DB2 UDB for z/OS Version 8 Performance Topics - IBM Redbooks

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EVE.EXT = 'ADD BILL' AND EVE.TXC = 'IBIA0102' In the query match with the predicates EVE.EXT = 'ADD BILL' AND EVE.TXC = 'IBIA0102' In the MQT due to join predicates. The predicate COV.CVT = 'P' 3.2.5 Conclusions filters to one aggregation in the MQT because of GROUP BY COV.CVT. The measurements show a performance improvement in elapsed time from 10.5 sec. to 0.91 sec. (about 91%) when using the MQT. Note that an expression like (A+B)*C cannot be derived from A*C+B*C. MQT considerations ► All MQTs and their indexes are dropped if their associated base tables are dropped. ► No primary keys, unique indexes or triggers are allowed on MQTs. ► Design issues between a few generic MQTs and many more specialized MQTs: – Trade off between query performance and MQT maintenance. – Identify a set of queries which consume a lot of resource. Design MQTs for the set of queries as a starting point. Example: Top queries that consume a large amount of resources. ► Automatic query rewrite is done at query block level by the DB2 optimizer. ► MQTs are not used for short running queries. ► Query rewrite works for both star join and non-star join queries. ► Code the predicates in the query in exactly the same way as they are in the MQT fullselect. Exception: The order of the items in the IN list predicate does not need to be in exactly the same order. MQTs can be created as a precomputed join, sort or aggregation, and reused by DB2 query rewrite in dynamic SQL to improve the execution of long running queries in the Data Warehouse environment, providing largely reduced elapsed time and CPU time. ► Query rewrite time seems reasonable for simple queries. ► Query rewrite time grows reasonably when the number of eligible MQTs increases. ► Query rewrite works. The query result can be obtained directly from the MQT or derived from the MQT. ► Query rewrite can select the best MQT from a set of qualified MQTs. ► Up to 100 times query performance improvement is observed; simple examples with tables that are not so large, show improvement of 22x, 31x, and 47x in elapsed time and 70x, 236x and 117x in CPU time. 52 DB2 UDB for z/OS Version 8 Performance Topics
The most important factor in the return on investment on MQTs remains the frequency of utilization, and, therefore, a balance of how specialized the MQT is and how well it performs versus the range of applicability. 3.2.6 Recommendations MQTs allow more flexibility for the physical data base design of tables at the detailed level (sometimes known as atomic level) in a corporate data warehouse. The base tables can be more normalized, closer to the conceptual model, and the performance issues of long running queries involving joins, summarizations, and subqueries can be resolved when materialized as MQTs. Plan MQTs for the top consuming queries, not for all queries. Use MQTs to aggregate results based on the most used predicates joining large tables and allow the DB2 optimizer to use regrouping, predicate matching and expression derivation. Multi-dimensional applications can gain benefits by using MQTs, when queries have opportunities for regrouping. If you can identify these cases, the same MQT can be reused in many different queries. A good case is when a new table in the DB2 work file as a result of join is scanned a large number of times in a nested loop join: MQTs can be indexed. The use of MQTs can potentially provide huge savings in a data warehouse environment. It is good for queries, but not for OLTP due to the extra cost for BIND. For large MQTs, remember to: ► Use segmented table spaces because of the almost instantaneous mass delete in REFRESH TABLE. ► Execute RUNSTATS after REFRESH for good access path selection; otherwise, DB2 uses default or out-of-date statistics. Keep the number of MQTs for a base table down to an acceptable number to avoid the extra cost of BIND time due to the large number of MQTs eligible for query rewrite, as well as the processing necessary for the maintenance of MQTs. For a simple query the measured overhead is about 0.4 ms to examine each qualified MQT. When creating a user-maintained materialized query table, initially disable query optimization. Otherwise, DB2 might automatically rewrite queries to use the empty materialized query table. 3.3 Star join processing enhancements 3.3.1 Star schema In this section we describe how, in DB2 V8, the execution of star join is improved by: ► Access path enhancements ► Better estimates of the filtering effect of dimensions ► Use of sparse indexes in cache for materialized snowflakes ► Use of in-memory work files The star schema data model is often used in data warehouses, data marts and OLAP. The representation of a star schema is shown in Figure 3-15. Chapter 3. SQL performance 53
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ibm.com/redbooks Front cover DB2 UD
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Note: Before using this information
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2.5.3 Increased number of deferred
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4.5.2 Conclusion . . . . . . . . .
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7.4.1 ODBC Unicode support . . . .
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x DB2 UDB for z/OS Version 8 Perfor
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3-48 Consistency query - 31 New . .
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xiv DB2 UDB for z/OS Version 8 Perf
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8-5 CF Request Batching - DB2 CPU .
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xviii DB2 UDB for z/OS Version 8 Pe
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Trademarks The following terms are
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Added information The following APA
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► Added reference to June 15, 200
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Michael Parbs is a DB2 Specialist w
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Hugh Smith Jim Teng John Tobler Yoi
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xxx DB2 UDB for z/OS Version 8 Perf
Page 34 and 35: 1.1 Overview 1.1.1 Architecture IBM
Page 36 and 37: - Column data type changes can be d
Page 38 and 39: 1.1.3 Data warehouse 1.1.4 Performa
Page 40 and 41: Volatile (or cluster) tables, used
Page 42 and 43: In this chapter we anticipate the a
Page 44 and 45: 2.1.3 I/O time 2.1.4 Virtual storag
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Page 48 and 49: application that can have great pot
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Page 58 and 59: Macro Parameter Old value New value
Page 60 and 61: 28 DB2 UDB for z/OS Version 8 Perfo
Page 62 and 63: ► Parallel sort enhancement Paral
Page 64 and 65: Characteristics of the host variabl
Page 66 and 67: 3.1.4 Performance Update 10 rows us
Page 68 and 69: ► Complexity of the fetch. The fi
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Page 72 and 73: 3.2.1 Creating MQTs MQTs compared t
Page 74 and 75: Special register CURRENT REFRESH AG
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Page 78 and 79: Figure 3-9 MQTs and short running q
Page 80 and 81: ► The elapsed time is 22 times sm
Page 82 and 83: Figure 3-13 Regrouping on MQT resul
Page 86 and 87: Star Schema Figure 3-15 Star schema
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Page 90 and 91: Star join access path without a spa
Page 92 and 93: 3.3.4 Performance Sparse index for
Page 94 and 95: V8 Star Join Access Path Figure 3-2
Page 96 and 97: 3.3.5 Conclusion Star join workload
Page 98 and 99: . SELECT * FROM PAOLO.TORDER WHERE
Page 100 and 101: But not all mismatched numeric type
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Page 104 and 105: Query performance problem Lack of m
Page 106 and 107: 3.5.1 Performance SORTDEVT SYSDA IN
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Page 110 and 111: Mismatched data types SELECT COUNT(
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Page 120 and 121: 100 Inserts activated trigger 100 t
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Page 124 and 125: stores the selected columns from ea
Page 126 and 127: While there is no optimistic lockin
Page 128 and 129: FETCH FROM Figure 3-45 FETCH syntax
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Static updatable cursor You can see
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Multi-row FETCH with a static curso
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3.12.5 Conclusion Multi-row FETCH a
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While, for or SELECT ... FROM ...
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3.14.2 Conclusion Percent reduction
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3.15.1 Installation commands. Of co
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Figure 3-47 Explain of the old cons
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in ms = 1 and the CPU cost is 16 se
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Figure 3-50 Suggested RUNSTATS stat
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Looking at the explanation, we can
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The Plug-In Options screen of Stati
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Before the introduction of MQTs, DB
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126 DB2 UDB for z/OS Version 8 Perf
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► Larger VSAM CI sizes: DB2 V8 in
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4.1.1 Performance support caused al
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Regression is about 5% better than
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The results indicate no significant
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Important: 4.1.2 Conclusion If you
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However, the combined impact of oth
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Frees up space below the bar for ot
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from the hiperpools, they were not
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So, we advise you to not overalloca
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See 4.3, “Monitoring DBM1 storage
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Table 4-4 System storage configurat
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Stack 11356 21033 85% 8648 19799 12
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KB 600 500 400 300 200 100 0 Figure
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For the same buffer pool size and o
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4.2.3 Conclusion Nondistributed per
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Important: With PTFs UK04394 (DB2 V
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- DATASPACE BP CONTROL BLOCKS = 0 M
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The EXTENDED REGION SIZE (MAX) is t
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RDS OP POOL (MB) N/A RID POOL (MB)
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As you can now appreciate, it is im
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Megabytes A V7 Customer DBM1 Thread
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4.5.1 Performance The most buffer p
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4.6.1 Performance maintained in a 2
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4.6.2 Conclusion We can conclude th
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service for Unicode conversions, an
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overcome this, when DB2 Connect is
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INSERT HV1 1200 HV2 1200 SELECT HV1
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AIX C-program Conversion Routines P
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4.7.1 Performance The improvements
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In October 2003, a new enhancement
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UseServerEncoding data source prope
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4.8.1 Performance 4.8.2 Conclusion
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Multilevel security with row-level
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► The security level that defines
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DB2 must call RACF for this dominan
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4.9.2 Conclusion The CPU increase c
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4.10.1 Performance VSAM does not kn
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4.10.2 Conclusion 4.10.3 Striping A
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5 4 3 2 1 0 9109TLLB 4 Parallel DB2
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This message is completed with the
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This enhancement is introduced by P
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This record is activated by: -START
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an online transaction with very sim
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5.1 System level point-in-time reco
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BACKUP SYSTEM During backup DB2 rec
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Figure 5-1 FRBACKUP PREPARE elapsed
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Figure 5-4 BACKUP SYSTEM FULL measu
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5.1.2 Conclusion The BACKUP SYSTEM
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Figure 5-7 shows the sliding scale
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Maybe you have implemented a space
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For dynamically prepared queries, D
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► CHAR(8) to VARCHAR(8) ► CHAR(
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Before ALTER INDEX add column, a ta
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30 25 20 15 10 Figure 5-12 FETCH CP
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Percent of index pages Avg. Index L
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300 250 200 time in seconds 150 100
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REORG REBALANCE We executed and mea
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5.4 Volatile table 5.4.1 Conclusion
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If explicit clustering for a table
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Load table of 20M rows, 10 partitio
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Times in seconds 20 18 16 14 12 10
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RUNSTATS INDEX PARTITION of a DPSI
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Note that when the qualified partit
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► “NO” - Values in such colum
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5.6.10 Support for more than 245 se
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6.1 Online CHECK INDEX Online CHECK
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SORTOUT DD UNIT=SYSDA,SPACE=(CYL,(5
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- SORT 6 indexes in parallel - CHEC
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make DB2 take the maximum paralleli
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6.3 LOAD and UNLOAD delimited input
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6.3.2 Conclusion We measured the CP
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Options for cardinality and distrib
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► Number of column groups: 1 ►
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cases is the total time of RUNSTATS
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6.4.5 Conclusion Statistics Advisor
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goals for end-user services. We sho
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alanced across all members. With th
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method. Prior to DB2 V8 those array
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when compared to DB2 V7. At the ser
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7.2.2 Performance - Distributed cli
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Recommendation If you currently do
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► The DB2 Universal JDBC type 4 D
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WebSphere z/OS - DB2 z/OS V8 - Serv
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DB2 Universal Type 4 Driver - JDBC
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Use DB2 Connect when a high amount
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JCC Type 4 Direct 4:3 Concentration
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The SYSIBM.INDOUBT table and the pa
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Batch updates A batched update is a
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Example In DB2 V8 SQL/XML publishin
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INSERT INTO PUB_TAB(DOC) SELECT XML
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7.5.3 Conclusion The new XML publis
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A second role of the managed server
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7.6.3 Performance The following inf
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Impact on coupling facility: You do
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Table 8-1 shows extracts from DB2 P
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and secondary GBP structures have t
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DB2 member already has the table sp
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8.2.1 Performance We ran a number o
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esolve any contention. This extra a
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There is also no need to use RELEAS
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Table 8-12 DB2 I/O CI Limit Removal
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8.5 Miscellaneous items In this sec
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DB2 V8 improves Restart Light. If i
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9.1 Unicode catalog DB2 for z/OS su
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that all applications are converted
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- CLASST: Specifies the threshold a
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From these measurements we observe
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Class 1 CPU time (MSEC) 200 150 100
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dynamic statement cache. If activat
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that everything is ready. This step
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Table Number of rows SYSDATABASE 75
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In Figure 9-7 we describe the perfo
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Old - Query 5 New - Query 5 CPU (se
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Query 35 36 Old DSNTESQ CPU 1 hr 1
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10.1 DB2 Estimator DB2 Estimator V8
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- REAL AND AUXILIARY STORAGE This i
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Another use is during back out of a
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In DB2, the IBM Data Encryption too
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The utilities ran on a G7 Turbo wit
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time Figure 10-1 DB2 HPU vs. UNLOAD
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DSNTIAUL with multi-row fetch The r
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A.1 Maintenance for DB2 V8 The APAR
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APAR # Area Text PTF and Notes PQ88
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APAR # Area Text PTF and Notes PK21
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B.1 DB2 PE Storage Statistics trace
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Storage heading Description 24 BIT
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C.1 DB2 SQL PA additional reports N
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|is the last matching predicate. Ap
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|ANL6052I *** NOTE: | |This index i
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PREDICATE ANALYSIS ----------------
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D.1 DB2 EXPLAIN EXPLAIN describes t
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Table D-2 PLAN_TABLE contents and b
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Column Type Content SORTC_ORDER BY
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Column Type Content OPTHINT CHAR(8)
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D.1.3 DSN_FUNCTION_TABLE You can us
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Example: D-1 Creating DSN_STATEMENT
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Column Type Content BIND_QUALIFIER
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ICF integrated catalog facility ICF
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► DB2 UDB for z/OS V8: Through th
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character set 174 CHECK DATA 262 CH
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Equi-join predicates 54, 402 Equiva
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MINSTOR 145-146 Mismatched data typ
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PQ84160 378, 387 PQ85764 387 PQ8584
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Sort tree nodes 144 SORTDATA 268 SO
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306 Universal Driver for SQLJ and J
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DB2 UDB for z/OS Version 8 Performa
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