Download - HPE Keynote Hadoop Summit San Jose 2016
Enterprise-grade Big DataChris EidlerVP, Solutions R&D, HPE
Inflection Point - Data Management goes Open Source
Infrastructure Layer
Data Layer
Analytics Layer
Apps Layer (Solutions)
Disruption ImpactWorkload Optimization
Building Blocks for Workload-Optimized Big Data
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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 4510Densest Storage block• Online Archival• Object storage
A Big Data Journey…
ETL Offload Archival
Deep Learning
Event Processing
In Memory Analytics
HP Big Data Reference ArchitectureElastic Platform for Analytics
Event ProcessingLow Latency Compute
Moonshot m710x
In Memory AnalyticsBig Memory Compute
Apollo xl170r w 512G memory
Archival StorageApollo 4200 w 6TB HDD
ETL Offload High Latency Compute
Apollo xl170 w 256G memory
Deep LearningHPC Compute
Apollo xl190r w GPUs
HDFS StorageData Lake
Apollow 4200 w 3TB HDD
What If….Opportunities for Platform Optimization
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
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HPE’s “The Machine”A shared something architecture
Platform Investigations for Workload Optimized Big Data
Confidential
Silicon Acceleration
Big Data/HPC/Cloud integration
HPC Big Data Cloud
Composed Big Data
Multicore x86 CPU
GPGPU FPGA SoC/ASIC
Software Hardware
Meaning Aware Storage
Push work into storage
HPE’s Own HDP Deployment – Modernizing Data ArchitectureMillions 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
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!
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
Thank you
Catch HPE Session at 11:30am Wed, Room 210C
Visit the HPE booth, complete a quiz & win a prize
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