Ibm pure data system for analytics n200x

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Ibm pure data system for analytics n200x

  1. 1. © 2013 IBM Corporation IBM® PureData™ System for Analytics N200x Technical Overview Adriano Di Massimo PureData for Analytics Europe IOT
  2. 2. © 2013 IBM Corporation2 Increasing Variety of data requires new techniques Increasing Velocity of data requires higher performance Increasing Volume of data requires growing capacity 35 ZB by 2020 Big Data Challenges for Both Transactions and Analytics are Increasing Demands on Data Systems Millions of transactions per second Telco subscriber activity logging Mobile CloudSocial Big DataCommerce 2020 50x 2010 Analytics Billions of devices & sensors Smart Meters, RFIDs, GPS
  3. 3. © 2013 IBM Corporation Strategic Big Data: the future Model of Datawarehouse Source: Top Ten Technology Trends for 2013 – Gartner Symposium Barcelona Nov 2012
  4. 4. © 2013 IBM Corporation IBM PureData System for Analytics (PDA) Purpose-built analytics engine Integrated database, server and storage Standard interfaces Low total cost of ownership Speed: 10-100x faster than traditional systems Simplicity: Minimal administration and tuning Scalability: Peta-scale user data capacity Smart: High-performance advanced analytics Transforms the User Experience
  5. 5. © 2013 IBM Corporation5 Announcing a New Model! PureData for Analytics now has TWO models N1001 – economical, high performance and scalability N200x – highest performance appliance to-date PureData for Analytics continues to provide: Fastest Time to Value on the market today Optimized Big Data analytics performance Simple administration for fast and agile deployment Accelerate analytic performance using large library of analytic functions The new N200x model addresses these key challenges Increased performance Better density Data center efficiency PureData System for Analytics N200x
  6. 6. © 2013 IBM Corporation Benefits of the IBM PureData System for Analytics The Fastest Performance of Netezza Technology to Date! 6 1 Based on a comparison of the IBM PureData System for Analytics N2001 to the IBM PureData System for Analytics N1001. The performance speed refers to the query times on both macro-analytic and mixed workload tests as conducted in IBM engineering lab benchmarks. The N2001 query times were an average of 3x faster than those of the N1001. Individual results may vary. 2 128 GB/sec scan rate assuming an average of 4x compression across the system. Individual results may vary. 3 Capacity of IBM PureData System for Analytics N2001 compared to previous generation IBM PureData System for Analytics N1001. 4-Each N2001 rack contains 34 hot spare drives and 240 active drives for a ratio of 1 spare per 7 drives. Each N1001 rack contains 4 hot spare drives and 92 active drives for a ratio of 1 spare per 23 drives. The N2001 has 3.3x more spares per active drive. Frequency of disk related service calls expected to decrease by 70% assuming the same drive failure rates. Accelerated Performance of Analytic Queries Accelerated Performance of Analytic Queries Increased Efficiency of your Data Center Increased Efficiency of your Data Center Simplicity and Ease of Administration Simplicity and Ease of Administration 3X faster performance1 for Big Data analytics 128 GB/sec effective scan rate per rack2 to tackle Big Data faster Improved system management and resilience to spend less time managing and more time delivering value 70% FEWER service calls with more spare drives and faster disk regeneration4 50% greater data capacity per rack3 helps optimize data center efficiency More capacity and less power per rack than both Oracle and Teradata
  7. 7. © 2013 IBM Corporation Benefits of the IBM PureData System for Analytics The Fastest Performance of Netezza Technology to Date! 7 1 Based on a comparison of the IBM PureData System for Analytics N2001 to the IBM PureData System for Analytics N1001. The performance speed refers to the query times on both macro-analytic and mixed workload tests as conducted in IBM engineering lab benchmarks. The N2001 query times were an average of 3x faster than those of the N1001. Individual results may vary. 2 128 GB/sec scan rate assuming an average of 4x compression across the system. Individual results may vary. 3 Capacity of IBM PureData System for Analytics N2001 compared to previous generation IBM PureData System for Analytics N1001. 4-Each N2001 rack contains 34 hot spare drives and 240 active drives for a ratio of 1 spare per 7 drives. Each N1001 rack contains 4 hot spare drives and 92 active drives for a ratio of 1 spare per 23 drives. The N2001 has 3.3x more spares per active drive. Frequency of disk related service calls expected to decrease by 70% assuming the same drive failure rates. Accelerated Performance of Analytic Queries Accelerated Performance of Analytic Queries Increase Efficiency of your Data Center Increase Efficiency of your Data Center Simplicity and Ease of Administration Simplicity and Ease of Administration 3X faster performance1 for Big Data analytics 128 GB/sec effective scan rate per rack2 to tackle Big Data faster Improved system management and resilience to spend less time managing and more time delivering value 70% FEWER service calls with more spare drives and faster disk regeneration4 50% greater data capacity per rack3 helps optimize data center efficiency More capacity and less power per rack than both Oracle and Teradata
  8. 8. © 2013 IBM Corporation The PureData System for Analytics AMPP Architecture PureData System for Analytics Appliance FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU S-Blades Network Fabric Field Programmable Gate Array = a blank canvas until it’s configured Advanced Analytics Advanced Analytics LoadersLoaders ETLETL BIBI Applications Disk Enclosures “Lite” Host (IBM xSeries, Red Hat Linux)
  9. 9. © 2013 IBM Corporation The PureData System for Analytics AMPP Architecture PureData System for Analytics Appliance FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU S-Blades Network Fabric Field Programmable Gate Array = a blank canvas until it’s configured Advanced Analytics Advanced Analytics LoadersLoaders ETLETL BIBI Applications Disk Enclosures “Lite” Host (IBM xSeries, Red Hat Linux) • AMPP Architecture - Combine the benefits of both technologies: SMP simplicity and MPP performance
  10. 10. © 2013 IBM Corporation Select State, Age, Gender, count(*) From MultiBillionRowCustomerTable Where BirthDate < ‘‘‘‘01/01/1960’’’’ And State in (’’’’FL’’’’, ’’’’GA’’’’, ‘‘‘‘SC’’’’, ‘‘‘‘NC’’’’) Group by State, Age, Gender Order by State, Age, Gender S-Blade Data Stream Processing FPGA Core CPU Core Decompress Project Restrict Visibility SQL & Advanced Analytics From MultiBillionRowCustomerTableWhere BirthDate <‘‘‘‘01/01/1960’’’’ Group by State, Age, Gender Select State, Age, Gender, count(*) And State in (‘‘‘‘FL’’’’, ‘‘‘‘GA’’’’, ‘‘‘‘SC’’’’, ‘‘‘‘NC’’’’) Order by State, Age, Gender From Select Where Group by Stream via Zone Map From 10
  11. 11. © 2013 IBM Corporation Select State, Age, Gender, count(*) From MultiBillionRowCustomerTable Where BirthDate < ‘‘‘‘01/01/1960’’’’ And State in (’’’’FL’’’’, ’’’’GA’’’’, ‘‘‘‘SC’’’’, ‘‘‘‘NC’’’’) Group by State, Age, Gender Order by State, Age, Gender S-Blade Data Stream Processing FPGA Core CPU Core Decompress Project Restrict Visibility SQL & Advanced Analytics From MultiBillionRowCustomerTableWhere BirthDate <‘‘‘‘01/01/1960’’’’ Group by State, Age, Gender Select State, Age, Gender, count(*) And State in (‘‘‘‘FL’’’’, ‘‘‘‘GA’’’’, ‘‘‘‘SC’’’’, ‘‘‘‘NC’’’’) Order by State, Age, Gender From Select Where Group by Stream via Zone Map From • Transparent I/O performance optimization - Use of FPGA (streaming approach) guarantees the highest and stable scan rate 11
  12. 12. © 2013 IBM Corporation CPU Request General Purpose Storage Request Transactional System used for BI Data Warehouse Workload Fewer requests, lots of data manipulation 12
  13. 13. © 2013 IBM Corporation Results Transactional System used for BI Request General Purpose Storage CPU Data Warehouse Workload Transaction systems are inefficient for data shuffling 13
  14. 14. © 2013 IBM Corporation Results PureData for Analytics System Intelligent StorageCPU Request Asymmetric Massively Parallel Processing Data Warehouse Blades Designed for Tera-scale Business Intelligence 14
  15. 15. © 2013 IBM Corporation Results Netezza Performance Server™ System Intelligent StorageCPU Request 1% of network traffic 2% of CPU requirements Asymmetric Massively Parallel Processing Data Warehouse Blades Highly efficient data movement 15
  16. 16. © 2013 IBM Corporation N200x: What’s new 16 FPGA Core CPU Core Decompress Project Restrict Visibility SQL & Advanced Analytics From Select Where Group by 120MB/sec 500MB/sec 800 MB/sec + 480 MB/sec N1001N200x 65 MB/sec 130 MB/sec 130 MB/sec 325 MB/sec (2.5 drives / core) 1000 MB/sec 1000 MB/sec + 1300 MB/sec PureData System for Analytics
  17. 17. © 2013 IBM Corporation How We Did it, Conceptually 17 Balanced Performance FPGA Core CPU Core 500 MB/sec 800 MB/sec + 1 drive @ 120 MB/sec More Drives with Faster Scan Rates Leading to Faster Performance Faster FPGA Cores, Driving Higher Performance 2.5 drives @ 130 MB/sec each 1000 MB/sec 1000 MB/sec + CPU Core • Analyze FPGA Core • Decompress • Project • Filter
  18. 18. © 2013 IBM Corporation PureData System for Analytics N1001 18 S-Blades Disks Memory CPU FPGA 8 8 6 6 6 6 6 14 Blades per full rack Each S-Blade 8 CPU Cores 8 FPGA Engines Sized to handle 8 disks or 960 MB/sec 92 Active Data Slices deliver 11 GB/sec raw disk throughput 8 8 Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA
  19. 19. © 2013 IBM Corporation PureData System for Analytics N200x 19 S-Blades Disks 40 40 32 32 32 32 32 7 Blades per full rack Each S-Blade 16 CPU Cores 16 FPGA Engines sized to handle 40 disks or 5.2 GB/sec 240 Active Data Slices deliver 31.2 GB/sec raw disk throughput 3x More Disk Throughput Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU FPGA 16 16
  20. 20. © 2013 IBM Corporation Netezza Platform Software v7.1 Highlights Scheduler rules for WLM Short query prioritization Snippet Result Cache Faster Bulk Fetching with ODBC Password aging and expiry nzPortal enhancements Cryptographic Standards (s800-131a) Support for Replication v1.5 Support for INZA 3.0 Resiliency Faster rebalance for failed disks Disk validation support Large scale disk replacement Call Home v1.0 Enhanced System Health Checks v2.2 ILMT support for Growth on Demand Platform & OS Client Kit support for AIX 7.1 RHEL 6.4 certification SQL Enhancements Multiple Schema (3-part naming) Orphan column query NOT IN / EXIST improvements CASE WHEN improvements Support 24 hour datetime CESU-8 support Transaction Enhancement Truncate table in TXN Improved view validation Temp table enhancements Deprecate Web Admin ETL ODBC loader support for INTERVAL Netezza Performance Portal Cryptographics standards (s800-131a) Scheduler rules History type AUDIT Restrict nzPortal users Groom dialogs 20
  21. 21. © 2013 IBM Corporation Directed Data Processing 21 Distribute Restrict Optimization – Use distribution key to target scans Transaction history distributed on customer ID Hosts
  22. 22. © 2013 IBM Corporation Directed Data Processing 22 Distribute Restrict Optimization – Use distribution key to target scans Hosts select from tx_hist where custid in (1, 2) custid = 1 custid = 1 custid = 1 custid = 1 custid = 2 custid = 2 custid = 2 custid = 2 custid = 3 custid = 3 custid = 3 custid = 3 select from tx_hist where custid = 3
  23. 23. © 2013 IBM Corporation Page Granular Zone Maps 23 October November Other 3 MB where col = October Total 12 MB (4 x 3 MB)
  24. 24. © 2013 IBM Corporation Page Granular Zone Maps 24 24X finer granularity October November Other Total 12 MB (4 x 3 MB) Total 1 MB (8 x 128KB) 3 MB 128 KB where col = October
  25. 25. © 2013 IBM Corporation Snippet Result Cache Observation • BI/Web page generated reports create queries with limited variation • Repeated tables, columns, restrictions Keep intermediate results • From simple table scans • Using existing storage Internal Benchmarking Results • Up to 2.5X faster for tactical queries 25
  26. 26. © 2013 IBM Corporation Snippet Result Cache SQL Query • Preserves intermediate tables generated by snippets for use in subsequent queries • Queries do NOT have to be identical to benefit Snippet Snippet Snippet Snippet Snippet Snippet Snippet Snippet SQL Query Snippet Snippet Snippet Snippet Snippet Snippet 26
  27. 27. © 2013 IBM Corporation ODBC Bulk Fetch Enhancements Delivers a more competitive select performance! ‒ Eliminates expensive conversion routines when the client and database share the same data type ‒ Nearly 4X faster for select data types! Sample improvements: Data Type Today NPS 7.1 Times Faster % Gain Char(ns) 175.704 45.009 3.90 74% Int1 101.38 54.86 1.85 46% Int8 76.421 24.198 3.16 68% Boolean (bit) 195.27 133.3441 1.46 31% Double 75.684 31.271 2.42 58% 27
  28. 28. © 2013 IBM Corporation Benefits of the IBM PureData System for Analytics The Fastest Performance of Netezza Technology to Date! 30 1 Based on a comparison of the IBM PureData System for Analytics N2001 to the IBM PureData System for Analytics N1001. The performance speed refers to the query times on both macro-analytic and mixed workload tests as conducted in IBM engineering lab benchmarks. The N2001 query times were an average of 3x faster than those of the N1001. Individual results may vary. 2 128 GB/sec scan rate assuming an average of 4x compression across the system. Individual results may vary. 3 Capacity of IBM PureData System for Analytics N2001 compared to previous generation IBM PureData System for Analytics N1001. 4-Each N2001 rack contains 34 hot spare drives and 240 active drives for a ratio of 1 spare per 7 drives. Each N1001 rack contains 4 hot spare drives and 92 active drives for a ratio of 1 spare per 23 drives. The N2001 has 3.3x more spares per active drive. Frequency of disk related service calls expected to decrease by 70% assuming the same drive failure rates. Accelerate Performance of Analytic Queries Accelerate Performance of Analytic Queries Increased Efficiency of your Data Center Increased Efficiency of your Data Center Simplicity and Ease of Administration Simplicity and Ease of Administration 3X faster performance1 for Big Data analytics 128 GB/sec effective scan rate per rack2 to tackle Big Data faster Improved system management and resilience to spend less time managing and more time delivering value 70% FEWER service calls with more spare drives and faster disk regeneration4 50% greater data capacity per rack3 helps optimize data center efficiency More capacity and less power per rack than both Oracle and Teradata
  29. 29. © 2013 IBM Corporation Benefits of the IBM PureData System for Analytics The Fastest Performance of Netezza Technology to Date! 32 1 Based on a comparison of the IBM PureData System for Analytics N2001 to the IBM PureData System for Analytics N1001. The performance speed refers to the query times on both macro-analytic and mixed workload tests as conducted in IBM engineering lab benchmarks. The N2001 query times were an average of 3x faster than those of the N1001. Individual results may vary. 2 128 GB/sec scan rate assuming an average of 4x compression across the system. Individual results may vary. 3 Capacity of IBM PureData System for Analytics N2001 compared to previous generation IBM PureData System for Analytics N1001. 4-Each N2001 rack contains 34 hot spare drives and 240 active drives for a ratio of 1 spare per 7 drives. Each N1001 rack contains 4 hot spare drives and 92 active drives for a ratio of 1 spare per 23 drives. The N2001 has 3.3x more spares per active drive. Frequency of disk related service calls expected to decrease by 70% assuming the same drive failure rates. Accelerate Performance of Analytic Queries Accelerate Performance of Analytic Queries Increase Efficiency of your Data Center Increase Efficiency of your Data Center Simplicity and Ease of Administration Simplicity and Ease of Administration 3X faster performance1 for Big Data analytics 128 GB/sec effective scan rate per rack2 to tackle Big Data faster Improved system management and resilience to spend less time managing and more time delivering value 70% FEWER service calls with more spare drives and faster disk regeneration4 50% greater data capacity per rack3 helps optimize data center efficiency More capacity and less power per rack than both Oracle and Teradata
  30. 30. © 2013 IBM Corporation Spend Less Time Managing and More Time Innovating 33 No dbspace/tablespace sizing and configuration No redo/physical/Logical log sizing and configuration No page/block sizing and configuration for tables No extent sizing and configuration for tables No Temp space allocation and monitoring No RAID level decisions for dbspaces No logical volume creations of files No integration of OS kernel recommendations No maintenance of OS recommended patch levels No JAD sessions to configure host/network/storage Data Experts, not Database Experts Easy Administration Portal No software installation No indexes and tuning No storage administration
  31. 31. © 2013 IBM Corporation IBM Netezza Performance Portal 2.0 Consolidating WebAdmin and Portal for Simple Admin 34 Simple web user interface – Part of the PureData System for Analytics New functional and usability enhancements – Administrative Functions • Hardware view & alerts • Database objects administration • User & Group management • View active sessions • Workload Management • View Events • Table skew/storage search • Capacity Planning – Monitor enhancements • Usability improvements – allow to resize monitors and mark not-monitored periods – Customer requested improvements • Show locks • Monitor System Resources • Perform System Administration • Understand & Predict Capacity
  32. 32. © 2013 IBM Corporation Netezza Performance Portal 2.1 • Support for Scheduler rules • Ability to restrict users from adding Hosts • New panel for Resource Allocation Performance History • Ability to view history of BAR operations • Support for EXPLAIN command with Query History enabled • Client field filters for Query History view • History type AUDIT added to Query History • IBM HTTP server replaces Apache server
  33. 33. © 2013 IBM Corporation Scheduler Rules for WLM 1. Replaces the Gatekeeper Scheduler 2. Ability to limit, prioritize, and abort queries through simple rules 3. Ability to match on group, plan type, priority, estimate, user, db, table, client info & tags 4. Great for large scale environments running in high concurrency 5. Helps to tune out query contention resulting from high use of disk and memory Gatekeeper GRASQB 36
  34. 34. © 2013 IBM Corporation Scheduler Rule Examples Modifying scheduler rules: – IF USER IS sam THEN INCREASE PRIORITY – IF TYPE IS LOAD THEN SET PRIORITY LOW – IF TAG IS eom THEN EXECUTE AS RESOURCEGROUP group42 – IF ESTIMATE >= 5 ESTIMATE < 12 THEN INCREASE PRIORITY – IF CLIENT_APPLICATION_NAME IS Cognos THEN ABORT – IF CLIENT_ACCOUNTING_STRING IN (‘weekly_report’, ‘daily_report’) THEN SET PRIORITY HIGH Limiting scheduler rules: – IF TAG IS cube THEN LIMIT 1 – IF TAG IS cube USER IS sam THEN LIMIT 2 – IF TYPE IS GENERATE STATISTICS THEN LIMIT 1
  35. 35. © 2013 IBM Corporation38 Real time link between your appliance and IBM • Automatic problem reporting • Ongoing Inventory tracking • Operational status and health for proactive support Improves support efficiency, effectiveness and the client experience • Reduces your Total Cost of Ownership (TCO) • Reduces duration of most common support calls • Raises our awareness of your issues sooner • Makes support more proactive without requiring you to do more • Helps to improve product and support quality over time Call Home Service
  36. 36. © 2013 IBM Corporation39 How it Works • Targeted NZEVENTs automatically run nzOpenPmr, collect data and email IBM • New email identifies you, appliance (identity, location and status) and fault data • Attached diagnostics include: + sysmgr and eventmgr logs + SMART logs for disks + cluster logs for Host issues + crash stacks for core dumps (avg. size: 15 Kbytes) • Automation opens PMR, posts diagnostic data and replies w/ PMR Configuration and Enablement • Requires recent NPS fixpack and functional SMTP routing • Additional configuration in callHome.txt + IBM Customer (ICN) + Machine Type, Model and S/N • Identity your Support contact and email alias • nzOpenPmr configuration creates new event table entry SAMPLE callHome.txt # /nz/data/config/callHome.txt # Installation-specific attributes. customer.company = Your Business customer.address1 = Appliance Install Address customer.address2 = Installed City, State, Zip customer.ICN = 1234567 contact1.name = Joe SysAdmin contact1.phone = 1.617.555.1212 contact1.email = jsysadmin@us.company.com contact1.cell = 1-508-555-9876 contact1.events = ALL contact2.name = D.B. Admin contact2.phone = +1.508.555.1212 contact2.email = dadmin@us.company.com contact2.cell = +1.508.555.2121 system.description = Test System system.location = Rm 122 Aisle F Slot 2 system.model = N2001-005 system.MTM = 3565 / DD0 system.serial = NZ3xxxx system.CC = 2 char Country Code (ISO) Call Home Service – How it Works
  37. 37. © 2013 IBM Corporation40 • Less than 5 minutes to rebalance a failed Blade – Unmount and remount disk rather than reboot the blade • Rebalance occurs under normal “pause” Blade – Avoids losing any process work (Loads or queries) . . . . . . . . . . . . . . . S-Blades . . . Faster Rebalance for failed Drives
  38. 38. © 2013 IBM Corporation Summary of competitive advantages 41 Transparent I/O performance optimization – Use of FPGA (streaming approach) guarantees the highest and stable scan rate, without any need of expensive performance improvement features like: • automatic dynamic storage differentiated by data access behaviour («virtual storage») • «in-memory» solution or • «columnar» storage Specific RDMS – Optimized software by removing all unnecessary and expensive typical OLTP RDBMS features like: • Log/journaling management • Lock management • Referential integrity feature management AMPP Architecture – Combine the benefits of both technologies: SMP simplicity and MPP performance – Symmetric «Shared Nothing» Architecture has limitations: • Frequent «bottlenecks» due to the mix of heterogenuous processes on the same physical resources • Risk of unbalanced use of clustered resources due to bad access configuration
  39. 39. © 2013 IBM Corporation Summary of competitive advantages Workload Management – World-class workload manager functionalities – Maximize resource usage without complex workload management settings Availability and Resiliency – No need of «fallback-like» / table mirroring functionalities • Disk availability is guaranteed by Raid1 • Zero-downtime in case of node failure is guaranteed by built-in spare S-blades – Efficient Incremental backup avoiding complex techniques like partitioning archive Simplicity – Zero-tuning • «Zone-map»: automatic anti-index approach to avoid scanning of unnecessary data for users query • Automatic update of data demographic statistics • Automatic partitioning • Ad-hoc query enabling technology – Near-zero administration – Data model agnostic 42
  40. 40. © 2013 IBM Corporation Inside the
  41. 41. © 2013 IBM Corporation • 8 Disk Enclosures • 96 1TB SAS Drives (4 hot spares) • RAID 1 Mirroring • 14 PureData for Analytics S-Blades™ • 2 Intel Quad-Core 2+ GHz CPUs • 4 Dual-Engine 125 MHz FPGAs • 24 GB DDR2 RAM • Linux 64-bit Kernel • 2 Hosts (Active-Passive): • 2 Quad-Core Intel 2.6 GHz CPUs • 7x146 GB SAS Drives • Red Hat Linux 5 64-bit • User Data Capacity: 128 TB** • Data Scan Speed: 145 TB/hr** • Load Speed (per system): 5+ TB/hr • Power Requirements: 7.6 kW • Cooling Requirements: 7.8 kW **: 4X compression assumed Scales from ¼ Rack to 10 Racks 32 TB to 1.2 PB of User Data PureData System for Analytics Hardware Overview: Model N1001 44
  42. 42. © 2013 IBM Corporation PureData System for Analytics Hardware Overview: Model N200x User Data Capacity: 192 TB* Data Scan Speed: 450 TB/hr* Load Speed (per system): 5+ TB/hr Power Requirements: 7.5 kW Cooling Requirements: 27,000 BTU/hr * Assuming 4X compression 2 Hosts (Active-Passive) 2 6-Core Intel 3.46 GHz CPUs 7x300 GB SAS Drives Red Hat Linux 6 64-bit 7 PureData for Analytics S-Blades™ 2 Intel 8 Core 2+ GHz CPUs 2 8-Engine Xilinx Virtex-6 FPGAs 128 GB RAM + 8 GB slice buffer Linux 64-bit Kernel 12 Disk Enclosures 288 600 GB SAS2 Drives 240 for User Data 14 for S-Blades 34 Spare RAID 1 Mirroring Scales from ½ Rack to 4 Racks 45
  43. 43. © 2013 IBM Corporation PureData System for Analytics Models 46 PureData System for Analytics N1001 PureData System for Analytics N200x Blade Type HS22 HX5 CPU Cores / Blade 2 x 4 Core Intel CPUs 2 x 8 Core Intel CPUs # Disks 96 x 3.5” / 1 TB SAS (92 Active) 288 x 2.5” / 600GB SAS2 (240 Active) Raw Capacity 96 TB 172.8 TB Total Disk Bandwidth ~11 GB/s ~32 GB/s S-Blades per Rack (cores) 14 (112) 7 (112) S-Blade Memory 24 GB 128 GB Rack Configurations ¼, ½, 1, 1 ½, 2 – 10 ¼, ½, 1, 2, 4 (6 and 8 rack configs to follow) FPGA Cores / Blade 8 (2 x 4 Engine Xilinx FPGA) 16 ( 2 x 8 Engine Xilinx Virtex 6 FPGA) User Data / Rack * 128 TB 192 TB * Assuming 4x Compression
  44. 44. © 2013 IBM Corporation New Offerings for the Entry-Level Market 47 PureData System for Analytics ‘Lite’ (Q4’13) – Entry-Level Striper Configuration (N2002-002) – 32 TB usable capacity – 50% better performance than a TwinFin-3 (N1001- 002) – Improved resiliency over TwinFin-3 with more spare drives IBM Netezza Platform Development Software – Virtualized Image supporting VMWare vSphere 5.1 – Documented reference architecture and best practices – Install Licensing – 16+ TB usable capacity (compressed) – Development and Test Only
  45. 45. © 2013 IBM Corporation IBM Netezza Platform Development Software Full function NPS 7.x software for DEV and TEST only In a fully virtualized offering Fully supported, simple to setup, running in minutes Just like an appliance Licensed per virtual server System Limits 16 CPU cores 64GB RAM 4TB raw space (~16TB w/compression) Host SPU SPU
  46. 46. © 2013 IBM Corporation IBM Announces Growth on Demand for PureData System for Analytics Program BasicsProgram Basics Instant UpgradeInstant Upgrade Simple DeploymentSimple Deployment New Offering called “Growth on Demand” Purchase a larger system, license 50% of the capacity and performance Grow in easy steps Additional capacity enabled by licensing and software configuration Capacity can be added, but not reduced with this program Provision one system Expand through licensing Zero impact on data center operations 49
  47. 47. © 2013 IBM Corporation Growth on Demand Single Rack Example Existing part (seven such parts, one for each model) New part : min 50% entitled capacity (both storage and performance), one for each existing part New part : adding 12.5% extra capacity (both storage and performance), one for each PDA model size 50% capacity 100% capacity FullRack ‘Normal’ FullRack ‘Minimumcapacity’ Add-on Add-on Add-on Add-on ‘Extracapacity’parts 50
  48. 48. © 2013 IBM Corporation IBM DB2 Analytics Accelerator Now even faster with N200x The PureData System for Analytics N200x is also the next generation DB2 Analytics Accelerator Providing the same improvements to our DB2 for zOS customers
  49. 49. © 2013 IBM Corporation Big Data Meets Deep Analytics 52 Analytics without constraint
  50. 50. © 2013 IBM Corporation IBM Netezza Analytics Ecosystem PureData for Analytics AMPP Platform Software Development Kit Software Development Kit 3rd Party In-Database Analytics 3rd Party In-Database Analytics Netezza In-Database Analytics Netezza In-Database Analytics User-Defined Extensions (UDF,UDA, UDTF,UDAP) Transformations Mathematical Geospatial [Esri / nzSpatial] Predictive Statistics Time Series Data Mining Fuzzy Logix SAS Zementis IBM SPSS Language Support (Map/Reduce, Java, Python, Lua, Perl, C, C++, Fortran, PMML) Mathworks Revolution Analytics BI Tools Visualization Tools 53
  51. 51. © 2013 IBM Corporation Integrated by Design IBM Netezza Analytics Version 2.0 54 Netezza In-Database Analytics 2.0 Transformations Mathematical Geospatial Predictive Statistics Time Series Data Mining No data movement Analyze deep and wide data High performance, parallel computation
  52. 52. © 2013 IBM Corporation55 Basic Math* Permutation and Combination* Greatest Common Divisor and Least Common Multiple* Conversion of Values* Exponential and Logarithm* Gamma and Beta Functions Matrix Algebra+ Area Under Curve* Interpolation Methods* Transformations MathematicalTime Series Linear Regression+ Logistic Regression+ Classification Bayesian Sampling Model Testing Geospatial Data Type Geometric Functions Geometric Analysis Predictive Geospatial * Fuzzy Logix DB Lytix capabilities + Netezza Analytics and Fuzzy Logix DB Lytix capabilities Data Profiling / Descriptive Statistics+ General Diagnostics Statistics+ Sampling Data prep Pre-Built In-Database Analytics Descriptive Statistics+ Distance Measures* Hypothesis Testing* Chi-Square & Contingency Tables* Univariate & Multivariate Distributions+ Monte Carlo Simulation* Autoregressive+ Forecasting* Association Rules+ Clustering+ Feature Extraction+ Discriminant Analysis* Data Mining Statistics
  53. 53. © 2013 IBM Corporation56 What’’’’s New in N200x: Summary 50% Greater Storage Capacity per rack 3x scan rate vs N1001 series Improved Resiliency and Fault Tolerance – More spare drives per cabinet – Faster drive regeneration – Online Firmware upgrades NPS 7.0 – Distribute Restrict Optimization – Page Granular Zone Maps
  54. 54. © 2013 IBM Corporation Catch the Striper “Wave” Why Upgrade to the IBM PureData System for Analytics N2000 Series Appliance
  55. 55. © 2013 IBM Corporation Why Upgrade Your TwinFin System? PureData System for Analytics N2002 provides: The latest hardware – 3x faster scan rates1 – 128 GB/sec effective scan rate per rack2 – 6x more memory per Blade server – Leverage future software enhancements longer Increased data center efficiency with 50% greater data capacity per rack3 Improved system management & resiliency 70% fewer service calls with more spare drives and faster disk regeneration4 Catch the Striper Wave before TwinFin comes to end of life 1 Based on a comparison of the IBM PureData System for Analytics N200x to the IBM PureData System for Analytics N1001. The performance speed refers to the query times on both macro- analytic and mixed workload tests as conducted in IBM engineering lab benchmarks. The N200x query times were an average of 3x faster than those of the N1001. Individual results may vary. 2128 GB/sec scan rate assuming an average of 4x compression across the system. Individual results may vary. 3 Capacity of IBM PureData System for Analytics N200x compared to previous generation IBM PureData System for Analytics N1001. 4 Each N200x rack contains 34 hot spare drives and 240 active drives for a ratio of 1 spare per 7 drives. Each N1001 rack contains 4 hot spare drives and 92 active drives for a ratio of 1 spare per 23 drives. The N200x has 3.3x more spares per active drive. Frequency of disk related service calls expected to decrease by 70% assuming the same drive failure rates.
  56. 56. © 2013 IBM Corporation IBM Netezza’s Market – Leading Evolution World’s First Data Warehouse Appliance World’s First 100 TB Data Warehouse Appliance World’s First Petabyte Data Warehouse Appliance World’s First Analytic Data Warehouse Appliance NPS® 8000 Series TwinFin™ with i-Class™ Advanced Analytics NPS® 10000 Series TwinFin™ World’s fastest and “greenest” analytical platform 2003 2006 2009 2010 2011 2013 PureData™ System for Analytics N2002
  57. 57. © 2013 IBM Corporation Striper Leverages the Latest Hardware 3x faster scan rate Drives per core have gone from 1 drive @ 120 MB/sec to 2.5 drives @ 130 MB/sec FPGA cores have gone from 500 MB/sec to 1000 MB/sec CPU cores have gone from 800 MB/sec to 1000+ MB/sec 6x more memory per Blade (better leveraged by NPS 7.x) 50% greater data capacity per rack
  58. 58. © 2013 IBM Corporation Striper vs. TwinFin Hardware Comparison PureData System for Analytics N1001 (TwinFin) PureData System for Analytics N2002 (Striper) Blade Type HS22 HX5 CPU Cores / Blade 2 x 4 Core Intel CPUs 2 x 8 Core Intel CPUs # Disks 96 x 3.5” / 1 TB SAS (92 Active) 288 x 2.5” / 600GB SAS2 (240 Active) Raw Capacity 96 TB 172.8 TB Total Disk Bandwidth ~11 GB/s ~32 GB/s S-Blades per Rack (cores) 14 (112) 7 (112) S-Blade Memory 24 GB 128 GB Rack Configurations ¼, ½, 1, 1 ½, 2 – 10 entry level, ½, 1, 2, 4 FPGA Cores / Blade 8 (2 x 4 Engine Xilinx FPGA) 16 ( 2 x 8 Engine Xilinx Virtex-6 FPGA) User Data / Rack * 128 TB 192 TB * Assuming 4x Compression
  59. 59. © 2013 IBM Corporation PureData System for Analytics N2002 HW Overview User Data Capacity: 192 TB2 Data Scan Speed: 478 TB/hr* Load Speed (per system): 5+ TB/hr Power Requirements: 7.5 kW Cooling Requirements: 27,000 BTU/hr 1 Clients interested in a smaller entry point should refer to the N2002-002 model 2 Assuming 4X compression Scales from ½ Rack to 4 Racks 1 2 Hosts (Active-Passive) 2 Intel 2.7 GHz Sandy Bridge CPUs 7x300 GB SAS Drives Red Hat Linux 6 64-bit 7 PureData for Analytics S-Blades™ 2 Intel 8 Core 2+ GHz CPUs 2 8-Engine Xilinx Virtex-6 FPGAs 128 GB RAM + 8 GB slice buffer Linux 64-bit Kernel 12 Disk Enclosures 288 600 GB SAS2 Drives • 240 for User Data • 14 for S-Blades • 34 Spare RAID 1 Mirroring
  60. 60. © 2013 IBM Corporation Striper Wave Offer Best discounting on the purchase of Striper ever! – Must return TwinFin machine(s) Leave the migration to us!* (estimated migration 1-2 weeks based on data and network) – Review Migration Planning Questionnaire – Develop Migration Plan – Support development of test strategy – Prepare Environment & Install tools for Data & Code Migration – Migrate Data & Code to new appliance* – Removal and secure disposal of TwinFin machine(s) Most favorable financing available – Pick your Plan** – Defer Payments for 90 days or more; or – 0% financing with No Upfront Cost; or – Lowest FMV Leasing Rates Available. * Beyond 100 hours of service, IBM can provide additional fee-based migration services via IBM’’’’s Lab Service Team for test execution support, complex environment considerations, handling for large data volumes, etc. ** With approved credit
  61. 61. © 2013 IBM Corporation Appliance Migration Service Benefits Reduce migration risks with proven guidance and expertise Leverage best practices & tools to accelerate migration activities Accelerate your ROI of new appliance Deliverables Migration Plan Migrated data/code in new Appliance* Features Up to 100 hours of Migration Services from IBM for one environment (20 Client Technical Professionals/80 Lab Services) – Project Management – Review Migration Planning Questionnaire – Develop Migration Plan – Support development of Test Strategy – Prepare Environment & Install tools for Data & Code Migration – Migrate Data & Code to new appliance* Beyond 100 hours of service, IBM can provide additional fee-based migration services via IBM’s Lab Service Team for test execution support, complex environment considerations, handling for large data volumes, etc. Quickly migrate your old Netezza Appliance to the latest PureData System for Analytics Appliance! * IBM will provide ETL/ Netezza connectivity, however 100 hours does not include manipulation of ETL code or enablement of newer ETL features *100 hours does not include test execution * Large data volumes/low capacity network may require additional fee-based Services time to complete migration * Estimated migration 1-2 weeks based on data and network, per environment
  62. 62. © 2013 IBM Corporation TwinFin to Striper Summary Better Longevity – TwinFin has been in the field since 2009 – IBM PureData System for Analytics N2000 series appliances have been out since February 1, 2013 – now is the time to make the switch – The new system is fully supported and allows you to take full advantage of many new enhancements Faster scan rates Better resiliency Greater density for data center efficiency Appealing Financials – Most favorable discount on Striper possible – Financing options from IGF – Bundled migration services
  63. 63. © 2013 IBM Corporation IBM Netezza Replication Services v1.5 Asynchronous, Homogeneous Replication for PureData System for Analytics (formerly Netezza) Simplifying Data Replication for Disaster Recovery and Scale
  64. 64. © 2013 IBM Corporation What’s This Replication Thing? IBM Netezza Replication Services keeps a collection of databases identical across multiple Netezza appliances. Our solution focuses on replication for Disaster Recovery. Disaster recovery: a replication use case in which failure of hardware or software in its operational environment causes no permanent loss of data or functionality. Data
  65. 65. © 2013 IBM Corporation Two Common Approaches When NOT Using Replication Two Common Options: Dual Feed ETL and Backup Shipping Primary DR Site ETL WAN WAN Full Backup + Incrementals Full Restore + Incrementals Dual Feed ETL Backup Shipping
  66. 66. © 2013 IBM Corporation Two Common Approaches When NOT Using Replication Dual ETL Feed Backup and Restore Benefits Drawbacks Benefits Drawbacks Data can arrive at both systems at roughly the same time. Easier to “flip” DR site to be primary site in the event of a failure. Some processes (such as sequences) may result in different values. In the event of an ETL error, bad data can be propagated to the DR site. Additional overhead for customer Only changed data is moved across the network. Backups can later be stored as part of backup strategy. Offers more control over timing of DR loads, not tied to ETL process. Occasional full backups recommended to ensure consistency, especially if backup files are later used for backup storage. Can result in very large data transfers, especially during initial full backups. Incremental backups do have some impact on system performance.
  67. 67. © 2013 IBM Corporation Replication Requirements Targeted with Our Solution Disaster Recovery solution for PureData Systems for Analytics – Protect business critical data – Meet regulatory requirements Scalable infrastructure that supports: – Growing user populations – Distributed access to BI and DW applications – Geographically dispersed user populations – Higher levels of concurrent access for BI and DW apps – Reduced application connection and access latencies (“put the data closer”) 70
  68. 68. © 2013 IBM Corporation Replication Solution Overview Homogeneous (PDA / Netezza only) Asynchronous, “warm stand-by” ( there is latency to the DR box) – Synchronous commit for the source PTS – Asynchronous transfer to the subordinate PTS, Subordinate Appliance(s) Hybrid Replication: SQL Statement & By Value • (Intelligence of solution decides which mode to use) – SQL statement-level replication (preferred, default) – Replication By-Value (when necessary)
  69. 69. © 2013 IBM Corporation • IBM PureData System for Analytics N200x (Striper) • IBM PureData System for Analytics N1001 (TwinFin) • IBM PureData System for Analytics N1000 (TwinFin) • IBM Netezza 100 (Skimmer) • IBM Netezza High Capacity Appliance C1000 • NEC InfoFrame DWH Appliance Supported Appliances 72 You can upgrade to IBM Netezza release 7.1.0.x from any 6.0.x or 6.1.x release, or from an earlier release of 7.1.0.x to a later 7.1.0.x release.
  70. 70. © 2013 IBM Corporation IBM Netezza Replication Services - Architecture
  71. 71. © 2013 IBM Corporation Description of “by SQL” Replication Method Preferred method of replication for our solution – Master node accepts SQL Data Manipulation Language (DML) and Data Definition Language (DDL) that update the replicated databases. – SQL statements captured to a replication log – Logs copied across the network to multiple Netezza nodes – Subordinates replay the SQL – Fewer performance implications to customer workloads (near zero impact) • Small amount of information to log/transfer The SQL statement that made the change • External table files logged that are referenced by DML operations Byte for byte identical to original imported data • Incoming load rates for up to three simultaneous parallel loads
  72. 72. © 2013 IBM Corporation Description of “by Value” Replication Method Alternative method of replicating changes – Used when DML or DDL SQL statements are detected to potentially produce different results on the subordinate. – Replays the rows which changed (and DDL to ensure appropriate table structure) Steps – On the master • Detect non deterministic SQL DML operations. • Mark the entire transaction as required to be replicated by the rows that changed and the DDL statements issued against replicated databases. • During commit processing of the transaction on the master, the set of rows which changed (inserted, updated or deleted) for each of the tables affected by DML are captured to the replication log. – On the subordinate • DDL statements against replicated databases are replayed • For each modified table, the new rows are inserted, and old rows deleted. Requirement to log the underlying row changes to tables – Performance impacted by waiting for rows to log to disk on source system. – Performance = length of time required for a transaction to complete will generally be longer than the time when replication is disabled. This method may be optimal for some workloads compared to “by SQL” – Session variable available to force the selection of this method when logging transactions • SET REPLICATE_ALWAYS_BY_VALUE=ON; nzreplshowsql command will output more details
  73. 73. © 2013 IBM Corporation IBM Netezza Replication Services - Roles Subordinate: Role in a replication set in which execution of UPDATE transactions against non- temporary tables or sequences in a replicated database are prohibited. Temporary table UPDATEs and persistent table SELECTs are fully supported. Master: Appliance that is the single source of changes to replicated databases and to global data. The other appliances in the replication set are subordinates. The role of master can be changed from one appliance to another by an administrator, typically in response to failures and planned outages, or to “follow the sun” across time zones. One master and many subordinates are permitted in a replication set. A subordinate replication host can perform query transactions for load balancing, including creating and updating temporary tables. Subordinate appliances can have databases outside of replication scope and they have no write restrictions.
  74. 74. © 2013 IBM Corporation The Persistent Transport System (PTS) External server collocated with every node in replication cluster A PTS has three major purposes: – Move data and files (synchronize transaction logs) from one node to another. – Send control messages from one node to another. – Act as a persistent store for recovery from failures. PTS H/W Specs: – 4 cores, 16GB RAM, 5TB+ of disk space, 250MB/s disk write rate for logs – Redhat Linux 5.7+ Can Be a Virtual Machine (VM) The New *flexible* PTS! (Valid option as of February 2014.) Note: we encourage customers to have a test environment, so please consider the need for not only appliances but appropriate PTS in your test environment.
  75. 75. © 2013 IBM Corporation Performance Benefits of a Replicated Environment Across the replicated cluster, the advantages of asynchronous replication: Because applications do not have to wait for transactions on the master to be transported and applied on target systems, asynchronous solutions can be deployed over long distances with (a) negligible impact on application performance, and (b) minimal network bandwidth consumption. On the master system, improve performance by offloading BI reporting to one or more replication target systems. On target systems, reduce network and database connection latencies by storing data closer to users and client applications. Across the replicated cluster, optimal use of network bandwidth,a direct consequence of the "by-SQL" approach to replicating load file and SQL statement when possible. This contrasts with other databases which log and transmit index and data structure changes.
  76. 76. © 2013 IBM Corporation Replication PTS HA: The ability to add a second host into the PTS HW to ensure if there is an issue with the host. (Note: this requires appropriate hardware and the RedHat Availability Add-On.) Replication Relaxed Serializability: Replication is compatible with the NPS feature relaxed serializability. Replication Master Continue on PTS Error: The ability to allow the source appliance to continue to change data even though a replication error occurred and it can not log to its PTS. Reduced Restrictions: The removal of restrictions in the SQL allowed on replicated databases. (Sequences, Non deterministic SQL, DML which selects from non-replicated data, Stored procedures which manipulate timestamps, TEMP tables now work identically when replication is enabled vs. disabled) Increased Resiliency, and Compatibility with Customer Workloads IBM Netezza Replication Services v1.5
  77. 77. © 2013 IBM Corporation NPS v7.1 is a Prereq for Replication v1.5 80 Highlights Scheduler rules for WLM Short query prioritization Snippet Result Cache Faster Bulk Fetching with ODBC Password aging and expiry nzPortal enhancements Cryptographic Standards (s800-131a) Support for Replication v1.5 Support for INZA 3.0 Resiliency Faster rebalance for failed disks Disk validation support Large scale disk replacement Call Home v1.0 Enhanced System Health Checks v2.2 ILMT support for Growth on Demand Platform & OS Client Kit support for AIX 7.1 RHEL 6.4 certification SQL Enhancements Multiple Schema (3-part naming) Orphan column query NOT IN / EXIST improvements CASE WHEN improvements Support 24 hour datetime CESU-8 support Transaction Enhancement Truncate table in TXN Improved view validation Temp table enhancements Deprecate Web Admin ETL ODBC loader support for INTERVAL Netezza Performance Portal Cryptographics standards (s800-131a) Scheduler rules History type AUDIT Restrict nzPortal users Groom dialogs
  78. 78. © 2013 IBM Corporation New Features in NPS 7.1 / Replication 1.5 WHAT IS IT – A system parameter (replContinueOnLogError) in the replc.cfg file. HOW IT WORKS – False (default): If a PTS error occurs while capturing the transaction log, the master aborts any active transaction. – True: Enables the master to continue processing transactions, regardless of the logging error, but replication stops so that loads can continue. The master node enters a "continue on error" state, where write workloads continue even though they are not recorded in the replication log. Because the transaction log is then invalid due to missing data, you must re-synchronize all nodes after resolving the PTS issues. HOW TO RECOVER – To recover from the replication suspension that results from the "master continue on error" feature, you must follow the backup and restore procedure. First, run the nzreplanalyze command to generate a directive file for synchronization and progress the master node from "continue on error" to a suspended state. Then, use nzreplbackup to create backup and activate master node. Finally, use nzreplrestore to restore the replication data to the subordinate(s). *No other database has this configuration setting! Master Continue on Error
  79. 79. © 2013 IBM Corporation New Features in NPS 7.1 / Replication 1.5 As of NPS 7.1 and Replication version 1.5, customers can utilize the "relaxed serializability" setting in NPS on replication databases! – This functionality utilizes an invisibility list. The invisibility list on the master is replicated for use on the subordinate. – There are no constraints around using this setting on the master or subordinate in replication environments. – To be clear, the serial execution on the subordinate did not change from the prior replication release but now it has the invisibility list to "see" the appropriate state of the database. – Its worth noting that the appliances behave the same way with relaxed serializability regardless of replication being turned on or off. NPS Configuration Notes (A best practice is to use it at a session level.) – It can be set system wide (globally). This requires a stop and start of the appliance. – It can be set with a session variable. Relaxed Serializability Support NOTE: customers need to know what is occurring to turn serializability to false. Therefore, it is a best practice to utilize it in session scope (as opposed to globally). NPS Feature will be documented as of NPS 7.1 for the first time
  80. 80. © 2013 IBM Corporation Replication Reduced Restrictions Reduced restrictions – Key software development project since January 2013 Things that now work fine with replication – SEQUENCES – Non deterministic SQL (ie. LIMIT 5, Random(), Window functions) – DML which selects from non-replicated data (system tables, databases) – Stored procedures which manipulate timestamps – Session scope temporary tables and variables - TEMP tables now work identically when replication is enabled vs disabled – Transactions larger than 300KB of SQL statements now supported – UDF, UDTF and UDA
  81. 81. © 2013 IBM Corporation Features This QuickStart includes the following activities: Install the 10 Gb NIC cards in the Netezza appliances, establish and validate connectivity with replication hardware and Netezza appliance. Install and configure a basic Netezza Replication Software Solution from one Netezza source to one target. Provide information sharing on how to best use and leverage the Netezza Replication Solution. Conduct a planning workshop to document disaster and recovery scenarios based on the requirements. The scope is limited to one Netezza source and one target. Additional nodes can be supported and quoted separately. The site survey / pre-engagement checklist is reviewed and completed by the client before any IBM resources come on-site. Deliverables Installation Report Disaster and Recovery Scenarios Document Ensure your solution is implemented efficiently with low risk Benefits Get a basic replication solution installed and configured quickly realizing your solution ROI faster Leverage IBM deep product expertise to define optimum disaster recovery solutions to satisfy your requirements Obtain a replication solution foundation to protect one of your most important assets, your data! Backed by world-class industry and product experts in deploying Information Management Software Duration 4 weeks PureData System for Analytics Replication QuickStart Offering
  82. 82. © 2013 IBM Corporation Announcement http://www-01.ibm.com/common/ssi/cgi- bin/ssialias?infotype=AN&subtype=CA&htmlfid=897/ENUS214-055&appname=USN Fix Central http://www- 933.ibm.com/support/fixcentral/swg/selectFixes?product=ibm/Information+Management/Netez za+NPS+Software+and+Clients&release=NPS_7.1.0&platform=All&function=all Knowledge Center http://www-01.ibm.com/support/knowledgecenter/ Replication Services https://w3-connections.ibm.com/communities/community/NetezzaReplication Netezza Developer Network download site: https://www14.software.ibm.com/webapp/iwm/web/reg/pick.do?source=swg-im- ibmndn&lang=en_US Contacts Doug Dailey, Netezza Product Manager (NPS), douglasd@us.ibm.com Chris Gerlt, Netezza Product Manager (Replication), chris.gerlt@us.ibm.com Questions about NPS 7.1 & Replication 1.5
  83. 83. © 2013 IBM Corporation © International Business Machines Corporation 2014 International Business Machines Corporation New Orchard Road Armonk, NY 10504 IBM, the IBM logo, PureSystems, PureFlex, PureApplication, PureData and ibm.com are trademarks of International Business Machines Corporation, registered in many jurisdictions worldwide. A current list of IBM trademarks is available on the Web at www.ibm.com/legal/copytrade.shtml All rights reserved.

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