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Hadoop In the Enterprise?


      Sih Lee & Peter Krey, Innovation & Shared Services
             Firmwide Engineering & Architecture


             Hadoop World, New York City, October 2nd, 2009




                                                                           2009 JPMorgan Chase & Co.
                                                                               All rights reserved.
                                                              Confidential and proprietary to JPMorgan Chase & Co.
Agenda

                                                                      Page



                                      JPMorgan Chase + Open Source      2


                                      Hadoop In The Enterprise?         3


                                      Active POC Pipeline               6


                                      Hadoop Positioning                7


                                      Cost Comparisons                  8


                                      Hadoop Additions & Must Haves    10
Hadoop In The Enterprise ?




                                      Q&A                              11




                                                                             1
JPMorgan Chase + Open Source




                                  Established Multi-Year Open Source History

                                  Big Supporter of Industry Standards & Open Source Projects

                                  Numerous Production Open Source Implementations
                                   QPID (AMQP) - Top Level Apache Project (http://qpid.apache.org/)
                                   Tyger - Apache + Tomcat + Spring - Fully Integrated App
                                   Server Environment 30+ OS Components
                                   Compute Backbone (CBB) HPC Grid - 1000's of Linux Based Compute
Hadoop In The Enterprise ?




                                   Servers
                                   MuleSoft.org (a.k.a. MuleSource) Enterprise Message Bus
                                   others …




                                                                                                      2
Hadoop In The Enterprise – Economics Driven



                                  Many Big Data Lessons Learned From Web 2.0 Community

                                  Potential For Large Capex and Opex "Dislocation"
                                    Reduced Consumption of Enterprise Premium Resources
                                    Grid Computing Economics Brought To Data Intensive Computing
                                    Stagnant Data Innovation

                                  Enabling & Potentially Disruptive Platform
                                    Many Historical Similarities
                                      Java, Linux, Tomcat, Web / Internet, …
Hadoop In The Enterprise ?




                                      Mini's to Client / Server, Client / Server to Web, Solaris to Linux, …
                                    Key Question: What Can Be Built On Top of and Enabled by Hadoop?




                                                                                                               3
Hadoop In The Enterprise – Choice Driven




                                  Overuse of Relational Database Containers
                                    Institutional “Muscle Memory” … Not Much Else to Choose From
                                    Increasing Large Percentage of Static Data Stored In Proprietary
                                    Transactional DB's
                                    Over-Normalized Schemas … Still Makes Sense With Cheap
                                    Compute & Storage?


                                  Enterprise Storage "Prisoners"
Hadoop In The Enterprise ?




                                    Captive To The Economics & Technology of "A Few" Vendors
                                    Developers Need More Choice
                                    Too Much Proprietary, Single-Source Data Infrastructure
                                    Increasing Need For Minimal / No System + Storage Admins




                                                                                                       4
Hadoop In The Enterprise – Other Drivers




                                  Growing Developer Interest In "No SQL" Data Technologies
                                    Open Source, Distributed, Non-relational Databases
                                    Growing Influence Of Web 2.0 Technologies & Thinking On Enterprise
                                    Hadoop, Cassandra, HBase, Hive, CouchDB, HadoopDB, …, others
                                    memcached For Caching

                                  FSI Industry Drivers
                                    Increased Regulatory Oversight + Reporting =
Hadoop In The Enterprise ?




                                    More Data Needed Over Longer Period Of Time
                                    Growing Need For Less Expensive Data Repository / Store
                                    Increasing Need To Support "One Off" Analysis On Large Data




                                                                                                         5
Active POC Pipeline




                                 Growing Stream of Real Projects To Gauge Hadoop "Goodness of Fit"
                                 Broad Spectrum of Use Cases
                                 Driven By Need To Impact / Dislocate OPEX + CAPEX
                                 Evaluated On Metric Based Performance, Functional, And
                                 Economic Measures
Hadoop In The Enterprise ?




                                                                                                     6
Hadoop Positioning
                                                                                                                Semi-Structured
                                                                                                                   Analysis
                                                                   Higher-Latency

                                                                                                                         • Map/Reduce + HDFS
                                                                                                                • DW7

                                                                                           • DW6
                                                                                              • DW5



                                                                                                      • DW3
                                                              • SQLDB1                                • DW4
                                GB’s                                                                                              TB’s –> PB’s
Hadoop In The Enterprise ?




                                                                     • SQLDB2               • DW2

                                                                     • SQLDB3               • DW1
                                           • InMemory1                          • SQLDB4




                                       Index Based Access –                                                   Index Based Access –
                                         Updates / XActns                                                           Analysis
                                                                         Lower-Latency


                                                                                                                                                 7
Comparative Storage Cost Bar Graph Slide


                                  “Normalized" SAN + NAS $ per gb per month versus HDFS $ per gb per month
Hadoop In The Enterprise ?




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                                                                                                             8
Enterprise Data Warehousing Costs


                                  "normalized” bar chart utilizing retail $ per TB

                                                              Data Warehouse S/W -- $K per TB

                                    $250



                                    $200



                                    $150
Hadoop In The Enterprise ?




                                    $100



                                     $50



                                      $0
                                                                                 Products

                                                                                                9
Hadoop Additions & Must Haves




                                  Improved SQL Front-end Tool Interoperability
                                   Better Interop With Skills & Content That Firms Already Have
                                  Improved Security & ACL enforcement … Kerberos integration?
                                  Grow Developer Programming Model Skill Sets
                                  Improve Relational Container Integration & Interop For Data Archival
                                  Management & Monitoring Tools
                                  Improved Developer & Debugging Tools
Hadoop In The Enterprise ?




                                  Reduce Latency Via Integration With Open Source Data Caching
                                   memcached, others
                                  Invitation To FSI or Enterprise Roundtable




                                                                                                         10
Q&A




                                   Sih Lee, Head of Innovation & Shared Services
                                   Firmwide Engineering & Architecture
                                   W# 212-622-3038
                                   sih.x.lee@jpmchase.com


                                   Peter Krey, Consultant, Innovation & Shared Services
                                   Firmwide Engineering & Architecture
                                   W# 212-622-2926
                                   peter.j.krey@jpmchase.com
Hadoop In The Enterprise ?




                                                                                          11

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Hw09 Data Processing In The Enterprise

  • 1. Hadoop In the Enterprise? Sih Lee & Peter Krey, Innovation & Shared Services Firmwide Engineering & Architecture Hadoop World, New York City, October 2nd, 2009  2009 JPMorgan Chase & Co. All rights reserved. Confidential and proprietary to JPMorgan Chase & Co.
  • 2. Agenda Page JPMorgan Chase + Open Source 2 Hadoop In The Enterprise? 3 Active POC Pipeline 6 Hadoop Positioning 7 Cost Comparisons 8 Hadoop Additions & Must Haves 10 Hadoop In The Enterprise ? Q&A 11 1
  • 3. JPMorgan Chase + Open Source Established Multi-Year Open Source History Big Supporter of Industry Standards & Open Source Projects Numerous Production Open Source Implementations QPID (AMQP) - Top Level Apache Project (http://qpid.apache.org/) Tyger - Apache + Tomcat + Spring - Fully Integrated App Server Environment 30+ OS Components Compute Backbone (CBB) HPC Grid - 1000's of Linux Based Compute Hadoop In The Enterprise ? Servers MuleSoft.org (a.k.a. MuleSource) Enterprise Message Bus others … 2
  • 4. Hadoop In The Enterprise – Economics Driven Many Big Data Lessons Learned From Web 2.0 Community Potential For Large Capex and Opex "Dislocation" Reduced Consumption of Enterprise Premium Resources Grid Computing Economics Brought To Data Intensive Computing Stagnant Data Innovation Enabling & Potentially Disruptive Platform Many Historical Similarities Java, Linux, Tomcat, Web / Internet, … Hadoop In The Enterprise ? Mini's to Client / Server, Client / Server to Web, Solaris to Linux, … Key Question: What Can Be Built On Top of and Enabled by Hadoop? 3
  • 5. Hadoop In The Enterprise – Choice Driven Overuse of Relational Database Containers Institutional “Muscle Memory” … Not Much Else to Choose From Increasing Large Percentage of Static Data Stored In Proprietary Transactional DB's Over-Normalized Schemas … Still Makes Sense With Cheap Compute & Storage? Enterprise Storage "Prisoners" Hadoop In The Enterprise ? Captive To The Economics & Technology of "A Few" Vendors Developers Need More Choice Too Much Proprietary, Single-Source Data Infrastructure Increasing Need For Minimal / No System + Storage Admins 4
  • 6. Hadoop In The Enterprise – Other Drivers Growing Developer Interest In "No SQL" Data Technologies Open Source, Distributed, Non-relational Databases Growing Influence Of Web 2.0 Technologies & Thinking On Enterprise Hadoop, Cassandra, HBase, Hive, CouchDB, HadoopDB, …, others memcached For Caching FSI Industry Drivers Increased Regulatory Oversight + Reporting = Hadoop In The Enterprise ? More Data Needed Over Longer Period Of Time Growing Need For Less Expensive Data Repository / Store Increasing Need To Support "One Off" Analysis On Large Data 5
  • 7. Active POC Pipeline Growing Stream of Real Projects To Gauge Hadoop "Goodness of Fit" Broad Spectrum of Use Cases Driven By Need To Impact / Dislocate OPEX + CAPEX Evaluated On Metric Based Performance, Functional, And Economic Measures Hadoop In The Enterprise ? 6
  • 8. Hadoop Positioning Semi-Structured Analysis Higher-Latency • Map/Reduce + HDFS • DW7 • DW6 • DW5 • DW3 • SQLDB1 • DW4 GB’s TB’s –> PB’s Hadoop In The Enterprise ? • SQLDB2 • DW2 • SQLDB3 • DW1 • InMemory1 • SQLDB4 Index Based Access – Index Based Access – Updates / XActns Analysis Lower-Latency 7
  • 9. Comparative Storage Cost Bar Graph Slide “Normalized" SAN + NAS $ per gb per month versus HDFS $ per gb per month Hadoop In The Enterprise ? p p p p N N N N N N AS AS AS AS oo oo oo oo SA SA SA SA SA SA N N N N ad ad ad ad H H H H 8
  • 10. Enterprise Data Warehousing Costs "normalized” bar chart utilizing retail $ per TB Data Warehouse S/W -- $K per TB $250 $200 $150 Hadoop In The Enterprise ? $100 $50 $0 Products 9
  • 11. Hadoop Additions & Must Haves Improved SQL Front-end Tool Interoperability Better Interop With Skills & Content That Firms Already Have Improved Security & ACL enforcement … Kerberos integration? Grow Developer Programming Model Skill Sets Improve Relational Container Integration & Interop For Data Archival Management & Monitoring Tools Improved Developer & Debugging Tools Hadoop In The Enterprise ? Reduce Latency Via Integration With Open Source Data Caching memcached, others Invitation To FSI or Enterprise Roundtable 10
  • 12. Q&A Sih Lee, Head of Innovation & Shared Services Firmwide Engineering & Architecture W# 212-622-3038 sih.x.lee@jpmchase.com Peter Krey, Consultant, Innovation & Shared Services Firmwide Engineering & Architecture W# 212-622-2926 peter.j.krey@jpmchase.com Hadoop In The Enterprise ? 11