demo app for adapting. You can create your 

own result layouts from the templates and reference them in the parameters. Make sure that the path is correct. 

In the HTML templates, you define what is in a result entry in the different views. You can enter fixed text and 

reference the response properties and values in double braces. 

For a deeper understanding of these HTML templates, familiarize yourself with the Tempo JSON rendering 

engine. 

Note: If you want to integrate graphics in result list templates, define the exact width and height in pixels. 

Use the corresponding CSS files to define the result layouts and the behavior on hover events. To tweak the layout 

of the details screen further, you can also use the widgets provided by jQuery UI. 



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12 Setting Up Roles and 

Authorizations 

12.1 The Authorization Model 

Authorization mechanisms ensure that authenticated users can do only those things they are allowed to do. You 

can use the authorization mechanisms of the SAP HANA database to specify who is allowed to access which data 

and for which activities. 

Authorization mechanisms can also be used to help control who is allowed to execute stored procedures and 

functions or execute system-level activities, for example: making backups, creating schema, users, roles, and so 

on. 

Authorizations are specified by granting privileges to principals. Principals are either users or roles. Roles 

represent collections of privileges that can be granted to users or other roles, which enables you to create a 

hierarchy of roles. Privileges are granted to principals by users. 

SAP HANA database authorization mechanisms use the following privileges: 

● System privileges 

Perform system-level operations or administrative tasks 

● Object privileges 

Perform specified actions on specified database objects 

● Analytic privileges 

Allow selective access control for database views generated when modeled are activated 

● Package Privileges 

Allow operations on packages, for example, creation and maintenance. Privileges can differ for native and 

imported packages. 

Other types of privileges enable you to provide specific additional authorizations, for example, to users who need 

to perform administrative tasks on objects in the repository or to users and clients that need access to 

applications: 

● Repository Privileges 

Enable users to perform basic repository operations, for example: import and export packages, and maintain 

delivery units (DU) 

● Application Privileges 

316 

Enable users and clients to access an application, configure what data to expose, and set rules for exposing 

URLs. 

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Setting Up Roles and Authorizations

12.2 Authentication Overview 

Authentication is the process used to validate the identity of the users who connect to SAP HANA. 

Secure authentication mechanisms ensure that the users requesting a connection really are who they claim to be. 

Note: For connections to SAP HANA it is important to distinguish between SQL- and HTTP-based 

connections. 

For SQL access to SAP HANA by means of client interfaces, for example, JDBC or ODBC, the following 

authentication methods are supported: 

● External authentication: 

○ Kerberos services 

A standardized service for client authentication in networks. The client connects to the Kerberos server to 

authenticate the user and to acquire an authentication ticket that proves the user’s identity to the SAP 

HANA database. The client uses the ticket to connect to the SAP HANA database. Kerberos also ensures 

the correct identity of the server. 

○ SAML (bearer token) 

SAP HANA can authenticate users who provide a valid standard-based SAML assertion issued by a 

trusted identity provider. 

● Internal authentication 

Users are authenticated by the SAP HANA database using the database user name and password. 

SAP HANA maps the external identity approved by external authentication service to the identity of an internal 

database user. This internal database user is then used for authorization checks during the database session. 

For HTTP access to SAP HANA by means of SAP HANA XS, the following authentication methods are supported: 

● User name and password: 

○ Using HTTP basic authentication 

○ Form-based authentication 

● SAP logon tickets 

12.3 Roles 

Roles contain privileges that are used to define which data, application, or function can be accessed and in which 

manner consumed. Roles are assigned either to users or to other roles at runtime. 

SAP delivers some generic roles with SAP HANA that can be used as they are or as templates (during design time) 

for creating roles that meet your company's specific requirements. More information about roles, their use at 

runtime and in design time are explained in the subsequent sections. 

● Roles 

● Roles as Repository Objects 

● Creating Roles in the Repository 


Setting Up Roles and Authorizations 

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12.3.1 Roles 

A role is a collection of privileges that can be granted to either a user or another role in runtime. 

A role typically contains the privileges required for a particular function or task, for example: 

● Business end users reading reports using client tools such as Microsoft Excel 

● Modelers creating models and reports in the modeler of the SAP HANA studio 

● Database administrators operating and maintaining the database and users in the Administration editor of the 

SAP HANA studio 

Privileges can be granted directly to users of the SAP HANA database. However, roles are the standard 

mechanism of granting privileges as they allow you to implement complex, reusable hierarchies of user access 

that can be modeled on business roles. Several standard roles are delivered with the SAP HANA database (for 

example, MODELING, MONITORING). You can use these as templates for creating your own roles. 

Roles in the SAP HANA database can exist as runtime objects only, or as design-time objects that become 

runtime objects on activation. 

Role Structure 

A role can contain any number of the following privileges: 

● System privileges for administrative tasks (for example, AUDIT ADMIN, BACKUP ADMIN, CATALOG READ) 

● Object privileges on database objects (for example, SELECT, INSERT, UPDATE) 

● Package privileges on repository packages (for example, REPO.READ, REPO.EDIT_NATIVE_OBJECTS, 

REPO.ACTIVATE_NATIVE_OBJECTS) 

● Analytic privileges on SAP HANA information models 

● Application privileges for enabling access to SAP HANA XS applications 

Note: Application privileges cannot be granted to roles in the SAP HANA studio. 

A role can also extend other roles. 

Role Modeling 

You can model roles in the following ways: 

● As runtime objects on the basis of SQL statements 

● As design-time objects in the repository of the SAP HANA database 

It is recommended that you model roles as design-time objects for the following reasons. 

Firstly, unlike roles created in runtime, roles created as design-time objects can be transported between systems. 

This is important for application development as it means that developers can model roles as part of their 

application's security concept and then ship these roles or role templates with the application. Being able to 

transport roles is also advantageous for modelers implementing complex access control on analytic content. They 

can model roles in a test system and then transport them into a productive system. This avoids unnecessary 

duplication of effort. 

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Secondly, roles created as design-time objects are not directly associated with a database user. They are created 

by the technical user _SYS_REPO and granted through the execution of stored procedures. Any user with access 

to these procedures can grant and revoke a role. Roles created in runtime are granted directly by the database 

user and can only be revoked by the same user. Additionally, if the database user is deleted, all roles that he or she 

granted are revoked. As database users correspond to real people, this could impact the implementation of your 

authorization concept, for example, if an employee leaves the organization or is on vacation. 

Caution: The design-time version of a role in the repository and its activated runtime version should 

always contain the same privileges. In particular, additional privileges should not be granted to the 

activated runtime version of a role created in the repository. Although there is no mechanism of 

preventing a user from doing this, the next time the role is activated in the repository, any changes made 

to the role in runtime will be reverted. It is therefore important that the activated runtime version of a role 

is not changed in runtime. 

12.3.2 Roles as Repository Objects 

The repository of the SAP HANA database consists of packages that contain design-time versions of various 

objects. Being a repository object has several implications for a role. 

Grantable Privileges 

According to the authorization concept of the SAP HANA database, a user can only grant a privilege to a user 

directly or indirectly in a role if the following prerequisites are met: 

● The user has the privilege him- or herself 

● The user is authorized to grant the privilege to others (WITH ADMIN OPTION or WITH GRANT OPTION) 

A user is also authorized to grant SQL object privileges on objects that he or she owns. 

The technical user _SYS_REPO is the owner of all objects in the repository, as well as the runtime objects that are 

created on activation. This means that when you create a role as a repository object, you can grant the following 

privileges: 

● Privileges that have been granted to the technical user _SYS_REPO and that _SYS_REPO can grant further. 

This is automatically the case for system privileges, package privileges, analytic privileges, and application 

privileges. Therefore, all system privileges, package privileges, analytic privileges, and application privileges 

can always be granted in modeled roles. 

● Privileges on objects that _SYS_REPO owns. 

_SYS_REPO owns all activated objects. Object privileges on non-activated runtime objects must be explicitly 

granted to _SYS_REPO. It is recommended that you use a technical user to do this to ensure that privileges 

are not dropped when the granting user is dropped (for example, because she leaves the company. 

The following table summarizes the situation described above: 

Privilege Action Necessary to Grant in Repository Role 

System privilege None 



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Privilege Action Necessary to Grant in Repository Role 

Package privilege None 

Analytic privilege None 

Application privilege None 

SQL object on activated object (for example, attribute 

view, analytic view) 

SQL object privilege on runtime object (for example, 

replicated table) 

Granting and Revoking 

None 

Grant privilege to user _SYS_REPO with WITH GRANT 

OPTION 

It is not possible to grant and revoke activated design-time roles using the GRANT and REVOKE SQL statements. 

Instead, roles are granted and revoked through the execution of the procedures GRANT_ACTIVATED_ROLE and 

REVOKE_ACTIVATED_ROLE. Therefore, to be able to grant or revoke a role, a user must have the SQL object 

privilege EXECUTE on these procedures. 

WITH ADMIN OPTION and WITH GRANT OPTION 

When you create a role on the basis of SQL statements (that is, as a runtime object), you can grant privileges with 

the additional parameters WITH ADMIN OPTION or WITH GRANT OPTION. This allows a user who is granted the 

role to grant the privileges contained within the role to other users and roles. However, if you are implementing 

your authorization concept with privileges encapsulated within roles created in design time, then you do not want 

users to grant privileges using SQL statements. Therefore, it is not possible to pass the parameters WITH ADMIN 

OPTION or WITH GRANT OPTION with privileges when you model roles as repository objects. 

Similarly, when you grant an activated role to a user, it is not possible to allow the user to grant the role further 

(WITH ADMIN OPTION is not available). 

Auditability 

The auditing feature of the SAP HANA database allows you to monitor and record selected actions performed in 

your database system. One action that is typically audited is changes to user authorization. If you are using roles 

created in the repository to grant privileges to users, then it is important to note that the creation of runtime roles 

through activation cannot be meaningfully audited. 

12.3.3 Creating Roles in the Repository 

You model roles in the SAP HANA repository in a domain-specific language (DSL). 

● A shared project must exist with a suitable package for storing roles. 

● You have the package and system privileges required for modeling and activating objects in the repository. 

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Caution: Theoretically, a user with authorization to model and activate repository objects can change 

a role that he has been granted. Once the role is activated, the user has the new privileges that he or 

she just added. Therefore, it is important that roles in productive systems are imported from a test or 

development system and changes to imported objects are not allowed. This danger is however not 

specific to roles but also applies to other repository objects, for example, modeled views. 

● You have granted privileges on non-activated runtime objects that you want to grant in the new role to the 

technical user _SYS_REPO. 

The following general conventions apply when modeling a role definition using the role DSL: 

● Comments start with a double-slash (//) or double-dash (--) and run to the end of the line. 

● When specifying a reference to a design-time object, you must always specify the package name as follows: 

○ package::object if you are referencing a design-time role 

○ package:object.extension if you are referencing any other design-time object 

● When specifying multiple privileges on the same object or the same privilege on multiple objects, you can do 

so individually line by line, or you can group them on a single line. Separate multiple objects and/or multiple 

privileges using a comma. 

1. From the main menu in the SAP HANA studio, choose File New Other SAP HANA Repository Role 

. 

The New Role dialog box appears. 

2. In the Container field, enter the path to the package where you want to create the role. 

3. In the Role name field, enter the name of the new role. 


The new role appears in the Project Explorer view and opens in the role editor as follows: 

// an empty role 

role :: { 

} 

The role is now ready to be defined. 

5. Optional: Specify the role(s) that you want to embed within the new role. 

You can specify both roles created in runtime and repository roles as follows: 

○ extends role :: 

○ extends catalog role "role_name" 

Example: 

role :: 

extends role sap.example::role1 

extends catalog role "CATROLE2" 

{ 

} 

6. Model the required privileges. 



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322 

Note: Unlike when you create a role using SQL statements, it is not possible to grant ALL 

PRIVILEGES when creating a role in the repository. You must model every privilege individually. 

a) Model system privileges using the keyword "system privilege" as follows: system privilege: 

PRIVILEGE; 

Example: 

role :: 

{ 

// multiple privileges in one line are OK 

system privilege: BACKUP ADMIN, USER ADMIN; 

} 

// you can also split lists into multiple entries 

system privilege: LICENSE ADMIN; 

b) Optional: Model object privileges on the design-time objects views and procedures using the keyword 

"SQL object" as follows: sql object :.extension: PRIVILEGE; 

Example: 

role :: 

{ 

sql object sap.example:MY_VIEW.attributeview: DROP; 

// object privileges can be split across lines 


// a single privilege can be given on multiple objects in a 

single line 

sql object sap.example:MY_VIEW.attributeview, 

sap.example:MY_OTHER_VIEW.analyticview, 

sap.example:MY_THIRD_VIEW.analyticview: SELECT; 

} 

c) Optional: Model object privileges on catalog objects using the keyword "catalog SQL object" as follows: 

catalog sql object "SCHEMA"."CATALOG_OBJECT": PRIVILEGE; 

Example: 

Note: You must always qualify catalog objects with the schema name. You must also reference 

catalog objects within double quotes, unlike design-time objects. 

role :: 

{ 

// catalog objects must always be qualified with the schema name 

catalog sql object "MY_SCHEMA"."MY_VIEW": SELECT; 

} 

d) Optional: Model schema privileges on schemas using the keywords "catalog schema" or "schema" as 

follows depending on whether you are referring to an activated schema or a schema in the repository: 

○ catalog schema "SCHEMA": PRIVILEGE; 

○ schema :.schema: PRIVILEGE; 

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Example: 

role :: 

{ 

catalog schema "MY_SCHEMA": SELECT; 

schema sap.example:MY_OTHER_SCHEMA.schema: SELECT; 

} 

e) Optional: Model package privileges using the keywords "package" as follows: package PACKAGE: 

PRIVILEGE; 

Example: 

role :: 

{ 

package sap.example: REPO.READ; 

} 

f) Optional: Model analytic privileges using the keywords "analytic privilege" or "catalog analytic privilege" 

depending on whether you are referring to an activated analytic privilege or a runtime analytic privilege 

○ analytic privilege: :.analyticprivilege 

○ catalog analytic privilege: "analytic_priv_name"; 

Example: 

role :: 

{ 

analytic privilege: sap.example:sp1.analyticprivilege, 

sap.example:AP2.analyticprivilege; 

catalog analytic privilege: "sp3"; 

} 

g) Optional: Model application privileges using the keyword "application privilege" as follows: 

application privilege: ; 

Example: 

role :: 

{ 

application privilege: sap.example::Execute; 

} 

Note: Application privileges are implemented using the application-privileges file 

(.xsprivileges). 

7. From the main menu, choose File Save . 

The role is saved as an .hdbrole file. After it has been saved, the file is committed to the repository 

8. Activate the role by right-clicking it in the Project Explorer view and choosing Team Activate . 

Note: Any changes made to a previously activated version of the role in runtime will be reverted on 

activation. This is to ensure that the design-time version of a role in the repository and its activated 

runtime version contain the same privileges. It is therefore important that the activated runtime 

version of a role is not changed in runtime. 



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The activated role is now visible in the Navigator view under Security Roles following the naming convention 

package::role_name and can be granted to users as part of user provisioning. 

Complete Role Definition Example 

role :: 

extends role sap.example::role1 

extends catalog role "CATROLE1", "CATROLE2" 

{ 

// system privileges 

system privilege: BACKUP ADMIN, USER ADMIN; 

// schema privileges 

catalog schema "SYSTEM": SELECT; 

schema sap.example:app1.schema: INSERT, UPDATE, DELETE; 

// sql object privileges 

// privileges on the same object may be split up in several lines 

catalog sql object "SYSTEM"."TABLE2": SELECT; 

catalog sql object "SYSTEM"."TABLE2": INSERT, UPDATE, DELETE; 

// or a list of objects may get a list of privileges (object = 

table, view, procedure, sequence) 

// SELECT, DROP for all objects in list 

sql object sap.example:VIEW1.attributeview, 

sap.example:PROC1.procedure, sap.example:SEQ1.sequence: SELECT, DROP; 

// additional INSERT, UPDATE for TABLE1 


// analytic privileges 

analytic privilege: sap.example:sp1.analyticprivilege, 

sap.example:AP2.analyticprivilege; 

catalog analytic privilege: "sp3"; 

} 

Related Links 

// design time privileges 

package sap.example: REPO.EDIT_NATIVE_OBJECTS; 

package sap.example, sap.co: REPO.READ; 

application privilege: sap.example::Execute, sap.example::Save; 






The Application-Privileges File [page 59] 

In SAP HANA Extended Application Services (SAP HANA XS), the application-privileges (.xssprivileges) 

file can be used to create or define the authorization privileges required for access to an SAP HANA XS 

application, for example, to start the application or to perform administrative actions on an application. These 

privileges can be checked by an application at runtime. 


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12.4 Privileges 

SAP HANA offers various privileges that can be assigned to users. Users can be a system, an application, a 

service, or a person, and each user is assigned specific roles. Privileges can be assigned to users, roles, or both. 

There are several privileges that are required either by the SAP HANA studio or by development tools, such as 

SQL. The following types of privileges are explained in the subsequent sections. 

● System privileges 

● Object privileges 

● Package privileges 

● Analytic privileges 

This section also contains information for creating and granting privileges to users. 

12.4.1 System Privileges 

System privileges are required to perform system-level operations or administrative tasks. 

The following lists shows some of the most common system-level tasks that administrators regularly must 

perform: 

● Database schema 

Creation and deletion of database schema 

● Users/Roles 

Maintenance and management of users and roles 

● Monitor/Trace 

Administration of monitoring and tracing 

● Backup/Restore 

Performance of backup and restore operations 

In the SAP HANA database the user SYSTEM has all system privileges. The SYSTEM user can grant system 

privileges to other users and roles. 

12.4.2 Object Privileges 

Object privileges enable users to perform specified actions on specified database objects. 

Object privileges are not specific to the SAP HANA database; they are part of the SQL standard. You can use the 

SQL statements GRANT and REVOKE to manage privileges. 

Note: . If object privileges (or any other privilege type) are granted to roles created in the repository, 

granting and revoking actions happen through the execution of stored procedures. 

The set of actions that can be allowed by an object privilege depends on the object type. For tables, you can use 

actions such as: drop, alter, select, insert and update. An execute action is available for privileges for procedures 

and functions. Privileges on a schema level are used to enable actions such as: create objects, perform select, 

update, delete or execute operations on all objects contained in the schema. 

In the SAP HANA database object privileges are not only available for database catalog objects such as tables, 

views and procedures. Object privileges can also be granted for non-catalog objects such as development objects 

in the repository of the SAP HANA database. 



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Some database objects depend on other objects. Views, for example, are defined as queries on other tables and 

views. The authorization for an operation on the dependent object (the queried tables and views) requires 

privileges for the dependent object and the underlying object. In case of views, the SAP HANA database 

implements the standard SQL behavior. A user has the authorization for an operation on a view if the following is 

true: 

● The privilege for operations on the view has been granted to the user or a role assigned to the user. 

● The owner of the view has the corresponding privileges on the underlying objects with the option to grant 

them to others. 

This behavior can be used to grant selective access to a table. 

12.4.3 Package Privileges 

In the SAP HANA repository, authorizations can be assigned to individual packages. 

Authorizations assigned to a repository package are implicitly assigned to the design-time objects in the package 

as well as to all sub-packages. Users are only allowed to maintain objects in a repository package if they have the 

necessary privileges for the package in which they want to perform an operation, for example to read or write to 

an object in that package. 

Note: Package authorizations can be set for a specific user or for a role. 

If the user-authorization check establishes that a user does not have the necessary privileges to perform the 

requested operation in a specific package, the authorization check is repeated on the parent package and 

recursively up the package hierarchy to the root level of the repository. If the user does not have the necessary 

privileges for any of the packages in the hierarchy chain, the authorization check fails and the user is not 

permitted to perform the requested operation. 

In the context of repository authorizations, there is a distinction to be made between native packages and 

imported packages. 

● Native Package 

A package that is created in the current system and expected to be edited in the current system. Changes to 

package objects must be performed in the original development system where they were created and 

transported into subsequent systems. The content of native packages are regularly edited by developers. 

● Imported Package 

A package that is created in a remote system and imported into the current system. Imported packages 

should not usually be modified, except when replaced by new imports during an update. Otherwise, imported 

packages should only be modified in exceptional cases, for example, to carry out emergency repairs. 

To perform every-day, package-related, application-development tasks in the repository, developers typically 

need the following privileges for the application packages: 

● REPO.READ 


● REPO.EDIT_NATIVE_OBJECTS 


● REPO.ACTIVATE_NATIVE_OBJECTS 


working in 

● REPO.MAINTAIN_NATIVE_PACKAGES 

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SAP HANA Repository Privileges 

In addition to the authorizations you can grant users for specific packages (and the design-time objects in those 

packages), you can also assign general system privileges to users to enable them to perform basic repository 

operations, for example: importing and exporting content, and maintaining delivery units (DU). 

If your daily tasks include general administration tasks, you need basic system-level privileges in the repository. 

To perform basic administration tasks in the repository, you typically need the following privileges: 

● REPO.EXPORT 

Enables you to export delivery units; exporting a DU transports it to another system 

● REPO.IMPORT 

Enables you to import delivery units; importing a DU transports it from another system 

● REPO.MAINTAIN_DELIVERY_UNITS 

Enables you to maintain your own delivery units (the DU-vendor must equal the system-vendor) 

● REPO.WORK_IN_FOREIGN_WORKSPACE 

Enables you to move objects from a "foreign" inactive workspace into your own workspace 

You can grant or revoke basic, repository privileges to users in the following ways: 

● SAP HANA Studio 

The System Privileges tab page in the Modeler perspective: Catalog -> Authorization -> Roles or Users 

Note: If you want to access the repository from the SAP HANA studio, Eclipse, or other clients,you need 

the EXECUTE privilege for SYS.REPOSITORY_REST, the database procedure through which the REST 

API is tunneled. 

Defining Repository Package Privileges 

In the SAP HANA repository, you can set package authorizations for a specific user or for a role. Authorizations 

that are assigned to a repository package are implicitly assigned to all sub-packages, too. You can also specify if 

the assigned user authorizations can be passed on to other users. 

To set user (or role) authorizations for repository packages, perform the following steps: 

1. In the SAP HANA studio, open the Navigator view of the Modeler perspective. 

2. In the Navigator view, expand the Security Roles/Users node for the system hosting the repository that 

contains the packages you want to grant access to. 

You can also define roles via source files; roles defined in this way can be assigned to a delivery unit and 

transported to other systems. 

3. Double click the user (or role) to whom you want to assign authorizations. 

4. Open the Package Privileges tab page. 

5. Choose [+] to add one or more packages. Press and hold the Ctrl key to select multiple packages. 

6. In the Select Repository Package dialog, use all or part of the package name to locate the repository package 

that you want to authorize access to. 

7. Select one or more repository packages that you want to authorize access to; the selected packages appear 

in the Package Privileges tab page. 



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8. Select the packages to which you want authorize access and, in the Privileges for screen page, check the 

required privileges, for example: 

a) REPO.READ 


b) REPO.EDIT_NATIVE_OBJECTS 


c) REPO.ACTIVATE_NATIVE_OBJECTS 


working in 

d) REPO.MAINTAIN_NATIVE_PACKAGES 



12.4.4 Analytic Privileges 

SQL privileges impose coarse-grained restrictions at object level only. Users either have access to an object, such 

as a table, view or procedure, or they do not. While this is often sufficient, there are cases when access to data in 

an object depends on certain values or combinations of values. Analytic privileges are used in the SAP HANA 

database to provide such fine-grained control of which data individual users can see within the same view. 

Note: Sales data for all regions are contained within one analytic view. However, regional sales managers 

should only see the data for their region. In this case, an analytic privilege could be modeled so that they 

can all query the view, but only the data that each user is authorized to see is returned. 

Analytic privileges are intended to control access to SAP HANA information models, that is: 

● Attribute views 

● Analytic views 

● Calculation views 

Therefore, all column views modeled and activated in the SAP HANA modeler automatically enforce an 

authorization check based on analytic privileges. Column views created using SQL must be explicitly registered 

for such a check (by passing the parameter REGISTERVIEWFORAPCHECK). 

Note: Analytic privileges do not apply to database tables or views modeled on row-store tables. Access to 

database tables and row views is controlled entirely by SQL object privileges. 

You create and manage analytic privileges in the SAP HANA modeler. 

Note: Some advanced features of analytic privileges, namely dynamic value filters, can only be 

implemented using SQL. The management of such analytic privileges created in SQL also varies to those 

created in the SAP HANA modeler. 

Structure of Analytic Privileges 

An analytic privilege consists of a set of restrictions against which user access to a particular attribute view, 

analytic view, or calculation view is verified. Each restriction controls the authorization check on the restricted 

view using a set of value filters. A value filter defines a check condition that verifies whether or not the values of 

the view (or view columns) qualify for user access. 

The specification of these restrictions is contained in an XML document that conforms to a defined XML schema 

definition (XSD). 

The following restriction types can be used to restrict data access: 

● View 

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● Activity 

● Validity 

● Attribute 

The following operators can be used to define value filters in the restrictions. 

Note: The activity and validity restrictions support only a subset of these operators. 

● IN 

● CP 

● EQ (=), LE (=) 

● BT 

● IS_NULL 

● NOT_NULL 

All of the above operators, except IS_NULL and NOT_NULL, accept empty strings (“”) as filter operands. 

The following are examples of how empty strings can be used with the filter operators: 

● For the IN operator: IN (“”, “A”, “B”) to filter on these exact values 

● As a lower limit in comparison operators, such as: 

○ BT (“”, “XYZ”), which is equivalent to NOT_NULL AND LE “XYZ” 

○ GT “”, which is equivalent to NOT_NULL 

○ LE “”, which is equivalent to EQ “” 

○ LT “”, which will always return false 

○ CP “”, which is equivalent to EQ “” 

The filter conditions CP “*” will also return rows with empty-string as values in the corresponding attribute. 

View Restriction 

This restriction specifies to which column view(s) the analytic privilege applies. It can be a single view, a list of 

views, or all views. An analytic privilege must have exactly one cube restriction. 

Example: IN ("Cube1", "Cube2") 

Note: When an analytic view is created in the SAP HANA modeler, automatically-generated views are 

included automatically in the cube restriction. 

Activity Restriction 

This restriction specifies the activities that the user is allowed to perform on the restricted view(s), for example, 

read data. An analytic privilege must have exactly one activity restriction. 

Example: EQ "read", or EQ "edit" 

Note: Currently, all analytic privileges created in the SAP HANA modeler are automatically configured to 

restrict access to READ activity only. This corresponds to SQL SELECT queries. This is due to the fact that 

the attribute, analytic, and calculation views are read-only views. This restriction is therefore not 

configurable. 



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Validity Restriction 

This restriction specifies the validity period of the analytic privilege. An analytic privilege must have exactly one 

validity restriction. 

Example: GT 2010/10/01, 01:01:00.000 

Note: All analytic privileges automatically become immediately valid and have unlimited validity when 

activated in the SAP HANA modeler. This restriction is therefore not configurable. 

Attribute Restriction 

This restriction specifies the value range that the user is permitted to access. Attribute restrictions are applied to 

the actual attributes of a view. Each attribute restriction is relevant for one dimension attribute, which can contain 

multiple value filters. Each value filter represents a logical filter condition. 

Value filters for attribute restrictions can be static or dynamic. 

● A static value filter consists of an operator and either a list of values as the filter operands or a single value as 

the filter operand. All data types are supported except those for LOB data types (CLOB, BLOB, and NCLOB). 

For example, a value filter (EQ 2006) can be defined for an attribute YEAR in a dimension restriction to filter 

accessible data using the condition YEAR=2006 for potential users. 

Note: Only attributes, not aggregatable facts (for example, measures or key figures) can be used in 

dimension restrictions for analytic views. 

● A dynamic value filter consists of an operator and a stored procedure call that determines the operand value 

at runtime. 

For example, a value filter (IN (GET_MATERIAL_NUMBER_FOR_CURRENT_USER())) is defined for the 

attribute MATERIAL_NUMBER. This filter indicates that a user with this analytic privilege is only allowed to 

access material data with the numbers returned by the procedure 

GET_MATERIAL_NUMBER_FOR_CURRENT_USER. 

Note: If you create an analytic privilege in the SAP HANA modeler, it is not possible to specify a 

procedure call when defining restrictions. If you want to create analytic privileges with dynamic filter 

conditions, you must do so using SQL. 

It is possible to combine static and dynamic value filters. 

An analytic privilege can have multiple attribute restrictions, but it must have at least one attribute restriction. An 

attribute restriction must have at least one value filter. Therefore, if you want to permit access to the whole 

content of a restricted view, then the attribute restriction must specify all attributes. 

Similarly, if you want to permit access to the whole content of the view with the corresponding attribute, then the 

value filter must specify all values. 

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The SAP HANA modeler automatically implements this specification if you do not select either an attribute 

restriction or a value filter. However, if you create the analytic privilege using SQL, you must make the 

specification manually. 

Example 1: 

 

 

 

Example 2: 

 

 

 

 

 

Logical Combination of Restrictions and Filter Conditions 

The result of user queries on restricted views is filtered according to the conditions specified by the analytic 

privileges granted to the user as follows: 

● Multiple analytic privileges are combined with the logical operator OR. 

● Within one analytic privilege, all attribute restrictions are combined with the logical operator AND. 

● Within one attribute restriction, all value filters on the attribute are combined with the logical operator OR. 

You create two analytic privileges AP1 and AP2. AP1 has the following attribute restrictions: 

● Restriction R11 restricting the attribute Year with the value filters (EQ 2006) and (BT 2008, 

2010) 

● Restriction R12 restricting the attribute Country with the value filter (IN ("USA", "Germany")) 

Given that multiple value filters are combined with the logical operator OR and multiple attribute 

restrictions are combined with the logical operator AND, AP1 generates the condition: 

((Year = 2006) OR (Year BT 2008 and 2010)) AND (Country IN ("USA", 

"Germany")) 

AP2 has the following restriction: 

Restriction R21 restricting the attribute Country with the value filter (EQ "France") 

AP2 generates the condition: 

(Country = "France") 

Any query of a user who has been granted both AP1 and AP2 will therefore be appended with the following 

WHERE clause: 



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((Year = 2006) OR (Year BT 2008 and 2010)) AND (Country IN ("USA", 

"Germany"))) OR (Country = "France") 

Dynamic Value Filters in the Attribute Restriction of Analytic Privileges 

The attribute restriction of an analytic privilege specifies the value range that the user is permitted to access using 

value filters. In addition to static scalar values, stored procedures can be used to define filters. This allows userspecific 

filter conditions to be determined dynamically in runtime, for example, by querying specified tables or 

views. As a result, the same analytic privilege can be applied to many users, while the filter values for authorization 

can be updated and changed independently in the relevant database tables. In addition, application developers 

have full control not only to design and manage such filter conditions, but also to design the logic for obtaining the 

relevant filter values for the individual user at runtime. 

Procedures used to define filter conditions must have the following properties: 

● They must be DEFINER procedures. 

● They must be read-only procedures. 

● A procedure with a predefined signature must be used. The following conditions apply: 

○ No input parameter 

○ Only 1 output parameter as table type with one single column for the IN operator 

○ Only 1 output parameter of a scalar type for all unary operators, such as EQUAL 

○ Only 2 output parameters of a scalar type for the binary operator BETWEEN 

● Only the following data types are supported as the scalar types and the data type of the column in the table 

type: 

○ Date/Time types DATE, TIME, SECONDDATE, and TIMESTAMP 

○ Numeric types TINYINT, SMALLINT, INTEGER, BIGINT, DECIMAL, REAL, and DOUBLE 

○ Character string types VARCHAR and NVARCHAR 

○ Binary type VARBINARY 

When the procedure is executed as part of the authorization check in runtime, the following constraints apply: 

● The user who must be authorized is the database user who executes the query accessing a secured view. This 

is the session user. The database table or view used in the procedure should therefore contain a column to 

store the user name of the session user. The procedure can then filter by this column using the SQL function 

SESSION_USER. This table or view should only be accessible to the procedure owner. 

● The user executing the procedure is the _SYS_REPO user. In the case of procedures activated in the SAP 

HANA modeler, _SYS_REPO is the owner of the procedures. For procedures created in SQL, the EXECUTE 

privilege on the procedure must be granted to the _SYS_REPO user. 

● If the procedure fails to execute, the user’s query stops processing and a “Not authorized” error is returned . 

The root cause can be investigated in the error trace file of the indexserver, 

indexserver_alert_.trc. 

When designing and implementing procedures as filter for dynamic analytic privileges, bear the following in mind: 

● To avoid a recursive analytic privilege check, the procedures should only select from database tables or views 

that are not subject to an authorization check based on analytic privileges. In particular, views activated in the 

SAP HANA modeler are to be avoided completely as they are automatically registered for the analytic 

privilege check. 

● The execution of procedures in analytic privileges slows down query processing compared to analytic 

privileges containing only static filters. Therefore, procedures used in analytic privileges must be designed 

carefully. 

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Runtime Authorization Check of Analytic Privileges 

When a user requests access to data stored in an attribute, analytic, or calculation view, an authorization check 

based on analytic privileges is performed and the data returned to the user is filtered accordingly. Access to a 

view and the way in which results are filtered depend on whether the view is independent or associated with other 

modeling views (dependent views). 

Independent Views 

The authorization check for a view that is not defined on another modeling view is as follows: 

1. The user requests access to an individual view, for example with a SELECT query. 

This is possible if the both of the following prerequisites are met: 

○ The user has been granted the SQL privilege SELECT on the view or the schema in which it is located. 

○ The user has been granted an analytic privilege that is applicable to the view. An analytic privilege is 

applicable to a view if it contains the view in the view restriction and at least one filter on one attribute of 

the view. 

Note: The user does not require the SELECT privilege on the underlying base tables or views of the 

modeling view. 

2. The authorization check determines the analytic privileges that are relevant for the current user and view. 

Relevant analytic privileges are those that met all of the following criteria: 

○ Analytic privileges previously granted to the user, either directly or indirectly through a role 

○ Analytic privileges with a view restriction that includes the accessed view 

○ Analytic privileges with a currently valid validity restriction 

Note: This check is always positive for analytic privileges created and activated in the SAP HANA 

modeler. 

○ Analytic privileges with an activity restriction covering the activity requested by the query are considered 

Note: This check is always positive for analytic privileges created and activated in the SAP HANA 

modeler. 

○ Analytic privileges with dimension restrictions covering some of the view’s attributes 

3. If no relevant analytic privileges are found, the user’s queries are rejected with a “Not authorized” error. 

This means that even though the user has the SELECT privilege on the view, access is not possible. 

If the user does have a relevant analytic privilege but does not have the SELECT privilege on the view, access 

is also not possible. If relevant analytic privileges are found, the authorization check evaluates the value filters 

specified in the dimension restrictions and presents the appropriate data to the user. 

Note: Multiple dimension restrictions and/or multiple value filters are combined as described in the 

section on the structure of analytic privileges. 



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Dependent Views 

Analytic views can be defined on attribute views, and calculation views that are defined on other modeling views. If 

a user requests access to such a view that is dependent on another view, the behavior of the authorization check 

varies as follows: 

● Analytic view associated with attribute view(s) 

A user can access an analytic view with associated attribute view(s) if one of the following prerequisites is 

met: 

○ The user has been granted an analytic privilege on the analytic view itself. 

○ The user has been granted an analytic privilege on an underlying attribute view. 

Result filtering is performed by a logical OR combination of all analytic privileges found on the analytic view 

and on its underlying attribute views. 

An analytic privilege on an analytic view with dependent attributes therefore does not restrict data access to 

the view, but rather increases it because the privilege on the analytic view is combined with privileges defined 

on the associated attribute views using logical OR. 

● Calculation view based on other view(s) 

A user can access a calculation view based on other view(s) if both of the following prerequisites are met: 

○ The user has been granted an analytic privilege on the calculation view. 

○ The user has been granted an analytic privilege on all underlying views if they are attribute, analytic, or 

calculation views. 

Result filtering is performed for each individual view. The underlying attribute, analytic, calculation views are 

authorized and filtered using the analytic privileges relevant for these views. The result of the top-level 

calculation view is then filtered using the analytic privileges defined on the calculation view itself. 

An analytic privilege on a calculation view based on other view(s) therefore further restricts data access to the 

calculation view as the privilege is evaluated on top of the result filtered by the analytic privileges defined on 

the underlying views (corresponding to a logical AND combination). 

Creation and Management of Analytic Privileges 

Analytic privileges can be created, dropped, and changed in the SAP HANA modeler and using SQL statements. 

The SAP HANA modeler should be used in all cases except if you are creating analytic privileges that use 

dynamic procedure-based value filters. 

To create analytic privileges, the system privilege CREATE STRUCTURED PRIVILEGE is required. To drop analytic 

privileges, the system privilege STRUCTUREDPRIVILEGE ADMIN is required. 

In the SAP HANA modeler, repository objects are technically created by the technical user _SYS_REPO, which by 

default has the system privileges for both creating and dropping analytic privileges. To be able to create, activate, 

drop, and redeploy analytic privileges in the SAP HANA modeler therefore, a database user requires the package 

privileges REPO.EDIT_NATIVE_OBJECTS and REPO.ACTIVATE_NATIVE_OBJECTS for the relevant package. 

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Implications of Creating Analytic Privileges Using SQL 

The SAP HANA modeler is the recommended method for creating and managing analytic privileges. However, it is 

necessary to use SQL to implement those features of analytic privileges not available in the modeler, that is, 

dynamic, procedure-based value filters as attribute restrictions. 

In the SAP HANA modeler, analytic privileges are created as design-time repository objects owned by the 

technical user _SYS_REPO. They must be activated to become runtime objects available in the database. Analytic 

privileges created using SQL statements are activated immediately. However, they are also owned by the 

database user who executes the SQL statements. This is the main disadvantage of using SQL to create analytic 

privileges. If the database user who created the analytic privilege is deleted, all objects owned by the user will also 

be deleted. Therefore, if you are using SQL to create analytic privileges, we recommend that you create a 

dedicated database user (that is, a technical user) for this purpose to avoid the potential loss of complex modeled 

privileges. 

An additional disadvantage of creating analytic privileges using SQL is that these analytic privileges are not in the 

SAP HANA repository and they cannot be transported between different systems. 

Granting and Revoking Analytic Privileges 

Analytic privileges are granted and revoked as part of user provisioning. 

If the analytic privilege was created and activated using the SAP HANA modeler, the analytic privilege is owned by 

the _SYS_REPO user. Therefore, to be able to grant and revoke the analytic privilege, a user needs the privilege 

EXECUTE on the procedures GRANT_ACTIVATED_ANALYTICAL_PRIVILEGE and 

REVOKE_ACTIVATED_ANALYTICAL_PRIVILEGE respectively. 

If the analytic privilege was created using SQL, only the owner (that is, the creator) of the analytic privilege can 

grant and revoke it. 

Related Links 



Example: Creating an Analytic Privilege with Dynamic Value Filter 

This example shows you how to create an analytic privilege that contains a dynamic procedure-based value filter 

and a fixed value filter in the attribute restriction. 

Assume you want to restrict access to product data in secured views as follows: 

● Users should only see products beginning with ELECTRO, or 

● Users should only see products for which they are specifically authorized. This information is contained in the 

database table PRODUCT_AUTHORIZATION_TABLE in the schema AUTHORIZATION. 

To be able to implement the second filter condition, you need to create a procedure that will determine which 

products a user is authorized to see by querying the table PRODUCT_AUTHORIZATION_TABLE. 



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1. Create the table type for the output parameter of the procedure: 

CREATE TYPE "AUTHORIZATION"."PRODUCT_OUTPUT" AS TABLE("PRODUCT" int); 

2. Create the table that the procedure will use to check authorization: 

CREATE TABLE "AUTHORIZATION","PRODUCT_AUTHORIZATION_TABLE" ("USER_NAME" 

NVARCHAR(128), "PRODUCT" int); 

3. Create the procedure that will determine which products the database user executing the query is authorized 

to see based on information contained in the product authorization table: 

CREATE PROCEDURE "AUTHORIZATION"."DETERMINE_AUTHORIZED_PRODUCT_FOR_USER" 

(OUT VAL "AUTHORIZATION"."PRODUCT_OUTPUT") 

LANGUAGE SQLSCRIPT SQL SECURITY DEFINER READS SQL DATA AS 

BEGIN 

VAL = SELECT PRODUCT FROM 

"AUTHORIZATION"."PRODUCT_AUTHORIZATION_TABLE” WHERE USER_NAME = 

SESSION_USER; 

END; 

Note: The session user is the database user who is executing the query to access a secured view. This 

is therefore the user whose privileges must be checked. For this reason, the table or view used in the 

procedure should contain a column to store the user name so that the procedure can filter on this 

column using the SQL function SESSION_USER. 

4. Create the analytic privilege: 

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CREATE STRUCTURED PRIVILEGE ' 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

'; 

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Now when a database user requests access to a secured view containing product information, the data returned 

will be filtered according to the following condition: 

(product LIKE "ELECTRO*" OR product IN 

(AUTHORIZATION.DETERMINE_AUTHORIZED_PRODUCT_FOR_USER()) 

12.4.5 Creating Analytic Privileges 

● To create, activate and drop the privilege you have system privileges CREATE STRUCTURED PRIVILEGE and 

STRUCTUREDPRIVILEGE ADMIN. 

● Make sure that both CREATE STRUCTURED PRIVILEGE and STRUCTUREDPRIVILEGE ADMIN are correctly 

owned by SYS_REPO user. 

● To activate and redeploy analytic privileges in the Modeler, a database user requires corresponding repository 

privileges, namely REPO.EDIT_NATIVE_OBJECTS and REPO.ACTIVATE_NATIVE_OBJECTS 

You apply analytic privileges when business users access values with certain combinations of dimension 

attributes. You can use analytic privileges to partition data among various users sharing the same data 

foundation. You can define restrictions for a selected group of models or apply them to all content models across 

packages. 

After activation, an analytic privilege needs to be assigned to a user before taking any effect. The user views the 

filtered data based on the restrictions defined in the analytic privilege. If no analytic privilege applicable for models 

is assigned to a user, he cannot access the model. If a user is assigned to multiple analytic privileges, the 

privileges are combined with OR conditions. 

Remember: In addition to the analytic privileges, a user needs SQL Select privileges on the generated 

column views. 

The generated column views adhere to the following naming conventions: 

For a view “MyView” in package “p1.p2” (i.e. subpackage p2 of package p1) the generated column view lies in 

schema _SYS_BIC and is named “_SYS_BIC”.”p1.p2/MyView”. Ensure that the users who are allowed to see the 

view have select privileges on the view (or the entire schema _SYS_BIC). 

Note: Multiple restrictions applied on the same column are combined by OR. However, restrictions across 

several columns are always combined by AND. 

1. Set Parameters for the Analytic Privilege 

a) In the Modeler perspective, expand the system node from the Navigator panel. 

b) Expand the Content node. 

c) Select the required package. 

d) From the context menu, choose New Analytic Privilege . 

1. Enter a name and description for the analytic privilege, and choose Next. 

2. Select the information models that you want to use for applying restrictions. 




Tip: You can choose to add more models in the editor pane. 

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2. Add Attributes 

a) If you want to add restrictions for all models, select the Applicable to all Information Models option. 

Note: If you do not select this option, the restrictions you create apply only to the secured list of 

models available in the Reference Models panel that you selected above. 

b) In the Associated Attributes Restrictions panel, choose Add to select the attributes for defining 

restrictions. 

c) Choose OK. 

3. Assign Restrictions 

Note: If you do not add any attributes for restrictions there will be unrestricted access to the 

selected models or to all the models (if Applicable to all the Information Models option is selected). 

a) In the Assign Restrictions pane, choose Add to add value restriction for the selected attributes. 

b) Select the required operator and enter a value (manually or via Value Help dialog). 

Remember: To activate the analytic privilege, you must assign a minimum of one restriction to each 

attribute. 

4. Activate the analytic privilege using the Save and Activate option in the editor. 

Note: Select the Save and Activate All option to activate the privilege along with all the required 

objects. 

5. Assign the privilege to a user 

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a) In the Navigator panel, navigate the Security Authorizations Users node. 

b) Select a user. 

c) In the context menu, choose Open. 

d) Choose Analytic Privileges tab page, and add the privilege. 

e) From the editor toolbar, choose Deploy. 

● Consider an analytic view (without fields coming from attribute views) or a calculation view SALES, 

which is added as part of an analytic privilege’s secured models having the following data. 

CUST_ID CUST_GROUP SALES 

1 GRP1 1000 

2 GRP2 1500 

3 GRP3 1200 

1 GRP4 1300 

If you create a restriction on column CUST_ID to filter data for CUST_ID 1 and 2, the conditions are 

combined with OR and the data available for a user is: 


1 GRP1 1000 

2 GRP2 1500 

1 GRP4 1300 

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If you create restrictions on columns CUST_ID and CUST_GROUP such as CUST_ID = 1 and 

CUST_GROUP = 1, the conditions are combined with AND, and the data available for a user is: 


1 GRP1 1000 

Note: 

○ The technical name used for attributes of calculation views and private attributes of 

analytic views, is the same as that of the attribute name. Hence any restriction applied to 

a private attribute of an analytic or calculation view attribute is also applied to any other 

private attribute of an analytic view and calculation view attribute having the same name. 

In the above example, if there is any other analytic view or calculation view, which is part 

of a privilege’s secured list of models, and has a field called “CUST_ID” (not coming from 

any attribute view), the data for these privileges also gets restricted. 

○ If Applicable to all information models is selected, any analytic view/calculation view (even 

if not part of the secured models) which has a (private) attribute called “CUST_ID”, the 

data for these privileges also get restricted. 

○ The behavior for the calculation view is the same as that of the analytic view described 

above. 

● Consider an attribute view CUSTOMER which is part of an analytic privilege’s secured list of models 

having the following data. 

CUST_ID COUNTRY MANDT 

1 IN 1 

2 IN 1 

3 US 1 

1 DE 2 

If you create a restriction on column CUST_ID to filter data for CUST_ID 1 and 2, the conditions are 

combined with OR and the data is shown as follows: 


1 IN 1 

2 IN 1 

1 DE 2 

If you create restrictions on columns CUST_ID and COUNTRY such as CUST_ID = 1 and COUNTRY = 

IN, the conditions are combined with AND, and the data available for a user is: 


1 IN 1000 



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Related Links 

Note: 

○ The technical name used for an attribute view attribute is /$. Hence, in the above example, the technical name for 

CUST_ID is mypackage/CUSTOMER$CUST_ID. This implies that if there is any other 

attribute view “STORE” which is a part of the analytic privilege and has CUST_ID as its 

attribute, it will not get restricted. 

○ Any analytic view that is part of the privilege’s secured list of models and has this attribute 

view as its required object, gets restricted using the technical name. In the example 

above, if an analytic view contains the attribute views CUSTOMER and STORE, both 

CUST_ID attributes are handled independently, because their internal technical name 

used for the privilege check are mypackage/CUSTOMER$CUST_ID and 

myotherpackage/STORE$UST_ID. 

○ If Applicable to all information models is selected, any analytic view (even if not part of the 

secured models) having this attribute view as its required object, also gets restricted. 

Structure of Analytic Privileges [page 328] 

An analytic privilege consists of a set of restrictions against which user access to a particular attribute view, 

analytic view, or calculation view is verified. Each restriction controls the authorization check on the restricted 

view using a set of value filters. A value filter defines a check condition that verifies whether or not the values 

of the view (or view columns) qualify for user access. 

Runtime Authorization Check of Analytic Privileges [page 333] 

When a user requests access to data stored in an attribute, analytic, or calculation view, an authorization 

check based on analytic privileges is performed and the data returned to the user is filtered accordingly. 

Access to a view and the way in which results are filtered depend on whether the view is independent or 

associated with other modeling views (dependent views). 

Dynamic Value Filters in the Attribute Restriction of Analytic Privileges [page 332] 

The attribute restriction of an analytic privilege specifies the value range that the user is permitted to access 

using value filters. In addition to static scalar values, stored procedures can be used to define filters. This 

allows user-specific filter conditions to be determined dynamically in runtime, for example, by querying 

specified tables or views. As a result, the same analytic privilege can be applied to many users, while the filter 

values for authorization can be updated and changed independently in the relevant database tables. In 

addition, application developers have full control not only to design and manage such filter conditions, but also 

to design the logic for obtaining the relevant filter values for the individual user at runtime. 

Creation and Management of Analytic Privileges [page 334] 

Analytic privileges can be created, dropped, and changed in the SAP HANA modeler and using SQL 

statements. The SAP HANA modeler should be used in all cases except if you are creating analytic privileges 

that use dynamic procedure-based value filters. 

Example: Creating an Analytic Privilege with Dynamic Value Filter [page 335] 

This example shows you how to create an analytic privilege that contains a dynamic procedure-based value 

filter and a fixed value filter in the attribute restriction. 

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12.4.6 Granting Privileges to Users 

Privileges can be granted to database users either directly, or indirectly through roles that they have been 

granted. In this case, the privileges are inherited. Roles are the standard mechanism of granting privileges to 

users. 

To be able to grant and revoke privileges and roles to and from users and roles, the following prerequisites must 

be met: 

Action Prerequisite 

Grant system privilege, object privilege, or package 

privilege to user or role 

Granting user must have the privilege being granted 

and be authorized to grant it to other users and roles 

Grant analytic privilege to user or role Granting user must have the object privilege EXECUTE 

Grant object privilege on activated modeled objects, 

such as calculation views, to user or role 

on the procedure 

GRANT_ACTIVATED_ANALYTICAL_PRIVILEGE 

Granting user must have the object privilege EXECUTE 


GRANT_PRIVILEGE_ON_ACTIVATED_CONTENT 

Grant role created in runtime to user or role ● Granting user must have the role being granted 

and be authorized to grant it to other users and 

roles, or 

● Granting user must be have the system privilege 

ROLE ADMIN 

Grant role created in the repository to user or role Granting user must have the object privilege EXECUTE 

on the procedure GRANT_ACTIVATED_ROLE 

Grant application privilege Granting user must have the object privilege EXECUTE 

Grant object privilege on schema containing activated 

modeled objects, such as calculation views, to user or 

role 

Revoke system privilege, object privilege, or package 

privilege from user or role 

Revoke object privilege on schema activated 

containing modeled objects, such as calculation views, 

from user or role 



on the procedure GRANT_APPLICATION_PRIVILEGE 

Granting user must have the object privilege EXECUTE 


GRANT_SCHEMA_PRIVILEGE_ON_ACTIVATED_CONT 

ENT 

Revoking user must be the user who granted the 

privilege 

Revoking user must have the object privilege EXECUTE 


REVOKE_SCHEMA_PRIVILEGE_ON_ACTIVATED_CON 

TENT 

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Action Prerequisite 

Revoke analytic privilege from user or role Revoking user must have the object privilege EXECUTE 


REVOKE_ACTIVATED_ANALYTICAL_PRIVILEGE 

Revoke role created in runtime from user or role Revoking user must be the user who granted the role 

Revoke role created in the repository from user or role Revoking user must have the object privilege EXECUTE 

on the procedure REVOKE_ACTIVATED_ROLE 

Revoke application privilege Revoking user must have the object privilege EXECUTE 

Revoke object privilege on activated modeled objects, 

such as calculation views from user or role 

1. In the Navigator view, choose Security Users . 

on the procedure REVOKE_APPLICATION_PRIVILEGE 

Revoking user must have the object privilege EXECUTE 


REVOKE_PRIVILEGE_ON_ACTIVATED_CONTENT 

2. Open the relevant user and grant the required roles and privileges (object privileges, analytic privileges, 

system privileges, and package privileges) to the user. 

To grant a role or privilege, choose the button and search for the required role or privilege. 

To allow the user to pass on his or her privileges to other users, select Grantable to other users and roles. 

Note: This option is not available if you are granting a role that was created in the repository. 

Note: You cannot grant application privileges directly to users in the SAP HANA studio. It is 

recommended that you grant application privileges to roles created in the repository and then grant 

the role to the user. 

3. Choose the (Deploy) button to save the changes. 

Related Links 

SAP HANA Administration 

12.5 Application Access 

When you develop and deploy applications in the context of SAP HANA Extended Application Services (SAP 

HANA XS), you must define the application descriptors, which describe the framework in which the application 

runs. This application framework includes the root point in the package hierarchy where content is to be served to 

client requests, whether or not the application is permitted to expose data to client requests, what kind of access 

to the data is allowed, and what if any privileges are required to perform actions on application-related packages 

and package content. The application descriptors include the following files: 

● Application-descriptor file 

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The location of the application-descriptor file defines the root path of the resources exposed to client 

requests by the application you develop. You can further restrict access using the application-access and 

application-privileges files. 

● Application-Access File 


a SAP HANA XS application package and what content they are allowed to see. You can use keywords in the 

application-access file to set authentication rules, define package-privilege levels (for example, EXECUTE or 

ADMIN), specify the connection security level (for example, SSL/HTTPS), allow or prevent the creation of 

entity tags (Etags), and so on. You can also define rewrite rules for URLs exposed by an application, for 

example, to hide internal details of URL paths from external users, clients, and search engines. 

● Application-Privileges File 

The application-privileges file enables you to define the authorization privileges required for access to an SAP 

HANA XS application, for example, to start the application (EXECUTE) or to perform administrative actions on 

an application (ADMIN). The privileges defined here are activated for a particular application in the 

application-access file. These privileges can be checked by an application at runtime. Privileges defined apply 

to the package where the privileges file is located as well as any packages further down the package hierarchy 

unless an additional privileges file is present, for example, in a subpackage. 

Related Links 

Note: An additional access-related file, the SQL-connection configuration file, enables you to execute SQL 

statements from inside your SAP HANA XS JavaScript application with credentials that are different to the 

credentials of the requesting user. Each SQL-connection configuration object has a unique name, and the 

administrator can assign specific, individual database users to this configuration. 

The Application-Descriptor File [page 49] 

Each application that you want to develop and deploy on SAP HANA Extended Application Services (SAP 

HANA XS) must have an application descriptor file. The application descriptor is the core file that you use to 

describe an application's framework within SAP HANA XS. 

The Application-Access File [page 50] 

SAP HANA XS enables you to define access to each individual application package that you want to develop 

and deploy. 

The Application-Privileges File [page 59] 

In SAP HANA Extended Application Services (SAP HANA XS), the application-privileges (.xssprivileges) 

file can be used to create or define the authorization privileges required for access to an SAP HANA XS 

application, for example, to start the application or to perform administrative actions on an application. These 

privileges can be checked by an application at runtime. 



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13 Implementing Lifecycle 

Management 

13.1 SAP HANA Delivery Units 

In SAP HANA, the delivery unit (DU) is the vehicle that lifecycle management (LCM) uses to ship one or more 

software components from SAP (or a partner) to a customer . 

Delivery Units correspond to an "application" with versions, for which support packages and patches are 

delivered. Delivery units are not an equivalent to development classes; they are similar to Software Component 

Versions in the Product Availability Matrix (PAM). You can also use the delivery unit to transport repository 

content between SAP HANA systems, for example, between development systems or between development and 

productive systems. 

Note: A governance plan exists for the naming of delivery units and the package structure. 

A delivery unit is identified by the following key properties: 

● Vendor 

Used primarily to define the identity of the company producing the software component to deliver, for 

example, "sap". However, vendor can also be used to specify any customer implementing SAP HANA. To 

create a delivery unit, it is a prerequisite to maintain a vendor in your system. 

● Name 

Used to identify the software component to be delivered 

Although a vendor might provide multiple versions of a delivery unit in parallel, only one version of a delivery unit 

can be installed in a HANA system at any one time. In addition, duplicate names are not allowed for delivery units. 

SAP HANA treats delivery units and their versions as software components and software-component versions. 

Software components and software-component versions are usually shipped as part of a product (product 

version). 

Note: If you try to create a delivery unit using a name that already exists in your system, you will receive a 

validation error. A validation error also occurs if the check for a valid vendor ID does not find a suitable 

entry. 

13.2 The SAP HANA Delivery-Unit Lifecycle 

In SAP HANA, lifecycle management (LCM) includes all the activities you need to plan and perform to ensure that 

the software components you develop for SAP HANA Application Services are produced and shipped in a 

regulated way that meets the requirements laid out for the SAP HANA platform. 

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Implementing Lifecycle Management

For example, you need to plan, manage, and maintain the application versions you want to ship, and you need to 

ensure that a stable plan exists to provide support for existing and all future versions of your application. 

SAP HANA lifecycle management uses the delivery unit (DU) is a vehicle to ship one or more software 

components from SAP (or a partner) to a customer. Delivery Units correspond to an "application" with versions, 

for which support packages and patches are delivered. You can also use the delivery unit to transport content 

between SAP HANA systems, for example, between development systems or between development and 

productive systems. 

Note: Delivery units are not to be confused with development classes; delivery units are similar to 

software component versions in the Product Availability Matrix (PAM). 

The Application-Development Lifecycle 

Application development on SAP HANA requires a server-centric life cycle for design-time objects, which are the 

development artifacts that you store in the SAP HANA repository. As an application developer, you check out 

design-time content from the repository and edit a copy of the checked-out artifact in the local file system on the 

your personal computer (PC). The following steps provide a brief, high-level overview of the development lifecycle 

for design-time content: 

1. Check out design-time content. 

Check out the package containing the design-time artifacts you want to work on (if the package already 

exists). 

2. Edit the design-time content. 

Edit the copies of the design-time artifacts, which are stored in your SAP HANA repository "workspace" on 

your local file system; the local copies of the design-time artifacts are created during the checkout process. 

3. Commit changes to design-time content. 

Committing the changes you have made to the design-time artifacts creates new versions of the artifacts in 

the SAP HANA repository. Note that identical (unchanged) versions of a file are not committed. 

4. Activate changes to design-time content. 

Activating the changes you have made to the design-time artifacts makes these changes available to 

applications and other users, creating runtime objects where necessary. 

13.3 Exporting Delivery Units 

Exporting a delivery unit (with all packages and dependencies) is the mechanism SAP HANA uses to enable the 

transfer of delivery units between systems, for example, to transport application content between development 

systems of from a development system to a consolidation system. 

The SAP HANA studio includes a mechanism that enables you to export and import delivery units. You can use the 

export feature to create an image of a delivery unit, which you can store either on the SAP HANA server or in the 

file system of a selected client for future import to another system. You can also export development objects as 

an archive that you can send to SAP support or share with other members of the development team. 


Implementing Lifecycle Management 

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To export a delivery unit, perform the following steps: 


Ensure that the SAP HANA studio is connected to the SAP HANA system hosting the delivery unit you want to 

export. If this is not the case, choose Select System... and change the system. 

2. In the File menu, choose Export.... 

3. Select the export destination. 

The export destination enables you to specify the purpose for which you want to export the packages that 

make up the export archive. The option you choose determines the contents of the export archive. In most 

cases, you would choose the Delivery Unit option, which includes everything you need to transport the 

application-development structure to another system . However, you can choose from the following 

additional export destination options: 

○ Developer Mode 

Includes most objects and data, but does not include translatable text bundles 

○ SAP Support Mode 

Includes only the active version of objects and any data required by SAP Support to reproduce an issue 

you have encountered and reported 

Specify the Delivery Unit option, for example, SAP HANA Content > Delivery Unit 

4. Select the source system; the system you want to export the delivery unit from. 

In the Systems for export screen area of the Delivery Unit dialog, select the SAP HANA system hosting the 

repository in which the delivery unit is located that you want to export and choose Next to confirm the 

selection.. 

5. Select the delivery unit to export. 

For example, HANA_XS_DOCS 

6. Filter the contents of the export package according to a specified time stamp. 

This step is optional. You can choose to export a complete delivery unit, or only those parts of a delivery unit 

that were changed during a specified time interval, which you define in the Filter by Time screen area. 

7. Select a location for the exported delivery unit: 

a) Server 

The SAP HANA studio automatically selects a file location to export the delivery unit to. 

b) Client 

Browse to the location in the local file-system where you want to store the exported delivery unit. 

8. Choose Next to confirm the settings. 

9. Choose Finish to start the export operation. 

10. Confirm the export operation succeeded. 

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You can browse to the location in the file system and examine the package contents in a file explorer to make 

sure the package contains the required content. 

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13.4 Importing Delivery Units 

Importing a delivery-unit archive is the mechanism SAP HANA uses to enable you to transport delivery units 

between systems, for example, to upload a delivery unit that was exported from another development system or 

saved as an archive on a local file system. 

The SAP HANA studio includes a mechanism that enables you to export and import delivery units. To import a 

delivery unit, perform the following steps: 


Ensure that the SAP HANA studio is connected to the SAP HANA system hosting the delivery unit you want to 

export. If this is not the case, choose Select System... and change the system. 

2. In the File menu, choose Import... 

3. Select the import mode. The choice you make determines the information you need to enter in the next steps. 

The import mode enables you to specify the purpose for which you want to import the packages that make up 

the import archive. In most cases, you would choose the Delivery Unit option, which includes everything you 

need to transport the application-development structure from another system . However, you can choose 

from the following additional import destination options: 

○ Data from local file 

Imports data from a comma-separated-list (CSV) file or a Microsoft Excel file stored on the local file 

system into a new or an existing table (and schema). 

○ Developer Mode 

Includes most objects and data, but does not include translatable text bundles. The import operation 

obeys the following rules regarding the contents of the imported archive: 

○ If a package with the same name as the one to be imported already exists on the target system, but 

the package languages differ, objects are imported with a warning message. 

○ If a package with the same name as the one to be imported does not already exist on the target 

system, then the respective package with its original language (fetched from the properties file) is 

created. 

○ For old objects where no related properties file exists, a package is created with its language set to 

the logon language of the current import session. 

○ Import SAP NetWeaver BW Models 

Imports SAP NetWeaver Business Warehouse (SAP NetWeaver BW) models that are InfoCubes 

optimized forSAP HANA, SAP HANA-optimized DataStore objects, and Query Snapshot InfoProviders to 

the SAP HANA modeling environment. 

Note: With this option, you must maintain connection details for the BW system you want to 

import from, for example, host name, instance ID, client number and so on. You can test the 

connection before continuing with the import operation. 

Specify the mode in which you want the data to be imported, for example, SAP HANA Content > Delivery 

Unit . 

4. Select the target system; the system you want to import the delivery unit into. 

In the Systems for export screen area of the Delivery Unit dialog, select the SAP HANA system hosting the 

repository into which you want to import the delivery unit and choose Next to confirm the selection. 



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5. Select the file containing the delivery unit you want to import. 

a) Server 

The SAP HANA studio automatically displays a list of available files stored in the default location; use the 

drop-down list to choose the file you want to import. 

b) Client 

Browse to the location in the local file-system where the file you want to import is stored. 

Before starting the import operation, the SAP HANA studio compares the contents of the delivery unit 

selected for imported with the current status of the repository on the target system and displays the results in 

the Object import simulation screen area. Hover the cursor over the icons in the Status column for a brief 

description of the indicated status. 

6. Choose Finish to start the import operation. 

Use the Actions screen area to specify what action to take if an imported object already exists in the target 

repository, for example: 

○ Overwrite inactive versions 

Overwrite inactive versions in your inactive workspace with objects from the imported delivery unit. 

○ Activate objects 

Activate objects imported from the delivery unit. 

○ Bypass validation 

Do not perform the client-side validation check on imported objects. 

7. Check the status bar in the SAP HANA studio to follow the progress of the import operation. 

You can also check progress in the Current tag page of the Job Log view. 

8. Confirm the import operation succeeded. 

13.5 Translating Delivery Units 

SAP HANA includes features that enable you to translate package-related metadata texts, for example labels and 

menu items in the user interface. The translation typically occurs on a separate dedicated system. 

If you plan to translate the contents of the new delivery unit you create, you must maintain translation details. The 

details include the connection to the translation system that the translation team use to store the localized 

versions of the translated data. The text to be translated is uploaded from the SAP HANA repository to the 

translation system and then reimported to the repository after the translated text are complete. As part of the 

translation process for delivery units, you typically perform the following tasks 

1. Maintain translation details for each delivery unit 

Translation details includes both mandatory and optional information. Mandatory details to maintain include 

the terminology domain, for example, Financial Accounting (FI), or Production Planning (PP) and the name 

space for the text collection, which is used by the translation systems. 

2. Maintain the connection with the remote translation system 

You need to be able to exchange the translation texts between SAP HANA and the translation system. 

3. Upload translation data to the translation system 

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4. Download translated text to the SAP HANA repository 

13.5.1 SAP HANA Delivery-Unit Translation Details 

The SAP HANA repository includes features for translating package-related metadata texts. If you plan to 

translate the contents of the new delivery unit you create, you must maintain translation details. 

Translation details provide a brief overview of the type and current status of the text objects to be translated, for 

example, by specifying the technical area of the new delivery unit and indicating the current status of translation 

texts. 

Note: Translation text can include the following elements: UI strings (menus, dialog titles), error 

messages, and documentation, amongst other things. Package names and descriptions are also relevant 

for translation purposes as are the names and descriptions of database views, tables, columns, and so on. 

To make things easier for the translation team, you should maintain the following metadata for translation 

purposes; the metadata must be maintained at the package level: 

● Terminology domain (mandatory) 

The technical/product area with which your delivery unit (application) is associated, for example: AC 

(Accounting General), FI (Financial Accounting), or PP (Production Planning and Control). This enables 

translator teams to assign work to the most suitable experts, and allows the translators to make use of 

existing terminology databases. The terminology domain is used by SAP internal translation systems. 

● Text collection (mandatory) 

The name space for the text objects in the translation system. Technically, you can use any value, but the 

text-collection name space is similar to the package namespace used in SAP HANA, for example: 

"sap.hana.xs.docs". The value assigned to the Text collection field is used by SAP internal translation systems. 

● Hint 

An optional field that customers and partners can use to pass on notes concerning the text objects tagged for 

translation. 

● Text status 

An optional field that customers and partners can use to pass on information indicating the current stage in 

the translation-review process of the text objects, for example: "New", "In review", "Reviewed", "Approved", 

"Published", and so on. 

13.5.2 Maintaining Translation Details 

Translation details provide a brief overview of the type and current status of the text objects to be translated, for 

example, by specifying the technical area of the new delivery unit and indicating the current status of translation 

texts. 

If you plan to translate the contents of a delivery unit, you must maintain translation details. You can maintain the 

translation details when you create a new delivery unit or for existing delivery units. It is mandatory to maintain 

the following translation-related details: 

● Terminology domain 

The technical/product area with which your delivery unit (application) is associated, for example: AC 

(Accounting General), FI, or PP. 

● Text collection 



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The name space for the text objects in the translation system, for example, "sap.hana.xs.docs". 


2. In the Navigator view, select the SAP HANA instance where the repository containing the delivery unit is 

located. 

3. Expand the Content node until you can see the package whose translation details you want to maintain. 

4. Maintain the translation details for the selected delivery unit, as follows: 

a) Right-click the package whose translation details you want to maintain and choose Edit. 

b) Choose Translation >> to display the Translation Details screen area at the bottom of the Edit Package 

Details dialog. 

c) Select a Terminology Domain from the drop-down list. 

d) Enter a Text collection name. 

e) Save the changes to the translation details. 

5. Save the changes to the delivery unit. 

6. Commit and activate the changes in the SAP HANA repository. 

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14 Using Database Client Interfaces 

SAP HANA provides client interfaces for connecting applications so they can retrieve and update data. 

SAP HANA provides many methods for applications to access its data. For example, a spreadsheet application 

could use ODBO to consume analytic views and enable users to create pivot tables, or a Web application could use 

OData interfaces to access the data and display it. 

SAP HANA can expose data with the following interfaces: 

● Client interfaces, which are available as long as the SAP HANA clients are installed: 

○ ODBC 

○ ODBO 

○ JDBC 

● Web-based interfaces, which must be defined by the application developer, who determines what data to 

expose and to whom: 

○ OData 

○ XMLA 

○ Server-Side JavaScript 

Related Links 

SAP HANA Database - Client Installation Guide 

Defining Web-based Data Access [page 164] 

SAP HANA extended application services (SAP HANA XS) provide applications and application developers 

with access to the SAP HANA database using a consumption model that is exposed via HTTP. 

14.1 Connecting via ODBC 

SAP HANA provides an ODBC driver for connecting applications to the database. 

Note: Make sure to use the 32-bit ODBC driver for 32-bit applications, and the 64-bit driver for 64-bit 

applications. 

1. Install the ODBC driver. The driver is installed as part of the SAP HANA client installation. 

2. Write code to create a connection to the database. You can use one of the following methods: 

○ Connection String (SQLDriverConnect): Use a connection string in the form: 

DRIVER={};UID=;PWD=; 

SERVERNODE=:; 

should be one of the following: 

○ HDBODBC: For 64-bit applications 

○ HDBODBC32: For 32-bit applications 


Using Database Client Interfaces 

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should be 315, for example, 30015, if the instance is 00. 

The following is an example of a connection string: 

DRIVER={HDBODBC};UID=myUser;PWD=myPassword;SERVERNODE=myServer:30015; 

○ DSN (SQLConnect): Create a data source by running the odbcad32.exe tool. You can run this via a 

Related Links 

command line or via the Control Panel /Administrative Tools /Data Sources (ODBC) . 

Note: 

○ The application is located in the system32 directory. To create a data source for the 32-bit 

driver on a 64-bit Microsoft Windows machine, run the tool from the SysWOW64 directory. 

In the DSN tab, choose Add, select the SAP HANA driver, and select Finish. The following appears: 

You cannot enter a user name and password here. For the server and port, you can either enter a key 

created using the SAP HANA user store (which defines the server, port, user name and password), or you 

can enter a server and port (e.g., myServer:30015). If you enter a server and port, then the application 

must supply the user name and password when connecting. 


Using the User Store [page 352] 

14.1.1 Using the User Store 

The SAP HANA user store enables you to store connection information for connecting to an SAP HANA system. 

Instead of entering connection information each time you make a connection, you store the information, assign it 

a key, and use this key when making connections. 

This makes it easier to move between systems (for example, when executing SQL from the command line), and 

also keeps connection information, including user names and passwords, in a secure place. 

The SAP HANA user store is part of the client installation. 

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Using Database Client Interfaces

1. In a command line, run the following: 

hdbuserstore.exe set : 

The server, port, user name and password are now stored in the user store. The key is a string you use to refer 

to this set of connection information. 

2. Use the key to reference a connection to a particular system. Always precede the key with an @, for example, 

@mykey. 

Use the key in the following ways: 

○ In the connection string, use the key for the SERVERNODE parameter, and do not include a user name 

and password, for example: 

SERVERNODE={@mykey};DRIVER={hdbodbc}; 

○ In creating a DSN, enter the key (for example, @mykey) for the server and port. 

○ In testing your connection (by running odbcreg -t hdbodbc), use the key (for example, @mykey) for 

the server and port. If the connection is successful, you get something like this: 

The response includes a sample connection string using the key. 

Related Links 

Testing the ODBC Installation [page 353] 

You can test the installation of the ODBC driver and your ability to connect by using the odbcreg tool, which 

is part of the ODBC installation. 

14.1.2 Testing the ODBC Installation 

You can test the installation of the ODBC driver and your ability to connect by using the odbcreg tool, which is 

part of the ODBC installation. 

1. Open a command window. 

2. Start the odbcreg tool by enter a command in the form: odbcreg -t hdbcodbc (for 64-bit driver) or 

odbcreg32 -t hdbcodbc32 (for 32-bit driver). 



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If the driver is installed properly, you should get the ODBC login screen. 

Note: You can also run the command odbcreg -g or odbcreg32 -g to get a list of installed 

drivers. The SAP HANA driver is called HDBODBC. 

3. Test your ability to connect by entering connection information (system, port, user name and password) and 

select OK. The tool closes and the results of the test are printed in the command window. 

You can also run odbcreg -g to get a list of installed ODBC drivers, and check to make sure that the SAP HANA 

driver (either HDBODBC or HDBODBC32) is installed. 

14.2 Connecting via JDBC 

SAP HANA provides a JDBC driver for connecting Java applications to the database. 

1. Install the JDBC driver. 

The driver (ngdbc.jar) is installed as part of the SAP HANA client installation and is located at: 

○ C:\Program Files\sap\hdbclient\ on Microsoft Windows platforms 

○ /usr/sap/hdbclient/ on Linux and UNIX platforms 

2. Add ngdbc.jar to your classpath. 

3. If you are on a version of Java earlier than Java 6, load the JDBC driver class, which is called 

com.sap.db.jdbc.Driver. 

4. Write Java code to create a connection to the database and execute SQL commands. Use a connection string 

in the form of jdbc:sap://:[/?]. For example: 

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jdbc:sap://myServer:30015/?autocommit=false 

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The port should be 315, for example, 30015, if the instance is 00. 

You can specify one or more failover servers by adding additional hosts, as in the following example: 

jdbc:sap://myServer:30015,failover1:30015,failover2:30015/? 

autocommit=false 

Related Links 

The following is an example of connecting to an SAP HANA server called myhdb, which was installed as 

instance 07, with user name myname and password mysecret. Make sure to change these for your 

system, and add the JDBC driver (ngdbc.jar) to your classpath. 

import java.sql.*; 

public class jdemo { 

public static void main(String[] argv) { 

Connection connection = null; 

try { 

connection = DriverManager.getConnection( 

"jdbc:sap://myhdb:30715/? 

autocommit=false",myname,mysecret); 

} catch (SQLException e) { 

System.err.println("Connection Failed. User/Passwd Error?"); 

return; 

} 

if (connection != null) { 

try { 

System.out.println("Connection to HANA successful!"); 

Statement stmt = connection.createStatement(); 

ResultSet resultSet = stmt.executeQuery("Select 'hello 

world' from dummy"); 

resultSet.next(); 

String hello = resultSet.getString(1); 

System.out.println(hello); 

} catch (SQLException e) { 

System.err.println("Query failed!"); 

} 

} 

} 

} 


14.2.1 Tracing JDBC Connections 

You can activate the JDBC trace to find errors while your application is connected to a database via JDBC. 

You must be logged on as the operating system user who started (or will start) the JDBC application. 

Note: 

● You always activate the JDBC trace for all JDBC applications that the current operating system user 

has started. 

● Configuration changes have an effect on all JDBC applications that the current operating system user 

has started. 

When the JDBC trace is activated, the JDBC driver logs on the client the following information: 



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● JDBC API calls called by the JDBC application 

● JDBC API call parameters 

● Executed SQL statements and their results 

The location of the trace file is determined by the trace options. 

Tracing via GUI 

You can start tracing by running the tracing configuration tool that includes a graphical user interface (GUI). 

Tracing via the GUI enables you to start and configure tracing without stopping and restarting your application 

that is connected via JDBC. 

1. On the client, enter the following command on the command line: java -jar 

\ngdbc.jar. 

2. Select Trace enabled. 

3. Select and modify the tracing options. 

4. Select OK. 

Tracing via Command Line 

You can start tracing by running the tracing configuration tool and sending commands via the command line. 

Tracing via the command line enables you to start and configure tracing without stopping and restarting your 

application that is connected via JDBC. 

1. Display the current configuration by running the command java -jar 

\ngdbc.jar. 

2. Select trace options by running the command java -jar \ngdbc.jar 

. 

3. Start tracing by running the command java -jar \ngdbc.jar TRACE ON. 

Related Links 

Trace Options 

Tracing via Connection String 

You can start tracing by adding an option in the connection string when creating a JDBC connection. 

Tracing via the connection string requires you to stop and restart your application that is making the JDBC 

connection. Also, with the connection string, you cannot turn off tracing or set any options except setting the 

trace filename. 

Add the trace option to the connection when creating a JDBC connection. 

Here is an example connection string that starts tracing: 

jdbc:sap://localhost:30015/?autocommit=false&trace=traceFile.txt 

The location of the trace file is determined by the trace options. 

Trace Options 

Options when enabling JDBC tracing. 

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The first column shows the field name in the GUI-based tracing configuration tool, and the second column shows 

the command to enter when using the command-line tool. 

Table 16: Trace Options 

Option Command Line Option Description 

Trace enabled TRACE ON | OFF Starts and stops tracing 

Trace file folder No command-line option. The folder can be specified 

with the FILENAME option. 

Sets the directory where the system 

writes the trace files. 

When no folder is specified, the files 

are saved in the working directory of 

the application. 

Trace file name TRACE FILENAME [] Sets the name of the trace file. 

Limit file size TRACE SIZE [KB|MB|GB] 

To remove the size limit, use the following option: 

TRACE SIZE UNLIMITED 

Stop on error TRACE STOP ON ERROR 

To no longer stop on the specified error, use the 

following option: 

TRACE STOP ON ERROR OFF 

The system assigns each trace file 

an additional unique ID, so the file 

name is: 

_.prt 

The default file name is 

jdbctrace. 

Limits the size of each trace file. 

Stops writing the JDBC trace when 

the specified error code occurs. 

14.2.2 Valid Java-to-SQL Conversions 

SAP HANA allows each Java object to be converted to specific SQL types using the JDBC method 

PreparedStatement.setObject or RowSet.setObject. 

Some conversions may fail at runtime if the value passed is invalid. 



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14.3 Connecting via ODBO 

SAP HANA provides an ODBO driver for connecting applications to the database and executing MDX statements. 

1. Install the ODBO driver. The driver is installed as part of the SAP HANA client installation. 

2. Specify in your client the provider name: SAPNewDBMDXProvider 

3. Create a connection string in the form of: 

;User ID=;Password=

3. In the Connection tab of the Data Link Properties window, enter the SAP HANA server name, instance number, 

user name and password. 



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4. Select the cube from which you want to import data. SAP HANA analytic and calculation views are exposed as 

cubes. 

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SAP HANA supports the following Microsoft Excel features: 

● Drilling down 

● Selection filtering 

● Top/bottom filters 

● Report filters 

● Member properties 

● Refresh cube 

● Convert PivotTable into formulas 

● Server formatting 

● Pre-modeled calculated members 

● Show/hide fields 

● Enhanced value and label filters 

● Insert slicer 

● Text search in report filter 

● PivotTable filter 

● Creation of named sets 

14.3.2 Multidimensional Expressions (MDX) 

Multidimensional Expressions (MDX) is a language you can use to query multidimensional data stored in OLAP 

cubes. 



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MDX uses a multidimensional data model to enable navigation in multiple dimensions, levels, and up and down a 

hierarchy. With MDX, you can access pre-computed aggregates at specified positions (levels or members) in a 

hierarchy. 

Note: MDX is an open standard. However, SAP has developed extensions to MDX that are designed to 

enable faster and more efficient access to multidimensional data, for example, to serve specific SAP 

HANA application requirements and to optimize the resultset for SAP HANA clients. 

MDX is implicitly a hierarchy-based paradigm. All members of all dimensions must belong to a hierarchy. Even if 

you do not explicitly create hierarchies in your SAP HANA data model, the SAP HANA modeler implicitly 

generates default hierarchies for each dimension. All identifiers that are used to uniquely identify hierarchies, 

levels and members in MDX statements (and metadata requests) embed the hierarchy name within the identifier. 

In SAP HANA, the standard use of MDX is to access SAP HANA models (for example, analytical and attribute 

views) that have been designed, validated and activated in the modeler in the SAP HANA studio. The studio 

provides a graphical design environment that enables detailed control over all aspects of the model and its 

language-context-sensitive runtime representation to users. 

MDX in SAP HANA uses a runtime cube model, which usually consists of an analytical (or calculation) view that 

represents data in which dimensions are modeled as attribute views. You can use the analytical view to specify 

whether a given attribute is intended for display purposes only or for aggregation. The key attributes of attribute 

views are linked to private attributes in an analytical view in order to connect the entities. One benefit of MDX in 

SAP HANA is the native support of hierarchies defined for attribute views. 

Note: MDX in SAP HANA includes native support of hierarchies defined for attribute views. SAP HANA 

supports level-based and parent-child hierarchies and both types of hierarchies are accessible with MDX. 

SAP HANA supports the use of variables in MDX queries; the variables are a SAP-specific enhancement to 

standard MDX syntax. You can specify values for all mandatory variables that are defined in SAP HANA studio to 

various modeling entities. The following example illustrates how to declare SAP HANA variables and their values: 

MDX 

Select 

From [MINI_C1_VAR] 

Where [Measures].[M2_1_M3_CONV] 

SAP VARIABLES [VAR_VAT] including 10, 


[VAR_TARGET_CURRENCY] including 'EUR', 

14.3.3 MDX Functions 

MDX in SAP HANA supports a variety of standard MDX functions. 

Table 17: Supported MDX Functions 


Aggregate Returns a calculated value using the appropriate aggregate function, based on the 

aggregation type of the member. 

Ancestor Returns the ancestor of a member at a specified level or at a specific distance away 

in the hierarchy. 

Ancestors Returns a set of all ancestors of a member at a specified level or at a specific 


Ascendants Returns the set of the ascendants of the member. 

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Avg Returns the average value of a numeric expression evaluated over a set. 

BottomCount Returns a specified number of items from the bottom of a set, optionally sorting 

the set first. 

Children Returns the children of a member. 

ClosingPeriod Returns the last sibling among the descendants of a member at a specified level. 

Count Counts the number of members in the tuple. 

Cousin Returns the child member with the same relative position under a parent member 

as the specified child member. 

Crossjoin Returns the cross product of two sets. 

CurrentMember Returns the current member along a hierarchy. 

DefaultMember Returns the default member of a hierarchy. 

Descendants Returns the set of descendants of a member at a specified level or at a specific 


Dimension Returns the hierarchy that contains a specified member or level. 

Dimensions Returns a hierarchy specified by a numeric or string expression. 

Distinct Returns a set, removing duplicate tuples from a specified set. 

DistinctCount Returns the number of distinct tuples in a set. 

DrillDownLevel Drills down the members of a set one level below the lowest level represented in the 

set, or to one level below an optional level of a member represented in the set. 

DrillDownLevelBottom Drills down the members of a specified count of bottom members of a set, at a 

specified level, to one level below. 

DrillDownLevelTop Drills down a specified count of top members of a set, at a specified level, to one 

level below. 

DrillDownMember Drills down the members in a specified set that are present in a second specified 

set. 

DrillDownMemberBottom Drills down the members in a specified set that are present in a second specified 

set, limiting the result set to a specified number of bottommost members. 

DrillDownMemberTop Drills down the members in a specified set that are present in a second specified 

set, limiting the result set to a specified number of topmost members. 

DrillUpLevel Drills up the members of a set that are below a specified level. 

DrillUpmember Drills up the members in a specified set that are present in a second specified set. 

Except Finds the difference between two sets, optionally retaining duplicates. 

Filter Returns the set resulting from filtering a set based on a search condition. 

FirstChild Returns the first child of a specified member. 

FirstSibling Returns the first child of the parent of a specified member. 



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Generate Applies a set to each member of another set, and then joins the resulting sets by 

union. Alternatively, this function returns a concatenated string created by 

evaluating a string expression over a set. 

Head Returns the first specified number of elements in a set. 

Hierarchize Orders the members of a specified set in a hierarchy in natural or, optionally, postnatural 

order. 

Hierarchy 

Instr The InStr function finds the starting location of a substring within a specified string. 

Intersect Returns the intersection of two sets, optionally retaining duplicates. 

IsAncestor Returns true if the first member specified is an ancestor of the second member 


IsGeneration Returns true if the member specified is a leaf, else returns false. 

IsLeaf Returns true if the first member specified is an ancestor of the second member 


IsSibling Returns true if the first member specified is an sibling of the second member 


Item If an integer is specified, the Item function returns the tuple that is in the zerobased 

position specified by Index. 

IIF Returns one of values determined by a logical test. 

Lag Returns the member that is a specified number of positions prior to a specified 


LastChild Returns the last child of a specified member. 

LastPeriods Returns a set of members prior to and including a specified member. 

LastSibling Returns the last child of the parent of a specified member. 

Lead Returns the member that is a specified number of positions following a specified 


Leaves If a dimension name is specified, returns a set that contains the leaf members of 

the key attribute for the specified dimension.If a dimension name is not specified, 

the function returns a set that contains the leaf members of the entire cube. 

Left The Left function returns a string of a specified number of characters from the left 

side (beginning) of a specified string. 

Level Returns the level of a member. 

Levels Returns the level whose zero-based position in a dimension is specified by a 

numeric expression. 

Max Returns the maximum value of a numeric expression evaluated over a set. 

Member_caption Returns the caption of a member 

Members Returns the set of all members in a specified hierarchy. 

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MembersAscendantsDesc 

endants 

Returns the set of specified members in a given hierarchy. 

Mid The Mid function returns a substring of a string argument. 

Min Returns the minimum value of a numeric expression evaluated over a set 

MTD Returns a set of members from the Month level in a Time dimension starting with 


Name Returns the name of a specified hierarchy or member. 

NextMember Returns the next member in the level that contains a specified member. 

NOT Performs a logical negation on a numeric expression. 

OpeningPeriod Returns the first sibling among the descendants of a specified level, optionally at a 

specified member. 

OR Performs a logical disjunction on two numeric expressions. 

Ordinal Returns the zero-based ordinal value associated with a specified level. 

ParallelPeriod Returns a member from a prior period in the same relative position as a specified 

member. 

Parent Returns the parent of a specified member. 

PeriodsToDate Returns a set of members (periods) from a specified level starting with the first 

member and ending with a specified member. 

PrevMember Returns the previous member in the level that contains a specified member. 

Properties Returns a string containing the value of the specified member property. 

QTD Returns a set of members from the Quarter level in a Time dimension starting with 


Range Performs a set operation that returns a naturally ordered set, with the two 

specified members as endpoints, and all members between the two specified 

members included as members of the set 

Right The Right function returns a string of a specified number of characters from the 

right side (end) of a specified string. 

Siblings Returns the set of siblings of a specified member, including the member itself. 

StrToMember Returns a member from a string expression in MDX format. 

StrToSet Constructs a set from a specified string expression in MDX format. 

StrToTuple Constructs a tuple from a specified string expression in MDX format. 

StrToValue Returns a value from a string expression 

Subset Returns a subset of tuples from a specified set. 

Sum Returns the sum of a numeric expression evaluated over a specified set. 

Tail Returns the last specified number of elements in a set. 



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TopCount Returns a specified number of items from the topmost members of a specified set, 

optionally ordering the set first. 

Union Performs a set operation that returns a union of two sets, removing duplicate 

members. 

UniqueName Returns the unique name of a specified hierarchy. 

WTD Returns a set of members from the Week level in a Time dimension starting with 


YTD Returns a set of members from the Year level in a Time dimension starting with the 

first period and ending with a specified member. 

14.3.4 MDX Extensions 

SAP HANA supports several extensions to the MDX language, for example, additional predefined functions and 

support for variables. 

Sibling_Ordinal Intrinsic Property 

The object Member includes a property called Sibling_Ordinal, that is equal to the 0-based position of the 

member within its siblings. 

WITH 

MEMBER [Measures].[Termination Rate] AS 

[Measures].[NET_SALES] / [Measures].[BILLED_QUANTITY] 

SELECT 

{ 

[Measures].[NET_SALES], 

[Measures].[BILLED_QUANTITY], 

[Measures].[Termination Rate] 

} ON COLUMNS, 

Descendants 

( 

[MDX_TEST_10_DISTRIBUTION_CHANNEL]. 

[MDX_TEST_10_DISTRIBUTION_CHANNEL].[All].[(all)], 

1, 

SELF_AND_BEFORE 

) 

DIMENSION PROPERTIES SIBLING_ORDINAL ON ROWS 

FROM MDX_TEST_10_ITELO_SALES_DATA 

MembersAscendantsDescendants Function 

SAP HANA includes a new function called MembersAscendantsDescendants that enables you to get, for 

example, all ascendants and descendants of a specific member. This function improves on the standard MDX 

functions Ascendants and Descendants. 

The function can be called as follows: 

MembersAscendantsDescendants (, ) 

● set: A set of members from a single hierarchy 

● flag: Indicates which related members to return, and can be one of the following: 

366 

○ MEMBERS_AND_ASCENDANTS_AND_DESCENDANTS 

P U B L I C 




○ MEMBERS_AND_ASCENDANTS 

○ MEMBERS_AND_DESCENDANTS 

○ ASCENDANTS_AND_DESCENDANTS 

○ ONLY_ASCENDANTS 

○ ONLY_DESCENDANTS 

SELECT 


ON COLUMNS, 

NON EMPTY 



MEMBERS_AND_ASCENDANTS_AND_DESCENDANTS )) } 

ON ROWS 

FROM [JUICE] 

SELECT 


ON COLUMNS, 

NON EMPTY 



ONLY_ASCENDANTS )) } 

ON ROWS 

FROM [JUICE] 

Variables 

An MDX SELECT statement in SAP HANA enables you to send values for variables defined within modeling views. 

Analytic and calculation views can contain variables, that can be bound to specific attributes. When calling the 

view, you can send values for those variables. These variables can be used, for example, to filter the results. 

SAP HANA supports an extension to MDX whereby you can pass values for variables defined in views by adding a 

SAP Variables clause in your select statement. Here is the syntax for a Select statement: 

: [WITH ] 

SELECT [[,...]] 

FROM 

[WHERE 

SAP VARIABLES: [[,] …]] 

: [] 

: INCLUDING | EXCLUDING 

: = | > | >= | < |


[VAR_TARGET_CURRENCY] including 'EUR' 

The following specifies an interval for variable VAR_K2. 

SELECT NON EMPTY 

{ 

[K2].[K2].Members 

}ON ROWS 

FROM [MINI_C1_VAR_SIMPLE] 

WHERE [Measures].[M3_CONV] 

SAP VARIABLES [VAR_K2] including [K2].[K2].&[122]:[K2].[K2].&[221] 

Metadata on Variables in Views 

SAP HANA includes the following set of tables that contain information about the variables defined for views: 

● BIMC_VARIABLE 

● BIMC_VARIABLE_ASSIGNMENT 

● BIMC_VARIABLE_VALUE 

● BIMC_VARIABLE_ODBO (virtual table) 

The tables enable, for example, an application to retrieve the variables defined for a view and create a user 

interface so the user can enter values. 

368 

P U B L I C 




15 SAP HANA Developer References 

The SAP HANA Developer's Guide comes with the following language, API and other references. 

Name Link 

SAP HANA SQL Reference http://help.sap.com/hana/html/sqlmain.html 

SAP HANA SQLScript Reference http://help.sap.com/hana/hana_dev_sqlscript_en.pdf 

SAP HANA System Tables and Monitoring Views 

Reference 

http://help.sap.com/hana/html/monitor_views.html 

SAP HANA R Integration Guide http://help.sap.com/hana/hana_dev_r_emb_en.pdf 

SAP HANA Business Function Library (BFL) Reference http://help.sap.com/hana/hana_dev_bfl_en.pdf 

SAP HANA Predictive Analysis Library (PAL) Reference http://help.sap.com/hana/hana_dev_pal_en.pdf 

SAP HANA XS JavaScript Reference http://help.sap.com/hana/jsapi/index.html 


SAP HANA Developer References 

P U B L I C 


www.sap.com/contactsap 


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