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

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Figure 11-10 shows that the average CPU high load of SAP BI back end on System p is 87.99% and the SAP BI Accelerator on the cluster of blades is 60.08% for 25 TB on 135 blades. Figure 11-10 Multiuser reporting: average CPU load 25 TB, 135 blades 11.5 Analysis and conclusions Project Jupiter demonstrated that DB2 for z/OS coupled with the SAP BI Accelerator is an ideal solution for business information and data warehousing. DB2 for z/OS, as the premiere IBM relational database management system, offers industry-leading performance, scalability, reliability, and manageability. 250 Best Practices for SAP BI using DB2 9 for z/OS
The SAP BI Accelerator with DB2 for z/OS on IBM Server Infrastructure can deliver very fast query execution with consistent response times. This was achieved with the use of highly compressed BI Accelerator index data structures and efficient parallel in-memory query processing. During our project with 100% query off-load to BI Accelerator, the need for extensive aggregates and database indexes tuning was completely eliminated, while exploiting DB2's strength as the master data repository. Figure 11-11 3 illustrates the key performance indicators (KPIs) of our project. Linear Scalability: Data Volume vs. Resources Total DB Size 25 TB 15 TB 5 TB Legend: Index creation throughput Multiuser reporting throughput avg. report response time avg. # records touched per report 0.6 TB / h 100,000 reports / h 4.5 sec 6 M records 1.1 TB / h 101,000 reports / h 4.2 sec 22 M records 27 blades 81 blades 135 blades BIA Resources Figure 11-11 Linear scalability: data volume versus resources 1.3 TB / h 101,000 reports / h 4.2 sec 37 M records Before our project, the largest supported SAP BI Accelerator configuration was the XLarge size that consists of up to 28 blades. Our results showed BI Accelerator query scalability up to 135 (plus 5 spare) blades with no observable scalability limits. Likewise, the BI Accelerator Index load rate can be sustained above 1 TB per hour. These impressive throughput results for BI Accelerator index load as well as for query data retrieval will readily meet the stringent requirements of the largest BI customers today. 3 This information was taken from a presentation by Thomas Becker of SAP, titled, “JUPITER: 25TB Showcase for SAP NetWeaver BI Accelerator and IBM Server Infrastructure,” at the IBM Poughkeepsie Customer Briefing Center on December 13th, 2007. Chapter 11. Project Jupiter: large BI Accelerator scalability evaluation 251
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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
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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
Page 218 and 219: From the hardware side, the BIA is
Page 220 and 221: 9.7 Overview The improvement of the
Page 222 and 223: 10.1 SQL efficiency for DSO Queries
Page 224 and 225: The first join predicate is "/BIC/A
Page 226 and 227: Figure 10-5 Associate local predica
Page 228 and 229: Step 3 is repeated for each master
Page 230 and 231: Using the InfoCube query example in
Page 232 and 233: The first join predicate in Figure
Page 234 and 235: Thus, we have broken down the origi
Page 236 and 237: Figure 10-14 Comparing filtering Th
Page 238 and 239: AND "/BIC/AZOSASALE00"."PLANT" = "/
Page 240 and 241: Column Local or join CALMONTH Local
Page 242 and 243: 10.4 Indexing of InfoCubes The defa
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Page 246 and 247: 11.1 Background To be more competit
Page 248 and 249: 11.2.1 Hardware and software config
Page 250 and 251: 11.2.2 Network infrastructure IBM S
Page 252 and 253: the chassis for blade-to-blade conn
Page 254 and 255: As part of the pre-benchmark planni
Page 256 and 257: 11.4 Test case scenarios The goal o
Page 258 and 259: Figure 11-3 explains the data flow
Page 260 and 261: In addition, each cube, especially
Page 262 and 263: Measurement results Table 11-2 prov
Page 264 and 265: Figure 11-7 shows the average CPU u
Page 266 and 267: The number of queries per hour show
Page 270 and 271: 11.5.1 Recommendations for configur
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Page 274 and 275: 12.1 Terminology: BI objects and pr
Page 276 and 277: Metadata plays a fundamental role i
Page 278 and 279: 12.3 Dataflow in SAP BI Data flow i
Page 280 and 281: 12.4 Information access As previous
Page 282 and 283: Predecessor Successor WW Sales Euro
Page 284 and 285: An InfoCube in SAP BI can have up t
Page 286 and 287: 12.8 Aggregates 4. The dimension ta
Page 288 and 289: The next example is an aggregate th
Page 290 and 291: For example, assume that different
Page 292 and 293: can be updated into InfoCubes or ot
Page 294 and 295: Figure 12-11 shows the steps that o
Page 296 and 297: Figure 12-12 on page 279 shows the
Page 298 and 299: The content, depicted in Figure 12-
Page 300 and 301: considerably more data records are
Page 302 and 303: The nodes stand for data sources, t
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Page 306 and 307: BI SAP Query Connector A resource a
Page 308 and 309: Business Intelligence Cockpit Web-b
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Page 314 and 315: Similar to the OLAP-standard term c
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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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