Performance rule violations usually result in increased CPU or I/O, time to fix the mistake, and ultimately, a cost to the business unit.

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1 Is your database application experiencing poor response time, scalability problems, and too many deadlocks or poor application performance? One or a combination of zparms, database design and application coding techniques can cause these performance issues. There are many new DB2 9 and DB2 10 techniques, system parameters, database design, and application coding methods to avoid problems and revitalized your older databases performance. This presentation will take you through the discoveries found during recent performance reviews and you will learn about the latest recommendations for fixing your database and application performance problems. David Beulke is an internationally recognized DB2 consultant, author and lecturer. He is known for his extensive expertise in database performance, data warehouses and internet applications. He is Past President of the International DB2 Users Group (IDUG), a member of IBM DB2 Gold Consultant program, a columnist for DB2 Magazine, co-author of the IBM DBA z/os DB2 Administration Certification exam, co-author of the Business Intelligence Certification exam, and former instructor for The Data Warehouse Institute (TDWI). He also writes a DB2 Family performance tips Blog at His performance tuning expertise has helped clients with their mainframe, UNIX and Windows DB2 systems. His clients have saved millions of dollars in CPU charges and avoided unnecessary hardware upgrades and dramatically reduced their CPU application demands.

2 Sign up for these great classes September 29 th and 30 th today! For more information on these classes go to the web at: Performance rule violations usually result in increased CPU or I/O, time to fix the mistake, and ultimately, a cost to the business unit. What will the cost be? Depends on the mistake and the frequency of the mistake. The following presentation will show real case studies of the actual cost of the mistakes.

3 Notes Longer development time, issue identification and problem resolution result from the different standards for COBOL and Java management. Many of the great procedures that were developed within the IT corporate structure during the early days of DB2 development were for COBOL applications

4 The ranks of the DBAs are under pressure to install, service and monitor more systems, database and applications. These demands make their days more hectic and less inclined to catch the design, table, index or implementation issues. These performance issues along with the consolidation demands put on application development environments also makes research and analysis for click related performance difficult. DBAs and application developers need to work together to monitor the performance of the overall system, the applications and any new processes. Now that the Java applications are supporting the web applications analysis and SQL statements need to be tracked back to a particular click activity. Capacity planners need to understand the application, the processing the impact of a click in the environment. This requires the capacity planner to have a much more fine grained capacity estimate for the web activities.

5 The ranks of the DBAs are under pressure to install, service and monitor more systems, database and applications. These demands make their days more hectic and less inclined to catch the design, table, index or implementation issues. These performance issues along with the consolidation demands put on application development environments also makes research and analysis for click related performance difficult. DBAs and application developers need to work together to monitor the performance of the overall system, the applications and any new processes. Now that the Java applications are supporting the web applications analysis and SQL statements need to be tracked back to a particular click activity. Capacity planners need to understand the application, the processing the impact of a click in the environment. This requires the capacity planner to have a much more fine grained capacity estimate for the web activities.

6 With the increased workload and the number of systems per DBA that need to be supported the system settings for DB2 subsystems only get reviewed during version migrations. This leads to generic settings, parameter issues and settings that are not appropriate or customized for the workload. These incorrect settings lead to more suspends, deadlocks and timeouts for your applications and everything slows down.

7 Within any given environment there are always performance issues. The problem only is the DBAs and application support developers are too busy to address them. Within this screen shot of the performance monitor, it shows huge problems with several aspects of the DB2 workload. The number of SUSPENDS, LOCK ESCALATIONS, ABORTS and Database EXCEPTIONS point to major issues within the performance of the system and the application. Within application coding there are also many considerations. Cursor handling continues to be a challenge for many programmers. The processing DECLAREs the cursor, OPENs the cursor, should FETCH many rows and then CLOSE the cursor. Within this client the applications were not performing all the steps for proper SQL cursor processing. The application processing was DECLAREing and OPENing and FETCHing from the cursors but the application was not CLOSEing the cursor. This causes the cursor resources to be left in the system and then timed out based on the system settings. This causes a huge amount of overhead for the overall system and should be fixed in the system.

8 The RID Pool or Row Id pool is a mechanism within the DB2 buffer pool system that is used to temporary hold a row id (row location information) of data that an application requested from the DB2 system. There is only a limited amount of space for the RID Pool and sometimes too many concurrent programs need to use it. High usage of the RID pool is typical of expensive access paths or a large number of program executing in a single DB2 system. These RID Pool Failures present a problem because when the RID Pool overflows DB2 is required change the access of the SQL from an index access to a tablespace scan. Changing to a tablespace scan can be very CPU and I/O intensive. The number of RID pool failures varies tremendously with many happening during the evaluation period averaging over 550 per day during this time period. Large robust systems are exposed to RID pool failures but should never experience any if possible. Working with several companies I have fixed many RID Pool problem situations removing the need for a tremendous amount of CPU and I/O resources. Since the system is experiencing tremendous CPU and I/O requirements already it is difficult to analyze the RID Pool failures to see which tablespace the row access is being changed to a tablespace scan. Also, since there are a large number of DB2 packages and plans that are doing poor access paths, it is difficult to key in on the applications causing these problems. Detailed analysis would be needed against the various program access methods and then discovering the tables or indexes causing the issues.

9 RI is critical for the overall processing and integrity of the data and should be defined in the database. The database s implementation of RI within its database tables is more extreme than any other company s because its table designs have many levels of relationships. The common implementation of RI contains 4 to 6 levels within the RI relationship structures. Within the some environments, there are many different tables that have 10 or more relationships. This is very unusual and should be of special note for the application support and development staff to make sure that it is processed properly. How many levels of Referential Integrity do you have in your databases? Compression offers tremendous savings potential by reducing the row size within DB2 saving sometimes up to 90% to 50% of the DASD used and accessing/caching more rows per I/O that can cut CPU tremendously. Implementing compression needs research to make the compression overhead is minimized. Since the compression cost ratio is 3 to 1 for compression (Insert or Update activity) versus decompression (Select activity) the I/O characteristics and analysis of workload need to be done for each table that may be compressed.

10 Many high performance database applications reference many existing services referencing many database tables but only a few of these tables utilize a partitioning tablespace that could help parallelism and spread out the locking and I/O workload. Table partitioning divides the data into multiple smaller datasets. These smaller datasets allow quicker parallel imagecopy and reorganization maintenance. Partitioning also helps spread the locks across the table helping reduce deadlocks and abends. SQL processing can also be automatically or manually parallelized cutting elapsed run time to only a fraction of time. Examining the system performance of the daily application showed that there were a number of considerations regarding the locking that is happening within the system. The first item that was noticed was that there were a number of lock escalations within the system. These lock escalations are expensive in terms of CPU and increased deadlock detection driving up CPU consumed. These lock escalations need to be researched and minimized across the system. The first situation to research is the settings on the various database objects. Within these definitions the LOCKMAX tablespace parameter escalates locks from a page lock to a tablespace lock after the application exceeds the number specified. Even though this was only found on three tables it should be removed at once. The analysis should also research the application program commit frequency and the timeframes of the lock escalations. These situations are probably more important than the settings as they will dictate the amount of work in the application/system at the time. Another aspect to research is the mix of the applications running together and analyze whether the mix is a cause or a victim of the lock escalation situation.

11 The cluster ratio is very important for SQL query performance and reflects the indexing and order of the stored data rows. DB2 tries to maintain the clustering order defined in the database tablespaces. Discovering a bad clustering order indicates that the data needs to be reorganized or have its clustering redefined. Bad clustering is indicated by finding a large number of rows in a FAROFFPOS within the database. This requires DB2 to do many extra random I/Os and consume more CPU for every individual data row accessed. Accessing nonclustered data is very expensive and INSERT and UPDATE activities can be even more expensive in performing more I/Os and CPU costs. Another aspect of the index analysis showed that there are a large number of indexes that have poor clustering and poor cluster ratios. These conditions are caused by wrong column types being used, wrong column order being defined and robust activity disorganizing the index. All of these index considerations need further detailed analysis to determine the root causes of these situations. These conditions sometimes cause double the I/O against the index structures and within the production environment; the amount of savings could be quite substantial. Many of these tables contain years of data and carrying around all the extra data is slowing down performance through extended overall processing. Especially during utility and insert processing, the many years of data slows down processing by maintaining large data stores and large numbers of indexes Analysis is necessary to understand the activity on each of these tables and design a segmentation strategy for separating the operational data away from the historical data. The segmentation strategy can be partitioning, versioning, Materialized Query Tables MQTs, or IBM s Smart Analytic Optimizer, Union All Views or DB2 temporal data support within DB2 10.

12 MQT as aggregates Data aggregation and summaries can save a tremendous amount of I/Os and CPU. Make sure the aggregates and summaries are monitored to demonstrate and justify their creation. This design and query technique has been used several times and provide tremendous performance.

13 Application success demands critical infrastructure reporting and monitoring of its performance, response time and transactions. This information is critical to determine its efficient services and where performance improvements are needed. To develop this End-to-End monitoring companies need to develop inventory list of reports available for both the mainframe & WAS environments. Analyze and understand what reports/element details are related across the mainframe and websphere platforms. Also procedures are needed to acquire these reports through standard every day operations. Also these reports need to be gathered consistently over a long period of time to establish a baseline of performance statistics for historical comparisons. Monitoring a particular time period, for example 15:00 15:05 should be started immediately so both the mainframe and websphere reports can be analyzed and understood by the overall performance team. Many application uses two, a websphere application and a websphere server environment to process the web application. These servers are very busy satisfying the application services requests and show large ratios of complete busy time within their overall processing. For example during the testing the performance reports documented that the websphere environment was processing the transaction script for 19.7 seconds with 5.2 seconds of that time the server was completely CPU busy. This situation and CPU busy ratio is a concern for long term overall performance.

14 The configuration of the application utilizing two servers and many different application services causes the application to perform many HTTP calls. These calls performance can be improved through consolidating the application and these calls within a single JVM. Garbage Collection (GC) is the cleanup of unreferenced memory items within the application services structure. The GC process is vital for the JVM to recycle and free memory for new objects needed within the application. The most important advantage of Data Studio and purequery are its capabilities to do a static bind for java SQL applications. In addition to all the static bind advantages highlighted on the previous slide, having a static java application environment helps the system reduces memory allocations. Since the workload is static it no longer requires a large system Dynamic Statement Cache, a large EDM Pool or a large number of server connections. Static SQL and static processes within DB2 system reduce the system resources required to execute the SQL processing. For example it can reduce the overall CPU demand and result in significant charge back savings within an enterprise.

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16 These are some items that can help the performance of your applications. The DB2 10 INCLUDE column option will help many applications with reducing the number of indexes on their tables. These are the DB2 SQL access types that usually clause performance problems. Each one of these access paths found within your application should be evaluated for improvement possibilities. The OPTIMIZE FOR 1 ROW phrase is great way to turn off a MERGE SCAN JOIN SQL access type usually improving performance and reducing elapsed run time. Also make sure that the indexes support the sorting done within your SQL statements.

17 Expensive access paths should always be evaluated. I usually develop a weekly report for my clients to review these access paths found in their environment. DB2 explain process should be done on each SQL statement within your environment. Know which access is a performance consideration immediately and make sure your performance is the best it can be.

18 An application process may require data from many tables and needs to get that information through efficient SQL performance. DB2 SQL Joins are much more efficient than any application process and should be used over single SQL statements in a process. Joining tables should be done when there are common columns supported by indexes to help performance. Using Materialize Query Tables (MQTs) helps data summarizes to be built once and used multiple times saving precious I/O and CPU. Multi-dimensional Clustering tables organizes the data along several common keys providing efficient I/O for queries. These table type should be analyzed to determine if they can improve your overall workload performance. Within applications cursor processing retrieves a single row. DB2 processes sets of data through SQL and cursors should be only used when absolutely necessary. Also when evaluating your applications evaluate the performance of the most frequently executed SQL within the environment. Improving an SQL statement a little that is executed a million times a day has much more impact than improving one statement that is executed 5 time a lot.

19 Joins should be done on common indexed columns with each table. Additional column criteria should be added to the WHERE clauses for these statement to further reduce the SQL result set returned to the application. DB2 is faster than the application code and this also reduces the I/Os required. Additionally limit the columns referenced in the SQL to only the columns that are absolutely needed. Choosing extra columns can eliminate index only access and require extra I/Os within the system. DB2 Engine on both z/os and LUW is faster than any application process. Drive processing into the DB2 Engine to minimize the overall processing, minimize the trips across the network and I/Os done within any application. Research all the access paths of your applications, analyze all your most frequently SQL access paths, dump the Dynamic Statement Cache, and use the IBM Optimization Service Center (OSC) to realize the performance aspects of your SQL and applications. Also look to combine the various SQL within your application. Can all the processing within the application be done in a single SQL CTE with CASE statements? Too many programs have too many simple SQL statements

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