Best Practices for SAP BI using DB2 9 for z/OS - IBM Redbooks

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In general, database administrators (DBAs) are not responsible for some of the processes discussed in this book, for example, analyzing and defining SAP aggregates (which are summary tables optimized for specific queries). It is important, however, for DBAs to be aware of these activities, since aggregate analysis and definitions should generally be done before solving a problem, when the root problem is a lack of aggregates. Missing or improperly defined aggregates can cause increased CPU usage, excessive I/O activity, and increased DB2 memory usage. Evaluation of query performance for SAP BI requires both SAP information (such as query performance indicators RSDDSTAT, or aggregate valuation and definition in RSA1) and also DB2 indicators (such as cached statement statistics, or using DB2 EXPLAIN PLAN to analyze the access path used by DB2). Likewise, an SAP BI administrator may not be familiar with the technical issues of DB structure, SQL evaluation, and DB2 parallelism capabilities. But if, after evaluating the data model and aggregates, there are still performance problems, the SAP BI administrator can work with the DB2 DBA to evaluate the DB2-related changes to address performance problems. Not all problems can be solved with aggregates, and the BI administrator may need to turn over some problems to the DB2 DBA. 1.3 Why run SAP BI on IBM System z The z in System z signifies zero downtime. System z hardware is designed to meet the world’s most critical computing needs. Reliability characteristics such as dynamic CPU sparing, logical partitioning, error detection and correction, and hardware cryptography are built into the architecture. If the nonspecialist IBM system offers 99.99% availability, the result is only 53 minutes of unplanned downtime per year. If the sysplex gives 99.999% availability, there is only 5 minutes per year of unplanned downtime. 1.3.1 Value provided by System z, z/OS, and DB2 In this section we give an overview of the value provided by System z, z/OS, and DB2. One-stop shopping IBM provides a one-stop shop for all three components — hardware, operating system, and database. 4 Best Practices for SAP BI using DB2 9 for z/OS
7 x 24 application availability 99.999% database reliability offers resilience to unplanned outages. Such database availability requires: ► A robust operating system. z/OS has more than one million lines of recovery code, and has been evolving since 1966. ► Reliable hardware with internal redundancy and error correction logic. z/990 has a mean time to failure (MTF) greater than 30 years. ► That a processor continues to operate after the loss of an engine. ► That there is no single point of failure (SPOF). This support is provided by Parallel Sysplex® with DB2 Data Sharing. ► Coupling Facilities, which fully support structure duplexing and automated takeover. ► Reliable DBMS. DB2 has been evolving for more than 20 years and has been stress-tested by more than 8,000 of the largest companies in the world. ► Dynamic CPU sparing. At a minimum, one of the z/Series processing units is designated as a spare. If a running CPU chip fails and the instruction retry is unsuccessful, the spare processing unit begins executing at precisely the instruction where the other failed. ► Activation of the spare is done completely by the hardware, enabling the system to be restored to full capacity in less than one second. Because most hardware failures requiring repair will not cause an outage at the time of failure or at the time of repair, the IBM System z achieves near-zero outage for unplanned hardware repairs. ► Minimal planned outages. This is also known as continuous operations: – Parallel Sysplex, coupled with DB2 Data Sharing and SAP Sysplex Failover, allows rolling maintenance and upgrades of hardware, z/OS, and DB2 without an outage. – DB2 Online Utilities eliminate database maintenance, which is the leading cause of planned outages in a UNIX® or Windows® environment. – All of this is further complemented by hot-pluggable features, including capacity on demand of System z and z/OS. Capacity and scalability Using a System z means that you have both vertical and horizontal capacity and scalability: ► Vertical growth is achieved through more or faster engines in a single symmetric multiprocessor (SMP) — the traditional growth path for UNIX and Windows. Chapter 1. Introduction 5
Page 1: Best Practices for SAP BI using DB2
Page 4 and 5: Note: Before using this information
Page 6 and 7: 4.4 Extended sparse index and in-me
Page 8 and 9: 11.3 SAP BI database and InfoCube l
Page 10 and 11: viii Best Practices for SAP BI usin
Page 12 and 13: Trademarks The following terms are
Page 14 and 15: The team that wrote this IBM Redboo
Page 16 and 17: Thanks to these authors from the Pr
Page 18 and 19: ► Send your comments in an e-mail
Page 20 and 21: 1.1 Product overview The business w
Page 24 and 25: ► Horizontal growth is achieved b
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Page 28 and 29: 2.1 BI architecture Figure 2-1 show
Page 30 and 31: New term Old term Analysis authoriz
Page 32 and 33: negative values means missing stati
Page 34 and 35: - When calculating database statist
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Page 38 and 39: Important: Never partition a PSA ta
Page 40 and 41: Figure 2-10 DPSIs versus NPSIs Figu
Page 42 and 43: Finally, Figure 2-12 explains which
Page 44 and 45: Figure 2-14 shows how the snowflake
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Page 64 and 65: Often the single-value based freque
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There is a separate IBM Redbooks pu
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5.1 Load PSA In this section we dis
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5.1.1 Load PSA To load data into th
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After the source system, the DataSo
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Note the available tabs (registers)
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Figure 5-8 shows the provided optio
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Figure 5-10 shows the following:
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The PSA table name is created autom
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5.1.4 PSA partitioning Partitioning
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72 Best Practices for SAP BI using
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An InfoCube, whether data target or
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6.1 Types of InfoCubes Data targets
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After selecting at least one time d
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6.2.1 Repartitioning implementation
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You will then be presented with a w
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From within the monitor you are abl
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Once your repartitioning process is
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Figure 6-14 is displayed once you h
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When you remodel an InfoProvider yo
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Figure 6-17 demonstrates how you wo
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At this step of the process you are
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6.3.2 Benefits of remodeling InfoPr
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6.4.3 Cumulative data versus non-cu
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Important: After the initial compre
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► Use DPSIs for the cube’s E- f
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7.1 Differences between DataStore a
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Figure 7-1 shows the initial status
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4. By selecting the Create button,
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Partitioning and clustering are bot
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7.4.2 Choosing and changing the clu
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7.4.4 Partitioning a DataStore obje
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From the ABAP Dictionary: Utility f
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Figure 7-9 DB2/390 Storage Attribut
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partitioning was used. The CREATE T
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, "/BIC/RECORDMODE" POSITION( 00289
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Upon completion of the job, you wil
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| "/BIC/DIVISION" VARGRAPHIC (00000
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| sql: | DELETE FROM DDSTORAGE | WH
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| "/BIC/CRMEM_VAL" DECIMAL (000017,
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| DDL time(___8): .........4 millis
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8.1 Troubleshooting general system
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You need to ascertain: ► Which us
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Further information about the subje
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8.2 Analyzing load performance In t
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We use transaction ST03 → Expert
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Click the Details tab of the RSMO w
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Select the component of interest to
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Figure 8-11 All statistical records
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Figure 8-13 Single statistical reco
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Loading from a flat file You can av
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and right-click to select the Simul
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Note: You must activate the saving
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5. In the right-hand panel of the w
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If your query has long run times th
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that the query runs against → Mai
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If the main component of query perf
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► Display Statistics Data (to sho
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Select the appropriate button, ente
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Figure 8-29 Statement details To ch
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The ratio (ST04 statement cache “
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Figure 8-32 Visual Explain - SQL te
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8.5 SAP Query Analysis Tool The SAP
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Display of sql access path SQL quer
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The access path is displayed hierar
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The table information tab shown in
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DB2 Plan Table Figure 8-42 DB2 plan
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Graphical view of each query block
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Now you see the graphical view of t
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8.5.4 Example of using the query an
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9.1 The BIA architecture Figure 9-1
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Figure 9-2 BIA t-shirt sizing The B
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From the hardware side, the BIA is
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9.7 Overview The improvement of the
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10.1 SQL efficiency for DSO Queries
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The first join predicate is "/BIC/A
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Figure 10-5 Associate local predica
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Step 3 is repeated for each master
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Using the InfoCube query example in
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The first join predicate in Figure
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Thus, we have broken down the origi
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Figure 10-14 Comparing filtering Th
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AND "/BIC/AZOSASALE00"."PLANT" = "/
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Column Local or join CALMONTH Local
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10.4 Indexing of InfoCubes The defa
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11.1 Background To be more competit
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11.2.1 Hardware and software config
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11.2.2 Network infrastructure IBM S
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the chassis for blade-to-blade conn
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As part of the pre-benchmark planni
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11.4 Test case scenarios The goal o
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Figure 11-3 explains the data flow
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In addition, each cube, especially
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Measurement results Table 11-2 prov
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Figure 11-7 shows the average CPU u
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The number of queries per hour show
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Figure 11-10 shows that the average
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11.5.1 Recommendations for configur
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12.1 Terminology: BI objects and pr
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Metadata plays a fundamental role i
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12.3 Dataflow in SAP BI Data flow i
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12.4 Information access As previous
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Predecessor Successor WW Sales Euro
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An InfoCube in SAP BI can have up t
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12.8 Aggregates 4. The dimension ta
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The next example is an aggregate th
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For example, assume that different
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can be updated into InfoCubes or ot
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Figure 12-11 shows the steps that o
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Figure 12-12 on page 279 shows the
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The content, depicted in Figure 12-
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considerably more data records are
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The nodes stand for data sources, t
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values, hierarchies, hierarchy node
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BI SAP Query Connector A resource a
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Business Intelligence Cockpit Web-b
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processors in terms of macros that
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Crystal Reports Designer Design com
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Similar to the OLAP-standard term c
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P table Master data table for time-
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The process instance contains the m
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Relational Query Model An abstracti
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SAP Business Information Warehouse
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source object element Component of
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elements to be displayed in the Web
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Web application object catalog Web
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You insert one or more queries in t
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IT scenario The environment we used
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Checks under z/OS and DB2 We recomm
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To check that the SAPCL procedure w
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List of SAP BW OSS Notes Table C-1
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SAP BI on DB2 for z/OS 390016 BW Da
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Network configuration: static multi
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START CU091060 START CU0A1070 START
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Table name Average row length Total
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Table name Average row length Total
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Parameters BPK16K0 BPK16K1 VIRTUAL
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drwxr-xr-x 3 t11adm sapsys 2048 200
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Example D-6 shows a cube index crea
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B49/S_RTNSVAL 24 DECIMAL 17 2 N 4 N
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-rw-r--r-- 1 t11adm sapsys 2084482
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-rw-r--r-- 1 t11adm sapsys 547449 2
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Online resources These Web sites ar
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Help from SAP SAP Support and downl
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C Candidates for partiioning Data W
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M master data 155, 211, 258, 277 si
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star schema 265-266 also see InfoCu
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Best Practices for SAP BI using DB2
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Best Practices for SAP BI using DB2 9 for z/OS - IBM Redbooks

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