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

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AND "/BIC/AZOSASALE00"."PLANT" = "/BIC/XZMATLPLNT"."PLANT" AND "/BIC/AZOSASALE00"."ACCNT_ASGN" IN ('00', '01', '04', '06') AND "/BIC/AZOSASALE00"."CALMONTH" BETWEEN '200311' AND '200404' AND "/BIC/AZOSASALE00"."CURTYPE" = 'B0' AND "/BIC/XZMATLPLNT"."OBJVERS" = 'A' AND "/BIC/XZMATLPLNT"."S__ZMATLONLY" = 360013 The join sequence that we wish to encourage is table /BIC/XZMATLPLNT accessed first, and joined to /BIC/AZOSASALE00. Therefore, local predicates on the /BIC/XZMATLPLNT should be indexed to encourage this as the leading table to be accessed. AND "/BIC/XZMATLPLNT"."OBJVERS" = 'A' AND "/BIC/XZMATLPLNT"."S__ZMATLONLY" = 360013 Note that the OBJVERS column has only one possible value, and therefore does not provide any filtering. The only reason to add this to the index is if index-only access is desired. Table 10-1 Index recommendation The index recommendation for table /BIC/XZMATLPLNT is shown in Table 10-1. Column Reason S__ZMATONLY Required to support local filtering /BIC/ZMATLPLNT Optional to support additional joins (see 10.3.1, “Index design for post-DSO access” on page 223) PLANT Optional to support additional joins (see 10.3.1, “Index design for post-DSO access” on page 223) Only local predicates are available as index matching on the leading table accessed. Join predicates are not. Thus the index design for BIC/XZMATLPLNT incorporates the local predicate first. The join predicates are not valid as filtering predicates on the leading table (since the join value is not known when the first table is accessed), but they do provide filtering if this table is ever chosen as a non-leading table in the join sequence. The join predicates in the index ensure that the subsequent table accessed will be joined in the sequence of the index, which can improve sequential retrieval for the non-leading table data. To support /BIC/AZOSASALE00 as the second table in the join sequence, the following predicates must be considered: WHERE "/BIC/AZOSASALE00"."/BIC/ZMATLPLNT" = "/BIC/XZMATLPLNT"."/BIC/ZMATLPLNT" AND "/BIC/AZOSASALE00"."PLANT" = "/BIC/XZMATLPLNT"."PLANT" 220 Best Practices for SAP BI using DB2 9 for z/OS
Table 10-2 Indexing options Column Local or join AND "/BIC/AZOSASALE00"."ACCNT_ASGN" IN ('00', '01', '04', '06') AND "/BIC/AZOSASALE00"."CALMONTH" BETWEEN '200311' AND '200404' AND "/BIC/AZOSASALE00"."CURTYPE" = 'B0' For the non-leading tables in the join, local predicates and join predicates are treated equally from the perspective of the ability to match index columns. Equal and IN predicates must precede range (BETWEEN, LIKE, =) predicates in the index, however, since range predicates will stop the index matching, and subsequent predicates will be applied as index screening. Similarly, a second IN predicate will also force matching to stop (at the column immediately preceding the second IN list) and revert to index screening. Therefore, where possible, priority should be given to equal predicates for indexing. Whether local predicates appear before join predicates depends on whether the local predicates will always appear in the query. If so, then the preference is to order local equal and IN columns before join columns in the index. This allows these columns to be used as matching as the leading or non-leading table in a join. Also, local predicates as the leading columns will ensure that any matching access to this index (as leading or non-leading table) will be restricted to the bounds of the equal predicate, which can provide a better bufferpool hit ratio and exploitation of index lookaside. To improve flexibility of local predicates, an alternative is to partition by a commonly used local predicate. A good example is often a time-based column in a data warehouse environment. Data warehouses (including SAP BI DSO and InfoCubes) generally contain many months or years of data, but users often query only the most recent, thus making separation of current and historical (using partitioning) a wise choice. The indexing options for table /BIC/AZOSASALE00 are shown in Table 10-2. Operator Partition candidate Index column sequence CURTYPE Local = Possibly 1 Optional ACCT_ASGN Local IN No 2 Optional Mandatory/optional /BIC/ZMATLPLNT Join = No 3 Mandatory PLANT Join = No 4 Mandatory Chapter 10. Tips for SQL efficiency 221
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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
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
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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
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 240 and 241: Column Local or join CALMONTH Local
Page 242 and 243: 10.4 Indexing of InfoCubes The defa
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 268 and 269: Figure 11-10 shows that the average
Page 270 and 271: 11.5.1 Recommendations for configur
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
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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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