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

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the F- fact table, the E- fact table reference point can be accessed directly for current data, thus improving query performance. There is one exception when SAP compression can be omitted. This is the case when you are using the SAP BIA and when the compression ratio is less than 1.5. 7. Use fast deletion of table partitions. Apply SAP note 894045 to activate the fast deletion of table partitions for partitioned PSA and F- fact tables. 8. Partition E-Fact and F- fact tables. The E- fact table (result of SAP compression) can be partitioned via SAP cube maintenance, which provides greater opportunity for improved query performance and elapsed time, and also potential reduction in operational costs. Partitioning the E- fact table increases the opportunity for DB2 parallelism, which can significantly reduce the query elapsed time. Similarly, queries with time-based filtering will be able to eliminate unnecessary partitions from being accessed regardless of the filtering dimensions or indexes chosen for fact table access. These two benefits also result in greater access path stability for queries against the InfoCube. The F- fact table will be automatically partitioned by request by setting a RSADMIN parameter. In addition to improving query performance, this significantly speeds up the deletion of a request and the RUNSTATS. Details are in SAP note 860830. An additional benefit of partitioning is the ability for partition level operations such as COPY utility, REORG, or RUNSTATS to be invoked by the DBA. With time-based partitions, historical partitions do not require further REORG/RUNSTATS because their data will not change over time. An increase in E- fact table size should not result in a significant increase in operational maintenance costs. For these reasons we recommend partitioning the E- fact tables and using InfoCube compression. 9. Use DB2 HW compression. DB2 hardware compression is one of the strengths that differentiates DB2 on System z from other platforms. Compression rates of 70% and greater are possible for large SAP BI objects, such as fact tables, data store objects, and large aggregates. The four main benefits of compression include: – Reduced disk space – Improved elapsed time for sequential processing (for example, queries, copy utility) 32 Best Practices for SAP BI using DB2 9 for z/OS
– Improved bufferpool hit ratio (more rows per page) – Reduced log data volume where there is insert-intensive processing With the compression dictionary moving above the 2 GB bar in V8, which may result in virtual storage relief for DBM1, there is more motivation for customers to exploit System z strong compression capabilities. 10.Use the SAP transaction/programs to remove unused data. Master data tables can be preloaded with SAP default data and loaded with data by a user that never gets utilized. This unused data can disrupt the cost-based optimizer's estimates of how many rows will be returned, or can result in this data being unnecessarily retrieved for every query involving that table. We recommend purging unwanted data using the following methods: – Trancode RSRV for dimension data. – The program to delete master data is RSDMD_DEL_BACKGROUND or functional module RSDMD_DEL_MASTER_DATA. – The program RSCDS_DEL_OLD_REQUESTS removes obsolete rows from F- fact tables (SAP note 609164). Chapter 3. Top ten SAP BI recommendations 33
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 22 and 23: In general, database administrators
Page 24 and 25: ► Horizontal growth is achieved b
Page 26 and 27: 8 Best Practices for SAP BI using D
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
Page 36 and 37: If you specify a partitioning schem
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
Page 46 and 47: ► Realignment This refers to the
Page 48 and 49: 3.1 Base recommendations - SAP BI i
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Page 54 and 55: 4.1 Dynamic index ANDing for star s
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Page 58 and 59: 4.2.1 Processing RUNSTATS for BI ta
Page 60 and 61: RUNSTATS will then be called over t
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Page 64 and 65: Often the single-value based freque
Page 66 and 67: Several things worth noting are:
Page 68 and 69: The unit of a value specified to MX
Page 70 and 71: condition, generated by SAP BI upon
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Page 74 and 75: 5.1 Load PSA In this section we dis
Page 76 and 77: 5.1.1 Load PSA To load data into th
Page 78 and 79: After the source system, the DataSo
Page 80 and 81: Note the available tabs (registers)
Page 82 and 83: Figure 5-8 shows the provided optio
Page 84 and 85: Figure 5-10 shows the following:
Page 86 and 87: The PSA table name is created autom
Page 88 and 89: 5.1.4 PSA partitioning Partitioning
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Page 92 and 93: An InfoCube, whether data target or
Page 94 and 95: 6.1 Types of InfoCubes Data targets
Page 96 and 97: After selecting at least one time d
Page 98 and 99: 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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134 Best Practices for SAP BI using
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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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