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DB2 10 for z/OS Update

DB2 10 for z/OS Update

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DB2 10 for z/OS Update

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  1. DB2 10 for z/OS Update Curt CotnerIBM FellowIBM Silicon Valley Lab

  2. DB2 10 for z/OS GA’ed October 2010 Completed Largest Beta Ever • 23 WW customers • +10 Extended Beta • Over 80 vendors Fastest uptake out of the gate • As of May, 2011 over 120 customer orders… 3x that of the prior release • More than 4x the number of licenses • About 25% are migrating from V8 • Every core beta customer is continuing with migration plans • First customer already in production • Migrated from V8 to V10 • Quality/stability looking good

  3. DB2 10 for z/OS • Fastest uptake • +2Xcustomers • +2.5Xlicenses • 25%coming from DB2 V8 • Customers in Production • SAP, data warehouse and OLTP workloads • Skip-level and V2V • Quality / stability solid • Production references DB2 V8 EOS: April 30, 2012 DB2 9 EOS: June 27, 2014

  4. The Latest DB2 10 CPU & Performance Feedback North America Insurance CICS/DB2 OLTP 15% CPU EMEA Insurance I/O Parallel Inserts 30% CPU; 41% Elapsed Time North America Banking CICS/DB2 7% CPU; 5% Elapsed Time North America Manufacturing CICS/DB 23% CPU EMEA Insurance Key Queries 3-15% CPU 4

  5. DB2 10: HUK-COBURG Performance Boost with CPU Savings Fully in Production • Client:One of the largest insurance companies in Germany, supporting almost 7 million customers and more than 12 million insurance policies • Challenge:Maintain 24x7 availability while efficiently handling 18 million transactions a day and supporting industry standards of 10+ years of historical data and photos • Solution: DB2 10 for z/OS, CICS Transaction Server for z/OS V4.1, and z196 hardware • Key Benefits: • Efficient, easy to scale solution • 10% performance improvement with sub-second response times • Cost savings with 10% CPU reduction “Migrating to DB2 10 generated a 10 percent performance improvement and 10 percent CPU savings in our production system almost immediately.” Matthias Jahns, Project Manager, HUK-COBURG

  6. Production Customer Experiences Fully In Production Fully In Production Fully In Production “We went for an early upgrade. The software was ready for us and we were ready for it. Why not take the savings early? DB2 10 has been a pleasant surprise. It will be difficult to find an area inside DB2 that does not give great performance. That being for developers, operation staff, administrators, etc. All will get benefits that could justify the upgrade in itself” “We are very pleased with the CPU savings we have seen with the out-of-the-box implementation during testing and early production phases. Our regression tests showed performance improvements just by running the workload on a DB2 10 CM member rather than a DB2 9 NFM member in the same data sharing group” “Migrating to DB2 10 generated a 10% performance improvement and 10% CPU savings in our production system almost immediately.” “The ‘overall performance’ in DB2 10 is better compared to DB2 9. The stability of DB2 10 is better compared to previous releases” In Production “Participation in the beta gave us confidence to upgrade from V8 to DB2 10. The benchmarks and analysis of functionality and performance have exceeded our expectations. So far our upgrades have gone smoothly and we are looking forward to completing our successful rollout of DB2 10”

  7. Who has DB2 10? … and many more

  8. SAP & System z Continue to Grow SAP Banking Services 7 on DB2 10 and z196 • Record-setting performance for SAP core banking workloads • Number of accounts processed larger than ever before: 150 million (Previously: 40 million) 4 of the 6 customers mentioned in this article are on System z Large-scale project run in Poughkeepsie in 1H 2011

  9. Other Triggers Driving Customers in 2012 • DB2 V8 • End-Of-Service effective: April 31, 2012 • 50% off Extended Service if purchase DB2 10 before July 1, 2012 • DB2 9 • Withdraw-from-Marketing • announce: Dec. 6, 2011 effective: Dec. 10, 2012 • End-Of-Service • announce: Feb. 7, 2012 effective: June 27, 2014

  10. DB2 10 Experiences Reduced cost Improved scalability Improved resilience Why DB2 10 Now? ”Our DB2 10 experience has given us confidence about the virtual storage relief and CPU savings. I am looking forward to continuing our rollout and reaping the benefits.” Niels Simanis Senior Technology Manager Danske Bank Benefits • 90%Virtual storage savings • 10%CPU savings on CICS transactions • 30%CPU savings on test batch workload Migration Tips • Plan well, including good maintenance practices • Rebind can get you the highest CPU savings • Expect increase in real storage consumption to support and exploit DB2 10

  11. DB2 10 Experiences Reduced cost Improved performance Improved scalability Why DB2 10 Now? “We are pleasantly surprised with the out-of-the-box CPU savings we have seen during testing and early production phases.” Terry Glover –Director IT Infrastructure Dillard’s Benefits • 20-30% CPU savings out-of-the-box • 5-15% Performance improvements for batch, CICS, and DDF Actual results may vary for other customers Migration Tips • Thorough preparation and planning • Good maintenance practices

  12. DB2 10: Customers seeing reduced costs, simplified workloads through proven technology For more customer references visit

  13. Lowest Cost Platform per User Consolidation savings with DB2 10 Easier porting of applications to DB2 for z/OS Extensive SQL & XML support added throughout Processing Savings with DB2 10 • 5 – 10% savings out of the box • Distributed application access can save up to 20% • Native SQL stored procedures can save up to 20% • Complex queries will now result in savings of up to 20% • Heavy insert activity can drive 10 – 40% savings

  14. IBM Relational Warehouse Workload (IRWW) with data sharing Base DB2 9 NFM REBIND with PLANMGMT(EXTENDED) • DB2 9 NFM  DB2 10 CM without REBIND measured 3.7% CPU reduction from DB2 9 • DB2 10 CM REBIND getting same access path measured 7.4% CPU reduction from DB2 9 • DB2 10 NFM measured same 7.4% CPU reduction from DB2 9 • DB2 10 CM or NFM with RELEASE(DEALLOCATE) measured additional 10% CPU reduction from DB2 10 NFM RELEASE(COMMIT)

  15. DB2 10 Higher Throughput & Better Scaling - Sample SAP ERP Measurement • Improved SQL runtime efficiency • Boosted SQL INSERT performance • Parallel I/O for index updates • Reduced latch contention • More efficient large bufferpools • Inline LOBs to avoid LOB TS access • DFSORT performance improvement • APAR PM18196 • Extended zIIP exploitation • Prefetching of pages into buffer pools • Large portion of Runstats

  16. Simplicity - Extraordinary Scalability DB2 10 for z/OS now enables applications 5-10 times the number of users and activity on a single system Virtual storage improvements deliver 10 times more scalability Fewer DB2 members required - reducing complexity and improving application performance Direct Row Access New Hash Access methodology eliminates multi-step indexing Significantly improves applications requiring single row access 30% to 50% improvement with Hash Access over Indexed data access Accounts Accounts We expect to reduce our data sharing requirements by 25%, which means less system, storage and resource expenses Banco do Brasil

  17. 17 17 Running Many Active Threads DB2 10 Today Coupling Technology Coupling Technology LPAR1 LPAR1 LPAR2 LPAR3 LPAR2 LPAR3 DB2A (500 thds) DB2A (2500 thds) DB2B (500 thds) DB2C (500 thds) DB2B (2500 thds) DB2C (2500 thds) DB2D (500 thds) DB2E (500 thds) DB2F (500 thds) • More threads per DB2 image • More efficient use of large n-ways • Easier growth, lower costs, easier management • Data sharing and Parallel Sysplex still required for very high availability and scale • Rule of thumb: save ½% CPU for each member reduced, more on memory • Data sharing and sysplex allows for efficient scale-out of DB2 images • Sometimes multiple DB2s per LPAR

  18. Other System Scaling Improvements • Other bottlenecks can emerge in extremely heavy workloads • Reduced latch contention • Improved efficiency for latch suspend/resume • new option to for readers to avoid waiting for inserters • eliminate UTSERIAL lock contention for utilities • Use 64-bit common storage to avoid ECSA constraints • DB2 10 NFM catalog restructure improves BIND / Prepare concurrency • SPT01 64GB constraint • Improved accounting rollup, compress SMF option • Reduced SMF data volume • Lower overhead for very large buffer pools

  19. Hash Access Select Balance From AccountsWHERE acctID = 17 • Hash Access provides the ability to directly locate a row in a table without having to use an index • Single GETP/RELP in most cases • 1 Synch I/Os in common case • 0 If In Memory Table • Greatly reduced Search CPU expense = Page in Bufferpool Accounts Table = Page Read from Disk

  20. Simplicity Time Travel Query Integrated Bitemporal capabilities Query over any current, prior or future period in time System and User-maintained temporal tables SQL standards work in progress Accounts Accounts Accounts What is the answer now? What was the answer in the past? What will the answer be in the future? “As much as 80% of our applications can use this, which will drastically save developer time and even more importantly make applications easier to understand to improve business efficiency and effectiveness”   The new temporal functionality in DB2 10 for z/OS will allow us to drastically simplify our data-related queries and reduce our processing cost by having DB2 handle data movement more efficiently than our custom code Major Insurance Company

  21. 21 21 Temporal data or versioned data Table-level specification to control data management based upon time Two notions of time: System time: notes the occurrence of a data base change “row xyz was deleted at 10:05 pm” Query at current or any prior period of time Useful for auditing, compliance Business time: notes the occurrence of a business event “customer xyz’s service contract was modified on March 23” Query at current or any prior/future period of time Useful for tracking of business events over time, application logic greatly simplified New syntax in FROM clause to specify a time criteria for selecting historical data

  22. 22 22 More Improvements for Applications SQL compile time: Optimization techniques Remove parallelism restrictions; more even parallel distribution Scalability: memory and latching relief allow more parallel Optimization validation with Real Time Statistics In-memory techniques for faster query performance Multiple IN-List matching IN-List predicate transitive closure SQL runtime: RID overflow to workfile Mitigate increased workfile usage by increasing RID pool size (default increased in DB2 10). MAXTEMPS_RID zparm for maximum WF usage for each RID list Sort performance enhancements Avoid workfile usage for small sorts Hash support for large sorts

  23. 23 23 And More Application Improvements pureXML enhancements Large object improvements Allow non-NULL default values for inline LOBs Loading and unloading tables with LOBs LOBs in input/output files with other non-LOB data SQL Enhancements Currently committed locking semantics Implicit casting or loose typing Timestamp with time zone Variable timestamp precision – seconds to picoseconds Moving Sum, Moving Average SQLPL performance improvements Extended indicator variables Row and column access control

  24. 24 24 System Administrator Tasks Security Administrator Tasks Database Administrator Tasks Access Monitor Audit Business Security & Compliance • Protect sensitive data from privileged users & improve productivity • SECADM & DBADM without data access • Usability: DBADM for all DB • Revoke without cascade • Separate authorities to perform security related tasks, e.g. security administrator, EXPLAIN, performance monitoring and management • New audit policy controls, audit privileged users • Row and column access control • Allow masking of value • Restrict user access to individual cells

  25. Continuous Availability: More Online Schema Changes • ALTER TABLESPACE • Page size (not XML) (BUFFERPOOL) • DSSIZE • SEGSIZE • Table space type • Single table simple -> PBG (inherit MC) • Single table segmented -> PBG • Classic partitioned -> PBR (inherit MC) • PBG -> Hash • MEMBER CLUSTER • ALTER INDEX • Page size (BUFFERPOOL) • In DB2 9 this was immediate with RBDP set • Other schema change enhancements • Table space no longer needs to be stopped to alter MAXROWS • Object no longer needs to be stopped to alter BPOOL in data sharing ALTER TABLESPACE … MAXPARTITIONS m ALTER TABLESPACE … SEGSIZE s ALTER TABLE … ADD ORGANIZE BY HASH

  26. Other Availability Improvements • Access currently committed data • Change DDF location alias names online • New MODIFY DDF ALIAS command • Online DDF CDB changes • LOCATIONS, IPNAMES, IPLIST • Dynamic add of active logs • New –SET LOG NEWLOG option • Pre-emptable backout

  27. Why is IBM focusing on IDAA? • Changing business requirements • BI/DW becoming mission critical and requires OLTP-like QoS • reliability, continuous availability, security, mixed workload management, … • orders of magnitude faster execution of complex, ad hoc queries • predictable query performance • Shift towards dynamic DW and operational BI • Combining OLTP and OLAP workloads • Traditional performance tuning tools of the trade such as indexing, pre-built aggregates and MQTs struggling to keep the pace • Require top DBA expertise and sophisticated tools • Even then not good enough due to ad-hoc, unpredictable nature of the workload • Technology trends • Very large number of processor sockets and cores • Specialized query processing engines • Appliances

  28. DB2 Components Applications DBA Tools, z/OS Console, ... Application Interfaces (standard SQL dialects) Operation Interfaces (e.g. DB2 Commands) DB2 Log Manager IRLM Buffer Manager Data Manager . . .

  29. IBM DB2 Analytics Accelerator as a Virtual DB2 Component Applications DBA Tools, z/OS Console, ... Application Interfaces (standard SQL dialects) Operation Interfaces (e.g. DB2 Commands) DB2 IDAA Log Manager IRLM Buffer Manager Data Manager . . .

  30. Deep DB2 Integration Applications DBA Tools, z/OS Console, ... Application Interfaces (standard SQL dialects) Operation Interfaces (e.g. DB2 Commands) DB2 IDAA Log Manager IRLM Buffer Manager Data Manager . . . Industry leading DW performance, ease of use Superior availability reliability, security, workload management, OLTP performance ... Netezza z/OS on System z 10‘s of processors 100‘s GB of memory

  31. The Best of Both Worlds Best in OLTP Industry recognized leader in mission critical transaction systems Data Mart Data Mart Data Mart Data Mart Data Mart Consolidation Best in Data Warehouse Proven appliance leader in high speed analytic systems Transaction Systems (OLTP) Best in Consolidation Unprecedented mixed workload flexibility and virtualization providing the most options for cost effective consolidation System z Recognized leader in mixed workloads with security, availability and recoverability for OLTP Netezza Recognized leader in cost-effective high speed deep analytics Data Warehouse Analytics

  32. Field Experiences Queries running up to 1908 times faster

  33. For More Information DB2 10 Customer Material DB2 10 e-kit SAP Benchmark: RFE (Request for Enhancement) database • VISIT the DB2 Best Practices • JOIN the World of DB2 for z/OS • JOIN the DB2 for z/OS group

  34. Engaging Web and Mobile Applications Modern User Interface and Form Factors Implemented using JavaScript for Web 2.0 in desktop Implemented using JavaScript in IBM Worklight for hybrid mobile application

  35. Eliminate mapping and transformation JSON Data Repository

  36. But --- there are Gaps in NoSQL DataStores …. Can Enterprises Live with these? Complex apps Data integration Multi-statement transactions Data Management tool-set and Eco-system Security Integration with Enterprise Data

  37. Goals for an IBM NoSQL Store • Embrace the flexibility and scalability of emerging NoSQL solutions • Add JSON capabilities • Ensure web scale application support • But don’t compromise traditional enterprise grade qualities of service and unique RDBMS capabilities • Complex transactions • Joins • Temporal Data • Geo-spatial data • Atomicity, Consistency, Integrity, Durability • Access control & security • Referential Integrity • Check constraints • Scalability • Robust monitoring • Keep it simple • Programming API • Simple API for simple JSON queries and updates • Extensions as needed for specialized functions • - temporal data, geo-spatial, granular access • Allow access to JSON data and relational tables in the same query • Administration • Autonomic storage management • Simple replication solutions • Little friction for model and schema changes • Keep it fast • Leverage the strengths of IBM technology • Indexing, buffering, scalability, access path optimization • Distributed caching