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HPE Keynote Hadoop Summit San Jose 2016

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HPE Keynote Hadoop Summit San Jose 2016

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HPE Keynote Hadoop Summit San Jose 2016

  1. 1. Enterprise-grade Big Data Chris Eidler VP, Solutions R&D, HPE
  2. 2. Inflection Point - Data Management goes Open Source Infrastructure Layer Data Layer Analytics Layer Apps Layer (Solutions) Disruption Impact Workload Optimization
  3. 3. Building Blocks for Workload-Optimized Big Data HPE Confidential - for HPE and Channel Partners only 3 Active Archive • Multi-temperate storage with data governance and federated queries • Denser TB/rack u, lower $/TB for long term storage Data Lakes • Ingestion of multiple types / sources of data • Batch, Interactive, Real-time workloads • Different infrastructure requirements Data Warehouse Modernization • Data Staging & landing zone • Bach processing • Traditional and rack density optimized form factors Use Cases: ProLiant DL300 series Apollo 4530 Apollo 4200 Traditional 1U/2U design • Building block for traditional Hadoop workloads Density optimized platform block for traditional Hadoop workloads • Same spindle/core ratios Storage optimized block • Foundation for Data lakes • Double the storage density of traditional platform Apollo 4510 Densest Storage block • Online Archival • Object storage
  4. 4. A Big Data Journey… ETL Offload Archival Deep Learning Event Processing In Memory Analytics
  5. 5. HP Big Data Reference Architecture Elastic Platform for Analytics Event Processing Low Latency Compute Moonshot m710x In Memory Analytics Big Memory Compute Apollo xl170r w 512G memory Archival Storage Apollo 4200 w 6TB HDD ETL Offload High Latency Compute Apollo xl170 w 256G memory Deep Learning HPC Compute Apollo xl190r w GPUs HDFS Storage Data Lake Apollow 4200 w 3TB HDD
  6. 6. What If…. Opportunities for Platform Optimization
  7. 7. The Coming Landscape – Non-Volatile Memory – More than fast – byte addressable and persistent – Photonics – Optical Networking will make most NVM equidistant – Some Implications on Big Data – 90% of a database write transaction is eliminated – A Shuffle …isn’t – HPE is contributing changes to Spark with HDP – Favored Algorithms might change – Graph and matrix inversion based algorithms Confidential HPE’s “The Machine” A shared something architecture
  8. 8. Platform Investigations for Workload Optimized Big Data Confidential Silicon Acceleration Big Data/HPC/Cloud integration Composed Big Data Multicore x86 CPU GPGPU FPGA SoC/ASIC Software Hardware Meaning Aware Storage Push work into storage
  9. 9. HPE’s Own HDP Deployment – Modernizing Data Architecture Millions in Savings and Significantly Improving Analytics Data Lake Core EA Dashboards & Reporting - Dedicated satellite - Marketplace interface - Certified reports/data - Enterprise consumption platforms Satellite Analytics Clusters - Super user + enterprise data - Provisioned via project interlock - Services analytics tools - Domain (BU) zones and refineries (ad-hoc jobs) - Synchronized via Hadoop replication Data Lake Core - Hadoop nucleus - Enterprise refinery - Certified enterprise data - No direct consumption for general users - Full dataset discovery via limited YARN containers Foundation for HPE’s Go- Forward Data Strategy • Democratizing Analytics • Open up analytics innovation through self service consumption and governance • Single E2E connected Data Platform • Serve up enterprise data w/ unprecedented speed, accuracy, simplicity and flexibility
  10. 10. HPE and Hortonworks Team Up • Alliance partner for 2+ years • HPE invested $50M in Hortonworks • HPE CTO/EVP Martin Fink is on the Board of Hortonworks • Close collaboration from Engineering to GTM • Technical Collaboration • YARN Node Labels (jira YARN-796) • Spark Optimized Shuffle for big memory • LLAP performance validation – Together we’re driving Hadoop Forward • More Open • More Secure • Optimized for Performance Many of the world’s largest enterprises put their trust in the HPE-Hortonworks team!
  11. 11. Learn More Here at Hadoop Summit! A New “Sparketecture” for Modernizing your Data Warehouse Wednesday, 11:30AM, Room 210C Demos @ Booth 501 Play the Hadoop Trivia Game and Win! – HPE Booth
  12. 12. Thank you Catch HPE Session at 11:30am Wed, Room 210C Visit the HPE booth, complete a quiz & win a prize 12

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