Achieving the best of both worlds: The hybrid data server approach

Transcription

1 Achieving the best of both worlds: The hybrid data server approach IBM DB2 Analytics Accelerator Powered by Netezza Gary Crupi, IBM Smart Analytics System 9700 / 9710 Technical Lead 2012 IBM Corporation

2 Topics for Today! A short look beyond the typical importance of Real Data Insights! Building the System z Foundation for Analytics! Extreme Performance; Customer Proof Points! IBM DB2 Analytics Accelerator Technology Introduction! Break! Using the IBM DB2 Analytics Accelerator! Traditional Techniques that augment this strategy (WLM and RLF)! Demonstration IBM Corporation

3 A quick survey of the typical importance of information slides IBM Corporation

4 Time is money The more data we have, the longer our analysis takes!! Waiting for fact based information to drive key decisions! Waiting for key reports to complete! Paying analysts to perform query analysis! Adding indices and MQTs in an attempt to speed up queries! Accumulating MIPS for long running queries IBM Corporation

5 Information Management Smart Business Analytics on System z OLTP vs. Analytics Examples OLTP - Transactional Withdrawal from a bank account using an ATM Buying a book at Amazon.com Check-In for a flight at the airport Hand-over manufactured printers to an oversea-carrier Transactional Analytics: (Operational BA) Approve request to increase credit line based on credit history and customer profile Propose additional books based on similar purchases by other customers Offer an upgrade based on frequent flyer history of all passengers and available seats Optimize shipping by selecting cheapest and most reliable carrier on demand Deep Analytics Regular reporting to central bank sum of transactions by account Which books were bestsellers in Europe over the last 2 months? Marketing campaign to sell more tickets in off-peak times Trend of printers sold in emerging countries versus established markets IBM Corporation

6 Top 5 System z customer trends I am seeing 1. Operational Data Store (ODS) / Near Real-Time ODS / Evolution to ODS Mix 2. Enterprise Data Warehouse / ODS / Data Mart Mixed Workloads Return 3. Enhancing and Modernizing legacy decision support / reporting systems 4. Reporting systems outgrowing core OLTP / including sneaky growth 5. Considering a move to System z from outdated technologies and Migrations IBM Corporation

7 Building the System z Foundation for Analytics IBM Corporation

8 IBM Smart Analytics System 9700 / 9710 z/vm 6.2 Linux on System z z/os V1.13 An integrated solution of hardware, software and services that enables customers to rapidly deploy cost effective game changing analytics across their business. Offered in standard and foundational configurations. The 9700 is built using the System z196 server. The 9710 leverages the System z114 server to deliver a truly compelling entry-level offering The standard configuration delivers everything as pictured. The foundational configuration removes the Linux on System z portion of the solution (z/vm, SPSS, Cognos, InfoSphere Warehouse) IBM Corporation

9 Technical Validation Phases! Phase 1 System Acquisition and Build Query Suite Contents, Preparation, and Execution Comparison and New Baseline Establishment SPSS Scenario Banking / Modeling and Scoring! Phase 2 Workload Simulation I/O Driven, Enumeration and Elasticity Inputs Scale Factor: 4, 12, 25, 100 TB DB2 Query Concurrency Examples: 10, 25, 50, 100, 300 % Data Accessed Examples:.5%, 1%, 5%, 20%, 50% Driven by light and heavy SQL Outputs MIPs, Memory, Storage Capacity, I/O Bandwidth Workload Simulation Customer Profile CP and I/O Driven! Finalize Configurations IBM Corporation

10 Development System Build! System z196 with 80 PUs, 750 GB memory! DS8800 Storage Approximately 1,125 TB usable storage! DB2 10 for z/os PUT , 12, 25, 100 TB databases Split and Order! Rational Performance Tester 2817-M80 IBM zenterprise 196 Feature Description 1129 Model M80 - Air Cooled GB Mem DIMM(5/feat)-A Way Processor CP CP GB Memory Capacity Incr GB Memory 3325 FICON Express8 10KM LX 4 ports 3326 FICON Express8 SX 4 ports 3367 OSA-Express3 1000BASET-EN 4 ports 3371 OSA-Express3 10 GbE SR 2 ports IBM Corporation

11 Scan Rate Comparison DB2 s ability to consume data! Table with 8k page size and 9 columns! IBM Smart Analytics System 9600 (DB2 9 for z/os and System z10) Compressed scan achieved 249 mb/sec/cp * Uncompressed scan achieved 322 mb/sec/cp *! IBM Smart Analytics System 9700 (DB2 10 for z/os and System z196) Compressed scan 445 mb/sec/cp Uncompressed scan 915 mb/sec/cp Extra Credit Table with 16k page size and 16 columns Compressed scan 537 mb/sec/cp Uncompressed scan 1,141 mb/sec/cp * Different SQL was used IBM Corporation

12 Foundational Query Comparison Foundational Queries Elapsed Time Minutes Query - shorter is better July July 2010 Normalized July IBM Corporation

13 Workload Simulation Elasticity Testing! Primary Workload Categories Transactional Analytics Mix of Reporting and Ad-Hoc Deep Analytics! Drive I/O lots of it with low and high concurrency! Light and Heavy queries with Low and High % data accessed IBM Corporation

14 Elasticity Results - % Data Accessed and Concurrency Matters! 12 TB Database, 12 CPs / 12 ziips, MDEG Heavy Queries with Lower % Data Accessed Values A : approx 90 orders, 360 line items B : approx 9,000 orders, 36,000 line items C approx 900,000 orders, 3,600,000 line items D -.05 approx 9,000,000 orders, 36,000,000 line items E -.1 approx 18,000,000 orders, 72,000,000 line items Elapsed Time Minutes.Seconds TB Heavy Queries Concurrent Users % Data Accessed 12 TB Heavy Queries Elapsed Time Minutes.Seconds Concurrent Users % Data Accessed 12 TB Heavy Queries Elapsed Time Minutes.Seconds Concurrent Users % Data Accessed IBM Corporation

15 Creating the Hybrid Data Server Combine the 9700/9710 with IDAA to provide an industry exclusive Data Mart Data Mart Data Mart Data Mart Consolidation Best in OLTP and Transactional Analytics Industry recognized leader in mission critical transaction systems Transaction Processing Systems (OLTP) Best in Deep Analytics Proven appliance leader in high speed analytic systems Transactional Analytics 15 Deep Analytics z/os: Recognized leader in transactional workloads with security, availability and recoverability IDAA Powered by Netezza: Recognized leader in cost-effective high speed deep analytics Together: Destroying the myth that transactional and decision support workloads have to be on separate platforms Best in Consolidation Unprecedented mixed workload flexibility and virtualization providing the most options for cost effective consolidation 2012 IBM Corporation

16 Extreme Performance; Customer Proof Points IBM Corporation

17 Information Management Smart Business Analytics on System z Large Insurance Company Adding value by Accelerating the Delivery of Business Reporting Total Qualifying Rows With Accelerated Time to Value DB2 Only DB2 with IDAA Total Rows Returned Hours Sec(s) Hours Sec(s) Times Faster Total Rows Query Reviewed Query 1 591,941,065 2,813, ,320 2:39 9, ,908 Query 2 591,941,065 2,813, ,780 2:16 8, ,644 Query 3 813,343,052 8,260, :16 4, Query 4 283,105,125 2,813, ,197 1:08 4, Query 5 591,941,089 3,422, :57 4, Query 6 813,343,052 4,290, :53 3, Query 7 591,941, ,521 58,236 0:51 3, Query 8 813,343,052 3,425, :44 2, ,320 Query 9 813,343,052 4,130, :42 2, ! IBM DB2 Analytics Accelerator (Netezza ) Production ready - 1 person, 2 days! Table Acceleration Setup in 2 Hours - DB2 Add Accelerator - Choose a Table for Acceleration - Load the Table (DB2 Loads Data to the Accelerator) - Knowledge Transfer - Query Comparisons! Initial Load Performance 400 GB Loaded in 29 Minutes 570 Million Rows (Actual: Loaded 800 GB to 1.3 TB per hour)! Extreme Query Acceleration x faster 2 Hours 39 minutes to 5 Seconds! CPU Utilization Reduction Up to 35% Customer Quote: we had this up and running in days with queries that ran over 1000 times faster IBM Corporation

18 Information Management Smart Business Analytics on System z Large Insurance and Risk Management Solutions Company Customer Goals utilizing IDAA! Supports the ongoing active cost management on mainframe! IDAA technology on zenterprise will enable further improvement on Software license costs! IDAA allows to significantly improve operational performance for financial reporting query response times! Applying traditional System z and DB2 quality of service! No changes to the applications or SQL! Reduction of CPU consumption on System z by shifting workload to IDAA! Disaster Recovery of IDAA QUERY DB2 Elapse Time IDAA Elapse Time Speed up Factor L seconds 89 seconds 8.3x L seconds 3 seconds 60x L seconds 1579 seconds 5.5x L seconds 27 seconds 90x With Accelerated Time to Value! IBM DB2 Analytics Accelerator (Netezza ) Day 1: IDAA hardware installation and configuration Day 2: Connection to z/os and pairing the Accelerator with DB2 Day 2: Created and loaded tables in the Accelerator and executed first queries! Ease of Use All applicable tables accelerated and queries executed within one hour! Table Loads Loaded 3 Tables GB raw data (uncompressed) - DB2 compression 123 GB - Accelerator compression 40 GB (Compression Factor:10x) - Load time 29 Minutes - Load rate: greater than 800 GB/hour IBM Corporation

19 Information Management Smart Business Analytics on System z International Securities Company Customer Goals utilizing IDAA! The customer is currently utilizing Sybase for their OLTP and Data Warehouse environments and moving the OLTP environment to DB2 for z/os.! The customer conducted a benchmark to determine if DB2 for z/os with IDAA is a viable platform for data warehousing.! Customer would like to reduce MIPs, Software Costs and the Total Cost of Ownership with the 9700 and IDAA Customer Statistics Data Warehouse is approximately 12 TB accelerated into IDAA 100 Simple queries and 112 complex queries were tested in the benchmark IBM DB2 Analytics Accelerator (Netezza ) Day 1-2: IDAA hardware installation and configuration Day 3: Created and loaded tables in the Accelerator and executed first queries 212 queries were executed sequentially (9700 only and then with IDAA) IBM Corporation

20 Information Management Smart Business Analytics on System z IDAA For SAP Business Intelligence AD-HOC Reporting! Data Warehousing and BI queries as found in SAP BW environments are typically complex and often ad-hoc in nature.! There is a common concern about the elapsed times of running these very resource intensive workloads in a native DB2 for z/os environment.! Data Warehousing and BI applications increasingly require very fast response times irrespective of the complexity of the queries.! Loaded InfoCube into IDAA, all tables involved in the star schema query were loaded to IDAA.! Executed 20 dedicated query tests on 18-million rows against InfoCube star schema 20 Rapid SAP NetWeaver BW ad-hoc Reporting Supported by IBM DB2 Analytics Accelerator for z/os Link: 2012 IBM Corporation

21 Information Management Smart Business Analytics on System z IBM DB2 Analytics Accelerator Technology Introduction IBM Corporation

22 Information Management Smart Business Analytics on System z DB2 Analytics Accelerator Product Components zenterprise Powered by Netezza Technology CLIENT OSA-Express4 10 GbE Primary 10Gb Backup Data Studio Foundation DB2 Analytics Accelerator Admin Plug-in BladeCenter 22 Users/ Applications Data Warehouse application DB2 for z/os enabled for IBM DB2 Analytics Accelerator IBM DB2 Analytics Accelerator 2012 IBM Corporation

23 Now expandable to 960 cores and 1.28 petabytes TF3 TF6 TF12 TF24 TF36 TF48 TF72 TF96 TF120 Cabinets 1/4 1/ Processing Units Capacity (TB) Effective Capacity (TB)* Accelerator Platforms Predictable, Linear Scalability throughout entire family Capacity = User Data space Effective Capacity = User Data Space with compression *: 4X compression assumed 23 Low Latency, High Capacity Update 2012 IBM Corporation

24 Information Management Smart Business Analytics on System z IDAA powered by Netezza 1000 Appliance TM Slice of User Data Swap and Mirror partitions High speed data streaming High compression rate Disk Enclosures SMP Hosts Snippet BladesTM (S-Blades, SPUs) 24 IBM DB2 Analytics Accelerator Server SQL Compiler, Query Plan, Optimize, Administration Processor & streaming DB logic High-performance database engine streaming joins, aggregations, sorts, etc IBM Corporation

25 Information Management Smart Business Analytics on System z The Netezza S-BladeTM Dual-Core FPGA Intel Quad-Core IBM BladeCenter Server IBM Corporation

26 Information Management Smart Business Analytics on System z The Key to the Speed select DISTRICT, PRODUCTGRP, sum(nrx) from MTHLY_RX_TERR_DATA where MONTH = ' ' and MARKET = and SPECIALTY = 'GASTRO group by DISTRICT, PRODUCTGRP FPGA Core CPU Core Slice of table MTHLY_RX_TERR_DATA (compressed) Uncompress Project Restrict, Visibility Complex Joins, Aggs, etc. sum(nrx) group by DISTRICT, PRODUCTGRP 26 select DISTRICT, PRODUCTGRP where MONTH = ' ' and MARKET = and SPECIALTY = 'GASTRO' 2012 IBM Corporation

27 Information Management Smart Business Analytics on System z Deep integration within DB2 for z/os Applications DBA Tools, z/os Console,... Application Interfaces (standard SQL dialects) Operational Interfaces (e.g. DB2 Commands) DB2 for z/os Data Manager Buffer Manager... IRLM Log Manager IBM DB2 Analytics Accelerator Superior availability reliability, security, Workload management z/os on System z Superior performance on analytic queries Powered by Netezza IBM Corporation

28 Information Management Smart Business Analytics on System z Bringing Netezza AMPP TM Architecture to DB2 AMPP = Asymmetric Massively Parallel Processing CPU FPGA Advanced Analytics Memory BI DB2 for z/os SMP Host CPU Memory FPGA Legacy Reporting CPU FPGA DBA Memory Network Fabric S-Blades Disk Enclosures IBM DB2 Analytics Accelerator IBM Corporation

29 Information Management Smart Business Analytics on System z Workload-Optimized Query Execution OLTP-like query Light ODSquery Light BI Query Heavy BI Query User control and DB2 heuristic DB2 for z/os and IBM DB2 Analytics Accelerator DB2 Native Processing Optimized processing for BI Workload Single and unique system for mixed query workloads Dynamic decision for most efficient execution platform New special register QUERY ACCELERATION NONE ENABLE ENABLE WITH FAILBACK New heuristic in DB2 optimizer IBM Corporation

30 Information Management Smart Business Analytics on System z Query Execution Process Flow Application Interface Optimizer SPU CPU FPGA Memory Application Query execution run-time for queries that cannot be or should not be off-loaded to IDAA IDAA DRDA Requestor SMP Host SPU CPU FPGA Memory SPU CPU FPGA Memory SPU CPU FPGA Memory DB2 for z/os DB2 Analytics Accelerator Queries executed without DB2 Analytics Accelerator Queries executed with DB2 Analytics Accelerator IBM Corporation

31 System Overview and Connectivity Client Application for queries SPU SPU SPU... DRDA DB2 Netezza Matching SQL Rewrite Catalog 10 Gbe Network Netezza Process Queries and Maint. Tasks HW Monitoring HW Failure Notifications OS Security Service Access DDF Queries & heartbeat via DRDA IBM DB2 Analytics Accelerator Stored Procedures Admin tasks (i.e. LOAD) via DRDA JDBC/DRDA DB2 Analytics Accelerator GUI CALL locally/remote Client Application for administration Software updates for IDAA and Netezza (kit) through HFS (USS) and stored procedure to Netezza 1000 hardware IDAA trace captures important nz log files as well 31

32 Information Management Smart Business Analytics on System z Flexible Deployment options! Multiple DB2 systems can connect to a single IDAA DB2 IDAA DB2! A single DB2 system can connect to multiple IDAAs IDAA DB2 IDAA! Multiple DB2 systems can connect to multiple IDAAs DB2 IDAA IDAA DB2 32 Better utilization of IDAA resources Scalability High availability Multiple options to deploy Dev/Test/QA Full flexibility for DB2 systems: residing in the same LPAR residing in different LPARs residing in different CECs being independent (non-data sharing) belonging to the same data sharing group belonging to different data sharing groups 2012 IBM Corporation

33 Network Configuration Options Option 1 Simple Direct attachment Virtual IP definition both on System z and Netezza Only one network link active at a time if Netezza fails over to standby host, connection might get lost OSA ports are configured such that only one link is active at a time. If the connection on this link breaks, the other is activated System z OSA port 1 port 2 SMP Host 1 port 1 port 2 10GbE SMP Host 2 port 1 port 2 10GbE IDAA Option 2 Additional redundancy or additional CEC requires Switch(es) Can address cable failures and Netezza fail over to standby host For higher availability requirements, a second switch is required OSA ports are configured such that packages are sent alternating, using both ports: multipathperconnection configuration System z OSA OSA port 1 port 2 port 1 port 2 Switch 1 Switch 2 SMP Host 1 port 1 port 2 10GbE SMP Host 2 port 1 port 2 10GbE IDAA 33

34 Network Configuration Options (continued) Option 3 zbx TOR Switch For clients with an installed zbx connected to zenterprise, the top-of-rack switch may be leveraged to connect to the IDAA Connection between zbx and IDAA can be direct or switched Ethernet Switch Private Service Network TOR Switch 10 GbE OSA- Express3 10 GbE OSX Private Data Network zenterprise zbx IDAA 34

35 Disaster Recovery Considerations (1 of 2) App 1 SYSPLEX DSG Member 1 DSG Member 2 App 2 Tables of App 4 Tables of App 5 App 4 App 3 Tables of App 1 Tables of App 2 Tables of App 3 App 5 Short Range Switch Short Range IDAA Instance 1 Long Range Short Range Switch Short Range IDAA Instance 2 Tables of App 1 Tables of App 2 Tables of App 3 Tables of App 4 Tables of App 5 35

36 Disaster Recovery Considerations (2 of 2) App 1 SYSPLEX App 1 DSG Member 1 DSG Member 2 Tables of App 4 App 2 App 2 Tables of App 5 App 3 Tables of App 1 App 3 Tables of App 2 Tables of App 3 App 4 Short Range Short Range Long Range Switch Short Range Short Range IDAA Instance 2 IDAA Instance 1 CREATE/LOAD Tables of App 1 36 Tables of App 2 App 5 Switch Tables of App 3 Tables of App 1 Tables of App 2 Tables of App 4 Tables of App 3 Tables of App 5

37 Using the IBM DB2 Analytics Accelerator 37

38 Information Management Smart Business Analytics on System z How do I use an Analytics Accelerator? IBM Corporation

39 Connection Profile 39

40 Finding the IDAA 40

41 How did it get here in the first place? Press <return> to accept the default of 30 minutes. Cancel the process by entering 0. Accelerator pairing information: Pairing code : 6048 IP address : Port : 1400 Valid for : 30 minutes Press <return> to continue 41

42 Other things you might be able to do! But, probably want to think about before you do them 42

43 Display Accelerator 43

44 Tables Enabled for Acceleration Twisty 44

45 Add Table (Note that removing a table is very similar) 45

46 Initial Table Status Note the following: Acceleration Disabled Last Load Initial load pending Distribution Key Random Organizing Key - none And highlight a table to enable: Alter Keys Load Remove Enable / Disable 46

47 Accelerator Data Load DB2 for z/os Accelerator Table B Table A IDAA Studio IDAA Administrative Stored Procedures Table C Table D Part 1 Part 2 Part 3 Part 1 Part 2... Part m Unload Unload... Unload USS Pipe USS Pipe... USS Pipe Coordinator CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory 47 1 TB / h can vary, depending on CPU resources, table partitioning, Update on table partition level, concurrent queries allowed Incremental Update under discussion

48 Incremental Update An alternative to a full table load or table partition load. Refreshes only the records of the table that have been recently modified in the data warehouse. This capability keeps the data on the DB2 Analytics Accelerator in sync with the data on the mainframe DB2. This is an initial release with the full release of incremental update being made available in the next major release of the offering. Incremental Update is a capability most customers want, and therefore is being added to the offering for all customers, and not a separately orderable feature IBM Corporation

49 Introducing Incremental Update ELT or ETL OLTP Application Data Warehouse Change Data Capture Table or Partition Update DB2 Analytics Accelerator Incremental Update Synchronizing data to lower data latency from days to minutes/seconds 49 Low Latency, High Capacity Update 2012 IBM Corporation

50 Option 1: Full Table Refresh! Changes in data warehouse tables typically driven by scheduled (nightly or more frequently) ETL process! Data used for complex reporting based on consistent and validated content (e.g., weekly transaction reporting to the central bank)! Multiple sources or complex transformations prevent from propagation of incremental changes! Queries may continue during full table refresh for accelerator! Full table refresh may be triggered through DB2 stored procedure (scheduled, integrated into ETL process or through GUI) Operational Analytics, Reports, OLAP, DB2 native processing Continuous Query Processing DB2 z/os Query Optimizer Accelerator processing ETL Process Changes / Replacement Full table refresh DB2 for z/os database IBM Corporation

51 Option 2: Table Partition Refresh! Changes in data warehouse table typically driven by delta ETL process (considering only changes in source tables compared to previous runs) or by more frequent changes to most recent data! Optimization of Option 1 when target data warehouse table is partitioned and most recent updates are only applied to the latest partition! Maintains snapshot semantics for consistent reports! Queries may continue during table partition refresh for accelerator! Table partition refresh may be triggered through DB2 stored procedure (scheduled, integrated into ETL process or through GUI) Replication Operational Analytics, Reports, OLAP, DB2 native processing January February Continuous Query Processing DB2 z/os Query Optimizer Accelerator processing 51 ETL Process Changes March April May Partition refresh DB2 for z/os database 2012 IBM Corporation

52 Option 3: Incremental Update (Controlled Availability)! Changes in data warehouse tables typically driven by replication or manual updates 52 Corrections after a bulk-etl-load of a data warehouse table Continuously changing data (e.g. trickle-feed updates from a transactional system to an ODS)! Reporting and analysis based on most recent data! May be combined with Option 1 & 2 (first table refresh and then continue with incremental updates)! Incremental update can be configured per database table Replication Application Changes Operational Analytics, Reports, OLAP, DB2 native processing Continuous Query Processing DB2 z/os Query Optimizer Incremental Update DB2 for z/os database Accelerator processing 2012 IBM Corporation

53 Load Table (and optionally enable it) 53

54 Loading and Refreshing IDAA Data Contents (1 of 3)! Implemented as Stored Procedure ACCEL_LOAD_TABLES Invoked directly or through IDAA Studio! IDAA Studio - a Single and Uniform Interface for: Initial Load of a DB2 Table into IDAA Refresh of a Table or any Subset of Table Partitions into IDAA New copy is created and then the Previous Table or Partition is removed Initial load of partition(s) added by means of ADD PARTITION to DB2 Table already residing in IDAA Delete the contents of Partition(s) in IDAA that were purged in DB2 by means of ROTATE PARTITION! Loading a subset of partitions is supported for partitioning-by-range only! There is no automatic checking if a table or partition needs to be refreshed due to its contents having changed, but any request to load a subset of partitions results in checking if some additional partitions need to be loaded as a result of the following DB2 operations: ADD PARTITION: results in loading the added partitions ROTATE PARTITION: results in refreshing the FROM partition ALTER PARTITION RANGE: results in exception 54

55 Loading and Refreshing IDAA Data Contents (2 of 3)! A Set of Tables can be specified as a unit of loading Tables are loaded sequentially and load is committed only if successful for all tables To load a number of tables in parallel, each table needs to be loaded separately (i.e. a separate stored procedure invocation for each of the tables)! When loading a partitioned table in its entirety or when refreshing a subset of partitions, the partitions are loaded in parallel Degree of parallelism specified in environment variable AQT_MAX_UNLOAD_IN_PARALLEL Default is 4 Parallelism applies to partitioning-by-growth, but only when the entire table is loaded! DB2 can route queries to IDAA while the table's or partition's content is being refreshed and they will be executed by IDAA in parallel to the refresh operation 55

56 Loading and Refreshing IDAA Data Contents (3 of 3)! LOCKMODE option for ACCEL_LOAD_TABLES Can either allow or prevent data modifying operations (insert, update, delete, some utilities) during load execution, i.e. during importing the DB2 data into IDAA Read-only DB2 operations are fully compatible with IDAA importing process LOCKMODE 56 TABLESET TABLE PARTITION NONE Usage!Consistent snapshot across all tables in SP invocation requested.!no data changes allowed on any of the tables until ALL tables loaded.!consistent snapshot of each individual table in SP invocation requested!no data changes allowed on a table until that table is loaded!consistent snapshot of each individual partition requested.!no data changes allowed on a partition until that partition is loaded.!if table non-partitioned, consistent snapshot of entire table requested.!data changes permitted on tables being loaded, only committed data is loaded!in case of lock conflicts, affected rows (pages) are skipped (not loaded into IDAA). Serialization Mechanism 1. Before unload, for all tables in input, LOCK TABLE IN SHARE MODE 2. Unload all tables/partitions with UNLOAD SHRLEVEL CHANGE ISOLATION UR 3. Unlock all locked tables at end (via commit). 1.Before unload of a table, LOCK TABLE t in SHARE MODE 2.Unload all tables/partitions with UNLOAD SHRLEVEL CHANGE ISOLATION UR 3.Unlock table t (via commit). 1.Unload all requested paritions/tables with UNLOAD SHRLEVEL REFERENCE 1.Unload all requested paritions/tables with UNLOAD SHRLEVEL CHANGE ISOLATEION CS SKIP LOCKED DATA

57 Distribution and Clustering in the Accelerator! In general, use defaults No Distribution Keys - random/balanced distribution No Organizing Keys no sequencing of data in a node! For larger tables, orders of magnitude improvement can be seen by specifying organizing and or distribution keys Distribution key: Determines how data is partitioned across worker nodes Organizing key: Determines the row sequence on disk within each node 57

58 Distribution Keys! DB2 table data added to the accelerator is distributed among multiple worker nodes within the accelerator. By default, there is no affinity between the data and a specific worker nodes.! Sometimes, large amounts of data needs to be redistributed or broadcasted within the cluster of worker nodes to join tables. In some cases, the volume is big enough to cause performance penalties.! The IBM DB2 Analytics Accelerator therefore allows specifying columns for the distribution. Using the join columns of two tables as distribution key, causes the rows with the same join values to be stored on the same worker node.! This enables co-located joins without data broadcasts. 58

59 Organizing Keys! Data is stored in data units (extents) of 3 MB. For each of these extends, the accelerator knows the MIN and MAX per column.! Without having any order in the data, the data range between MIN and MAX shows the full spectrum for each extend.! By specifying organizing keys, the data is ordered for the specified columns, allowing smaller value ranges for these columns.! Queries first check if their predicates are matching the MIN/MAX range of an extend. This allows skipping complete extends. 59

60 IDAA Administrative Stored Procedures 60 ACCEL_ADD_ACCELERATOR ACCEL_TEST_CONNECTION ACCEL_REMOVE_ACCELERATOR ACCEL_UPDATE_CREDENTIALS ACCEL_ADD_TABLES ACCEL_ALTER_TABLES ACCEL_REMOVE_TABLES ACCEL_GET_TABLES_INFO ACCEL_LOAD_TABLES ACCEL_SET_TABLES_ACCELERATION ACCEL_CONTROL_ACCELERATOR ACCEL_UPDATE_SOFTWARE ACCEL_GET_QUERY_DETAILS ACCEL_GET_QUERY_EXPLAIN ACCEL_GET_QUERIES Pairing an accelerator to a DB2 subsystem Check of the connectivity from DB2 procedures to the accelerator Removing an accelerator from a DB2 subsystem and cleanup resources on accelerator Renewing the credentials (authentication token) in the accelerator Add a set of tables to the accelerator Alter table definitions for a set of tables on the accelerator (only distribution and organizing keys) Remove a set of tables from the accelerator List set of tables on the accelerator together with detail information Load data from DB2 into a set of tables on the accelerator Enable or disable a set of tables for query off-loading Controlling the accelerator tracing, collecting trace and detail of the accelerator (software level etc.) Update software on the accelerator (transfer versioned software packages or apply an already transferred package, new: also list software both on z/os and accelerator side) Retrieve statement text and query plan for a running or completed Netezza query Generate and retrieve Netezza explain output for a query explained by DB2 Retrieve active and/or history query information from accelerator

61 CURRENT QUERY ACCELERATION! New DB2 Special Register to control the offload of queries from DB2 to the IBM DB2 Analytics Accelerator.! Needs to be set prior to query execution to enable or suppress offload of queries.! Following three values can be used: NONE (DB2 execution only) ENABLE (Offloads the query if eligible and returns an error if the accelerator fails to execute the query) ENABLE WITH FAILBACK (Offloads the query if eligable. If the accelerator fails to execute the query, DB2 will try to execute it instead. No failback is possible after successful OPEN of a query.) SET CURRENT QUERY ACCELERATION ENABLE; 61

62 Routing Criteria A query can be routed to IDAA if:! Query acceleration is enabled System parameter ACCEL set to AUTO or COMMAND If COMMAND, the accelerator must be explicitly started by the START ACCEL command System parameter ACCEL_LEVEL set to a value of V2 Applies to DB2 9 only. ACCEL_LEVEL is deprecated in DB2 10 Special register CURRENT QUERY ACCELERATION set to a value other than NONE Either explicitly or implicitly by system parameter QUERY_ACCELERATION The accelerator is active Use command START ACCEL unless already started! The data of all the referenced tables and columns in the query are loaded and reside in the same accelerator.! The SQL query is among the query types that DB2 for z/os can route (next slide)! The SQL functionality required to execute the query is supported by the IDAA (3 slides forward) 62

63 Heuristic Routing Criteria not just based on elapsed time! DB2 Optimizer uses a set of rules to determine whether a given query is better off being executed in DB2 core engine or routed to the accelerator, such as: In general, typical OLTP access path patterns are not routed to the accelerator, e,g. Equal unique access One fetch access If none of these: WHERE, GROUP BY, ORDER BY, aggregate functions is specified (i.e. all rows are to be returned), the query is not routed If all the tables referred in the query are small, the query is not routed SMALLTABLE_THRESHOLD (number of pages) determines what is a small table SMALLTABLE_THRESHOLD is specified by the DB2 Profile (1) mechanism The default value is 50 If SMALLTABLE_THRESHOLD = -1, this check is ignored, i.e. the table size is not observed when deciding whether to route the query to the accelerator If a large result set is expected, the query is not routed RESULTSET_THRESHOLD (number of rows) determines what is a large result set. RESULTSET_THRESHOLD is specified by the DB2 Profile (1) mechanism The default value is -1, which means that this check is ignored,! Recommendation: Use default values. Change only after rigorous testing! 63 (1)

64 Query Off-load Applicability! IDAA V2 is based on Netezza which supports rich set of SQL and data types BI tools such as Cognos has run on Netezza for years and will run on IDAA as well! Due to very large number of query types and SQL functions not all of them could be processed in V2. Key restrictions include: No static SQL Not all DB2 functions, No Mathematical functions such as SIN, COS, TAN. No advanced string functions such as HEX, POSITION, LOCATE, LEFT, OVERLAY No advanced OLAP functions such as RANK, ROLLUP, CUBE No User Defined Functions No correlated table expressions or recursive correlated table expressions No correlated subquery in the SELECT list Not UTF-16 and MIXED/DBCS EBCDIC No multiple encoding schemes in the same statement Not all DB2 special registers: CURRENT PATH, SERVER, SQLID, SCHEMA, APPLICATION ENCODING SCHEME Not all DB2 data types: LOBs, ROWID, XML, DECFLOAT, BINARY! None of these restrictions is a design problem, IBM plans to lift them in future releases based on customer feedback and needs 64

65 Administration Explorer Used to browse the connected DB2 subsystems, find existing accelerators or browse DB2 objects. New connection profiles or SQL scripts are also created from here. 65

66 SQL Project / Script Window 66

67 SQL Script Editor! In the upper right corner of the SQL Script Editor, you find buttons to run the SQL or to use Visual Explain for displaying the access graph. Run SQL EXPLAIN query with built in Visual Explain! The Accelerator GUI is able to receive the Netezza Plan files for query executions that happened on the accelerator side. These files are parsed and embedded into DB2 Visual Explain.! Distribution and Organizing keys can be altered on the fly based on the Explain output. The accelerator redistributes table data in the background. 67

68 IDAA Studio Query Monitoring 68

69 EXPLAIN " DB2 EXPLAIN function enhanced, provides information about accelerator usage # Whether query qualifies for acceleration and, if not, why # The access path details associated with query execution by IDAA are provided independently of DB2 EXPLAIN by the IDAA Studio. " For each query (irrespective of number of query blocks) row inserted into following tables: # in both PLAN_TABLE and DSN_QUERYINFO_TABLE, if the query is re-routed $ PLAN_TABLE's ACCESSTYPE column is set to a value of 'A' $ DSN_QUERYINFO_TABLE's QI_DATA column shows the converted query text # in DSN_QUERYINFO_TABLE only, if the query is not re-routed $ REASON_CODE and QI_DATA columns provide details! Note that EXPLAIN tables can be populated with above described information even if no accelerator is connected to DB2 # Specifying EXPLAINONLY on START ACCEL command does not establish any communications with an actual accelerator, but enables DB2 to consider its presence in the access path selection process 69

70 DSN_QUERYINFO_TABLE Column Name QUERYNO Column Contents The statement identification, the same value as in PLAN_TABLE. Use it with EXPLAIN_TIME to correlate DSN_QUERYINFO_TABLE and PLAN_TABLE QBLOCKNO QINAME1 QINAME2 APPLNAME PROGNAME VERSION COLLID GROUP_MEMBER SECTNOI SEQNO EXPLAIN_TIME TYPE REASON_CODE QI_DATA SERVICE_INFO If REASON_CODE = 0, the name of the accelerator If REASON_CODE = 0, the location of the accelerator The name of the application plan for the row. Applies only to embedded EXPLAIN statements that are executed from a plan or to statements that are explained when binding a plan. A blank indicates that the column is not applicable. The name of the program or package containing the statement being explained. Applies only to embedded EXPLAIN statements and to statements explained as the result of binding a plan or package. A blank indicates that the column is not applicable. The version identifier for the package. Applies only to an embedded EXPLAIN statement executed from a package or to a statement that is explained when binding a package. A blank indicates that the column is not applicable. The collection ID for the package. Applies only to an embedded EXPLAIN statement that is executed from a package or to a statement that is explained when binding a package. A blank indicates that the column is not applicable. The member name of the DB2 that executed EXPLAIN. The column is blank for non-data sharing. The section number of the statement. The time at which the statement is processed. This time is the same as the BIND_TIME column in PLAN_TABLE. 'A' identifies a query that is considered for acceleration. REASON_CODE identifies if the query qualifies for acceleration or not. If 0, the query qualifies for acceleration. Otherwise, the query cannot be accelerated. More details on the next chart. If REASON_CODE = 0, the text of the converted SQL statement (sent to IDAA). Otherwise, the description of the reason for not qualifying for acceleration IBM internal use only 70 QB_INFO_ROWID IBM internal use only

71 DSN_QUERYINFO_TABLE's REASON_CODE Values Value Description 0 Query qualifies for acceleration 1 No active accelerator was found when EXPLAIN was executed. 2 The special register CURRENT QUERY ACCELERATION is set to NONE. 3 The query is a DB2 short running query or re-routing to the accelerator is not considered advantageous. 4 The query is not read-only 5 The query is running under the private protocol. 6 The cursor is defined as scrollable or rowset cursor. 7 The query refers to multiple encoding schemes. 8 The query FROM clause specifies a data-change-table-reference. 9 The query contains a correlated table expression. 10 The query contains a common table expression reference The query contains an unsupported expression. QI_DATA contains the expression text. The query references table table-name that is either not defined in accelerator, or the table is defined, but is not enabled for query re-routing. The accelerator accelerator-name containing the tables of the query is not started. The column column-name referenced in the query is altered in DB2 after the data is loaded in the accelerator through 999 IBM internal use

72 Running an EXPLAIN via IDAA Data Studio Plugin 72

73 Access Path Graph 73

74 Determining why a query was not accelerated! You can analyze information in DSN_QUERYINFO_TABLE to identify the reason why the query was not accelerated.! NOTE: The Administration Explorer view of the default Accelerator perspective does not allow the viewing of data in tables. You will use the Data perspective for viewing the contents of the DSN_QUERYINFO_TABLE.! To Open the Data Perspective 74

75 DSN_QUERYINFO_TABLE Double click on the QI_DATA cell for your row to see the complete text explaining why the query could not be routed. 75

76 Profile Tables! Four Heuristics Parameters can be adjusted via DB2 PROFILE Tables 76

77 Profile Table Example! Create the profile monitoring tables SYSIBM.DSN_PROFILE_TABLE SYSIBM.DSN_PROFILE_HISTORY SYSIBM.DSN_PROFILE_ATTRIBUTES SYSIBM.DSN_PROFILE_ATTRIBUTES_HISTORY! DDL for tables and the related indexes can be found in member DSNTIJSG of the SDSNSAMP library.! Insert rows into SYSIBM.DSN_PROFILE_TABLE to create a profile. The value that you specify in the PROFILEID column identifies the profile and DB2 uses that value to match rows in the SYSIBM.DSN_PROFILE and DSN_PROFILE_ATTRIBUTES tables. Specifying different columns in DSN_PROFILE_TABLE as filtering criteria can define different scopes for SQL statements. For example, to create a global profile with PROFILE ID 1 you may use the following INSERT statement. INSERT INTO SYSIBM.DSN_PROFILE_TABLE (PROFILEID) VALUES (1); 77 To create a profile for SQL statements from a specific authorization ID and IP address with profile ID 2 you may use INSERT statement similar to the one shown below: INSERT INTO SYSIBM.DSN_PROFILE_TABLE (PROFILEID,AUTHID,LOCATION,PLANNAME,COLLID,PKGNAME,PROFILE_TIME STAMP) VALUES (2,'IDAA2',' ',NULL,NULL,NULL,CURRENT TIMESTAMP);

78 Profile Table Example Continued! Insert rows into the SYSIBM.DSN_PROFILE_ATTRIBUTES table to define the type of monitoring. PROFILEID column: Specify the profile that defines the statements that you want to monitor. Use a value from the PROFILEID column in SYSIBM.DSN_PROFILE_TABLE. KEYWORD column: Specify one of the following monitoring keywords: ACCEL_TABLE_THRESHOLD or ACCEL_RESULTSIZE_THRESHOLD ATTRIBUTEn columns: Specify the appropriate attribute values depending on the keyword that you specify in the KEYWORDS column. For example, the following INSERT statement specifies that DB2 enables result set size checking and sets the threshold as 10,000 rows for all the statements that satisfy the scope that is defined by profile 2. Profile 2 is applicable only to the authorization ID "IDAA2" and IP address INSERT INTO SYSIBM.DSN_PROFILE_ATTRIBUTES (PROFILEID,KEYWORDS, ATTRIBUTE2) VALUES (2,'ACCEL_CHECK_RESULTSIZE',1); INSERT INTO SYSIBM.DSN_PROFILE_ATTRIBUTES (PROFILEID,KEYWORDS, ATTRIBUTE2) VALUES (2,'ACCEL_RESULTSIZE_THRESHOLD',10);! Estimated result size for a query can be found in EXPLAIN output in COMPCARD column of the DSN_DETCOST_TABLE. The size can be inaccurate for various reasons like incomplete/missing/default stats, stale stats, or other deficiencies. Hence it is not recommended to use ACCEL_RESULTSIZE_THRESHOLD keyword normally. To specify that DB2 sets small table threshold as globally, the following INSERT 78 statement can be used:

79 Profile Table Example Start / Stop Profile! Load or reload the profile tables into memory by issuing the following command: START PROFILE! You would see the following messages when the START PROFILE command is issued: DSNT741I -DA12 DSNT1SDV START PROFILE IS COMPLETED. DSN9022I -DA12 DSNT1STR 'START PROFILE' NORMAL COMPLETION ***! Any rows with a Y in the PROFILE_ENABLED column in SYSIBM.DSN_PROFILE_TABLE are now in effect. DB2 monitors any statements that meet the specified criteria.! To disable the monitoring function for a specific profile Delete that row from DSN_PROFILE_TABLE, or change the PROFILE_ENABLED column value to N. Then, reload the profile table by issuing the START PROFILE command as shown below: DELETE FROM SYSIBM.DSN_PROFILE_ATTRIBUTES WHERE PROFILEID=2 START PROFILE! To disable all monitoring and subsystem parameters that have been specified in the profile tables Issue the following command. STOP PROFILE 79

80 Is my Profile being used?! Verify that a profile is used by running an EXPLAIN statement To verify that a statement uses a defined profile, execute EXPLAIN ALL on the query. Profile monitoring must be enabled (using START PROFILE) before running the EXPLAIN ALL. With DB2 Analytics Accelerator, the REASON column on DSN_STATEMNT_TABLE is serving a dual purpose. In addition to the reason why DB2 used default values to estimate the cost, the PROFILEID text is also appended to its value. If DB2 has enough information to estimate the cost (i.e., without using default values) then column REASON in DSN_STATEMNT_TABLE shows just the PROFILEID string concatenated with the PROFILEID value whenever a qualifying profile is used for that query. For example, EXPLAIN populates REASON column with the value "PROFILEID 1", which means PROFILEID number 1 was applied for the particular SQL statement. This entry shows a sample row from DSN_STATEMNT_TABLE when COST_CATEGORY=A.! This entry shows a sample row from DSN_STATEMNT_TABLE when COST_CATEGORY=B. Column REASON in the DSN_STATEMNT_TABLE shows not only the reason for COST_CATEGORY=B, but also it appends the PROFILEID string concatenated with the PROFILEID value. 80

81 IDAA Support and Documentation! DB2_Analytics_Accelerator_for_z~OS 81

82 Traditional Techniques that augment this strategy 82

83 Workload Management Balancing query length, business importance, and service Think about this: Large query submitter behavior: Short query submitter behavior: expect answer now expect answer later Who's impacted more real time?? Priority The ideal workload manager policy for data warehousing: Consistent favoring of shorter running work... through WLM period aging with select favoring of critical business users through WLM explicit prioritization of critical users ** no need to pre-identify shorts either keep em short Business Importance Period Aging High Medium Low Business Importance Long Short Medium Query Type 83

84 Service Classification Period Performance Goal Type Duration text Importance 1 5,000 Velocity = ,000 Velocity = ,000,000 Velocity = ,000,000 Velocity = Discretionary CPU Usage 84

85 Demonstration IBM Corporation

86 Information Management Smart Business Analytics on System z Options for Workload Analysis Stage Questionnaire Quick Workload Test Detailed Online Workload Analysis Purpose! Initial assessment based on size, query response time, update characteristics and customer pain points! Assessment based on dynamic customer workload, runtime statistics, table sizes and SQL! Assessment based on data mart definition for customer data model and offload capabilities in a real DB2 Analytics Accelerator environment. Addresses all inhibitors for offload and data mart definition questions IBM Corporation

87 Information Management Smart Business Analytics on System z Quick Workload Test Collecting information from dynamic statement cache, supported by stepby-step instruction and REXX script (small effort for customer) Uploading compressed file (up to some MB) to IBM FTP server Customer Database Documentation and REXX procedure Data package (mainly unload data sets) Pre-process and load IBM lab Database Quick Workload Test Tool Report Assessment IBM Corporation

88 Information Management Smart Business Analytics on System z Workload Assessment Report Summary based on queries, elapsed time and CPU time Reasons why certain queries may not run in IDAA How much of the current elapsed time may run on IDAA Detailed querylevel assessment of the workload Elapsed time per query 88 SQL statement per query 2012 IBM Corporation

89 Information Management Smart Business Analytics on System z IBM Corporation