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

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Figure 8-13 Single statistical record - DB request times How do you determine which table? If the job is still running, you can check Global Work Process Overview (SM66) to determine which table is being processed for a specific user and a specific job. If the job is no longer running, you can check which table is being processed in the SM37 job of the process chain graphical view. See Figure 8-14. Figure 8-14 Display current work process activities from SM66 152 Best Practices for SAP BI using DB2 9 for z/OS
Alternatively, if temporary trace is permitted for individual analysis, there is an SAP profile parameter stat/tabrec that can be activated to get more statistics on table access or transactions. You can change the online parameter stat/tabrec, which specifies the maximum number of table access statistics subrecords that the kernel can write for each transaction step. The N tables with the highest DB request time for each dialog step are stored. If you only want to activate the table access statistics for specific transactions, you can specify a maximum of five transactions in the online parameters stat/tcode1 to stat/tcode5. The table access statistics are then only produced for these transactions. After tracing is done, it should be set to 0 (zero) at all times. Otherwise, the number of statistics records rises greatly, which can lead to performance problems in the statistics collector. To change parameter/tabrec online: 1. Start the workload monitor by calling transaction ST03. 2. Choose Expert → User Mode. 3. Choose Collector & Perf. Database → Statistics Records and File → Online Parameters → Dialog Step Statistics. 4. The system displays the Change Runtime Parameters for Statistics Collection dialog window. To look at table access statistics: 1. Start the workload monitor by calling transaction ST03. 2. Choose the user mode. 3. In the Workload tree, choose the instance to be analyzed and the time period. 4. Choose Analysis Views → Table Access Statistics. At this point, information from ST03, RSMO, RSPC, and STAD transactions should provide you with a general idea of where the potential cause is. Now what can you do to alleviate it? If extraction takes the most elapsed time For this condition you can do a few things on the source data and source system to improve extraction. Source data can be from an earlier system, flat file, or R/3 system. Generally, these are beyond your control, especially an earlier system, which may have slow disks, not enough CPUs, and less memory. However, you can have some influence on loading from a flat file and from a R/3 system, as described here. Chapter 8. Query and Load performance 153
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Best Practices for SAP BI using DB2
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Note: Before using this information
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4.4 Extended sparse index and in-me
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11.3 SAP BI database and InfoCube l
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viii Best Practices for SAP BI usin
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Trademarks The following terms are
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The team that wrote this IBM Redboo
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Thanks to these authors from the Pr
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► Send your comments in an e-mail
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1.1 Product overview The business w
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In general, database administrators
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► Horizontal growth is achieved b
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8 Best Practices for SAP BI using D
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2.1 BI architecture Figure 2-1 show
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New term Old term Analysis authoriz
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negative values means missing stati
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- When calculating database statist
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If you specify a partitioning schem
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Important: Never partition a PSA ta
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Figure 2-10 DPSIs versus NPSIs Figu
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Finally, Figure 2-12 explains which
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Figure 2-14 shows how the snowflake
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► Realignment This refers to the
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3.1 Base recommendations - SAP BI i
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the F- fact table, the E- fact tabl
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34 Best Practices for SAP BI using
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4.1 Dynamic index ANDing for star s
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Figure 4-2 and Figure 4-3 on page 3
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4.2.1 Processing RUNSTATS for BI ta
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RUNSTATS will then be called over t
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DSNU610I -DB2T 081 16:36:03.85 DSNU
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Often the single-value based freque
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Several things worth noting are:
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The unit of a value specified to MX
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condition, generated by SAP BI upon
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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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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
Page 120 and 121: ► Use DPSIs for the cube’s E- f
Page 122 and 123: 7.1 Differences between DataStore a
Page 124 and 125: Figure 7-1 shows the initial status
Page 126 and 127: 4. By selecting the Create button,
Page 128 and 129: Partitioning and clustering are bot
Page 130 and 131: 7.4.2 Choosing and changing the clu
Page 132 and 133: 7.4.4 Partitioning a DataStore obje
Page 134 and 135: From the ABAP Dictionary: Utility f
Page 136 and 137: Figure 7-9 DB2/390 Storage Attribut
Page 138 and 139: partitioning was used. The CREATE T
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Page 144 and 145: | "/BIC/DIVISION" VARGRAPHIC (00000
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Page 148 and 149: | "/BIC/CRMEM_VAL" DECIMAL (000017,
Page 150 and 151: | DDL time(___8): .........4 millis
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Page 154 and 155: 8.1 Troubleshooting general system
Page 156 and 157: You need to ascertain: ► Which us
Page 158 and 159: Further information about the subje
Page 160 and 161: 8.2 Analyzing load performance In t
Page 162 and 163: We use transaction ST03 → Expert
Page 164 and 165: Click the Details tab of the RSMO w
Page 166 and 167: Select the component of interest to
Page 168 and 169: Figure 8-11 All statistical records
Page 172 and 173: Loading from a flat file You can av
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Page 176 and 177: Note: You must activate the saving
Page 178 and 179: 5. In the right-hand panel of the w
Page 180 and 181: If your query has long run times th
Page 182 and 183: that the query runs against → Mai
Page 184 and 185: If the main component of query perf
Page 186 and 187: ► Display Statistics Data (to sho
Page 188 and 189: Select the appropriate button, ente
Page 190 and 191: Figure 8-29 Statement details To ch
Page 192 and 193: The ratio (ST04 statement cache “
Page 194 and 195: Figure 8-32 Visual Explain - SQL te
Page 196 and 197: 8.5 SAP Query Analysis Tool The SAP
Page 198 and 199: Display of sql access path SQL quer
Page 200 and 201: The access path is displayed hierar
Page 202 and 203: The table information tab shown in
Page 204 and 205: DB2 Plan Table Figure 8-42 DB2 plan
Page 206 and 207: Graphical view of each query block
Page 208 and 209: Now you see the graphical view of t
Page 210 and 211: 8.5.4 Example of using the query an
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Page 214 and 215: 9.1 The BIA architecture Figure 9-1
Page 216 and 217: Figure 9-2 BIA t-shirt sizing The B
Page 218 and 219: 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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