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

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11.2.2 Network infrastructure IBM System z9® DB2 Database Server IBM System Storage 3 x DS8300 IBM System Storage DS8300 IBM System p5 SAP BI Server IBM System x Query Load Driver The network configuration for the Jupiter environment is shown in Figure 11-2. In this diagram, you can see that the following technologies were used for our network infrastructure: FICON® channel, GbE, 10 GbE, InfiniBand®, and Fibre Channel. Figure 11-2 Jupiter network configuration Jupiter Network Configuration IBM BladeCenter® SAP BIA Server HS21 Intel Blades Connection between System z and DS8300 There were 24 FICON channel connections between System z and the three DS8300 storage systems (eight connections between System z and each DS8300 storage system). They were critical for writing data to the DB2 database during InfoCube load and reading data during the BI Accelerator index creation. Connection between System p and DS8300 There were eight Fibre Channel connections between System p and the DS8300 storage system. Multipath Subsystem Device Driver (SDD) was used. This enabled parallel access to the file systems on the DS8300 storage system. Since 232 Best Practices for SAP BI using DB2 9 for z/OS GPFS Storage Nodes IBM System Storage 2 x DS8300 Legend (type of connection) Fibre Channel Gigabit Ethernet InfiniBand FICON Channel
the input files for the InfoCube load resided on this storage system, it was critical to get the maximum bandwidth to the storage system. Connection between System p and System z There were eight 10 Gigabit Ethernet (GbE) lines between System p and System z. We could have used fewer than eight connections. However, the precise data rate requirement was not known at the beginning of the project. It was safer to over-configure than to under-configure, to ensure that there were no network constraints during InfoCube load and during BI Accelerator index creation phases. The data rate was not expected to be close to the aggregated bandwidth of these eight connections. Multiple connections mitigated (but did not totally prevent) delays due to latency from channel busy, hardware implementation, and physical media. To simplify the environment, our System p was configured as a single system image. Since multiple SAP application servers can run in one partition, our Jupiter project employed multiple instances for a more realistic customer environment. This affected our network implementation, because each SAP application server can use only one SAPDBHOST connection, which is usually associated with one physical network connection. To make use of all eight connections, we combined them into one virtual connection using a virtual IP address (VIPA). This approach utilizes network trunking, such as EtherChannel or MultiPath. EtherChannel is supported on System p but not on System z. So instead we used a MultiPath network connection, which has similar functionality to the EtherChannel. Example D-1 on page 326 shows our setup definition of static multipath. Each connection is configured with its own subnet on separate VLANs. This ensures that traffic is sent and returned over the same physical connection, and also provides better analysis and monitoring of performance data. Also, a jumbo frame size was configured for the large block sizes transmitted. For load balancing, there is an algorithm to distribute traffic to all connections when several are combined into one virtual connection. This method provides higher availability, since another available physical connection associated with the virtual connection can be used if one of the physical connections is down. For details and guidance on high availability network implementation, refer to SAP on IBM System z: High Availability for SAP on IBM System z Using Autonomic Computing Technologies, SC33-8206. Connection between System p and blade cluster There was one 10 GbE connection from System p to our network switch, and an EtherChannel of four GbE connections from the switch to each blade chassis. Within the chassis, there was one GbE interface for each of the 14 blades within Chapter 11. Project Jupiter: large BI Accelerator scalability evaluation 233
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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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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 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
Page 246 and 247: 11.1 Background To be more competit
Page 248 and 249: 11.2.1 Hardware and software config
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
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
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Page 296 and 297: Figure 12-12 on page 279 shows the
Page 298 and 299: 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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