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Level Up – How to Achieve Hadoop Acceleration
- 1. Grab some coffee and enjoy the pre-show banter before the top of the hour!
- 2. Level Up – How to Achieve Hadoop Acceleration The Briefing Room
- 3. Twitter Tag: #briefr The Briefing Room Welcome Host: Eric Kavanagh [email protected] @eric_kavanagh
- 4. ! Reveal the essential characteristics of enterprise software, good and bad ! Provide a forum for detailed analysis of today’s innovative technologies ! Give vendors a chance to explain their product to savvy analysts ! Allow audience members to pose serious questions... and get answers! Twitter Tag: #briefr The Briefing Room Mission
- 5. This Month: BIG DATA ECOSYSTEM September: INTEGRATION & DATA FLOW October: ANALYTIC PLATFORMS Twitter Tag: #briefr The Briefing Room Topics 2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room
- 6. LOOK BEFORE YOU LEAP INTO HADOOP! Twitter Tag: #briefr The Briefing Room Executive Summary u Yes, you still need to PLAN u File formats and partitioning MATTER u Pay attention to TCO u Be willing to fail fast, OFTEN
- 7. Twitter Tag: #briefr The Briefing Room Analyst: Robin Bloor Robin Bloor is Chief Analyst at The Bloor Group [email protected] @robinbloor
- 8. Twitter Tag: #briefr The Briefing Room HP Vertica ! HP Vertica offers a range of enterprise software and database management solutions ! The column-oriented Vertica Analytics Platform leverages a standard SQL interface that now integrates with Hadoop ! HP’s big data initiative includes HAVEn (Hadoop, Autonomy IDOL, Vertica, Enterprise Security and n Apps), a platform designed to analyze and manage petabytes of data
- 9. Twitter Tag: #briefr The Briefing Room Guest: Walter Maguire Walter Maguire has twenty-seven years of experience in analytics and data technologies. He practiced data science before it had a name, worked with big data when "big" meant a megabyte, and supported the movement which brought data management and analytic technologies from back-office to the front. In October of 2010, Walt became the first hire west of Denver for Vertica, makers of the Vertica Analytics software platform for real-time analytics of structured and unstructured data. Since then, he has helped build the HP Vertica customer base and team in the western USA. Now as Chief Field Technologist with HP Vertica, Walt addresses customer needs with the continuing evolution of Vertica and HAVEn, the HP Big Data strategy that links hardware, software, services, and business transformation consulting for successful execution.
- 10. Big Data & SQL: Hadoop Convergence With the HP Vertica Analytics Platform Walt Maguire, Chief Field Technologist, HP Vertica Chris Selland, VP Business Development, HP Vertica © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
- 11. Essential Requirements of an Analytics Platform © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 11 without notice.
- 12. Introducing HP Vertica Dragline Faster answers from Big Data at a fraction of the cost of traditional data warehouses Store all your data in any format cost-effectively across Vertica + Hadoop Explore all your data directly in Hadoop without moving or changing it Serve all of your data consumers without compromise from individualized queries to large complex reports HP Vertica © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 12 without notice.
- 13. Cost-Optimized Storage - ILM Tier-off older data Hot Cool Cold Dark Data © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 13 without notice. Value Discovery Interactive Data Frequently queried Vertica data cache Batch Data Archive Data Serve Convert data to Vertica storage format Explore Any format Store Location Format Any format
- 14. The Richest, Most Open SQL on Hadoop Challenge: Extracting data from Hadoop requires complex and brittle ETL processes Solution: Hadoop Navigation and Analytics Benefits: • Navigate Hadoop data using its native catalog • Quickly and easily load native data types from Hadoop to Vertica • Avoid creating and maintaining time-consuming schemas • Use the full power of HP Vertica SQL and analytics • Choose your own Hadoop distribution © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 14 without notice.
- 15. The Richest, Most Open SQL on Hadoop Challenge: Extracting Data from Hadoop requires complex and brittle ETL processes Solution: Hadoop Navigation and Analytics Benefits: • Navigate Hadoop data using its native catalog • Quickly and easily load native data types from Hadoop to Vertica • Avoid creating and maintaining time-consuming schemas • Use the full power of HP Vertica SQL and Analytics • Choose your own Hadoop distribution © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 15 without notice.
- 16. HP Vertica Flex Zone Avoid creating and maintaining time-consuming schemas Faster SQL querying Auto-schematization Flexible parsers © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 16 on semi-structured data semi-structured data loading for JSON and delimited data One-step schema for blazing-fast performance Load, manage, and explore semi-structured data
- 17. Exploring Data with FlexZone Create Flex Table (with or without any columns) Load Flex Tables (using parsers data format independent) Explore Data Using map functions © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Materialize Flex Table (Compute keys / Build Views Materialize flextable columns) Manage Flex Table (Alter, Config, etc)
- 18. Monitor Customer Experience by Joining Machine Logs to Tweets Create Flex Table with Machine Log Data Explore Data with Map Functions Create Flex Table with Twitter Data Sentiment Score Tweets with Pulse © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Join Machine Log Data to Tweets with Time Series Event Join Associate customer sentiment with application response times
- 19. Ecosystem HP Vertica © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
- 20. Hadoop Partnership Momentum and Milestones • Integrated SQL-on-Hadoop solution with MapR live as of May 2014 • Reseller relationship with Hortonworks announced July 2014 • Significant joint customer base with Cloudera © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
- 21. HP Vertica Marketplace © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
- 22. Thank you! Walt Maguire Chief Field Technologist, HP Vertica [email protected] Chris Selland VP Business Development, HP Vertica [email protected] © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
- 23. Twitter Tag: #briefr The Briefing Room Perceptions & Questions Analyst: Robin Bloor
- 24. THE NEXT PHASE OF HADOOP’S EVOLUTION? Robin Bloor, PhD
- 25. Hadoop Evolution Serial batch workloads MapReduce Versatile data storage Key-value access only Island of processing FROM TO Multiple concurrent workloads Multiple algorithms “Optimized” data storage SQL, JSON & even SPARQL access Integrated processing
- 26. The Data Warehouse: From/To
- 27. Data & Data Lifecycle Management
- 28. The Major Workload Will Be Analytics The consequences are that: 1. DATA ACCESS will need to be more versatile 2. WORKLOAD MANAGEMENT will need to be more versatile 3. Hadoop will need to “shake hands” with ONE OR MORE database engines
- 29. u In general what is the DBA overhead for the combination of Hadoop, Flex Zone and Vertica? u How does data lifecycle management work in practice? u Analytics can be done on Hadoop, in Flex Zone and in Vertica. How are these choices normally handled in a Flex Zone/Vertica environment? u What analytics components can be used with Flex Zone and Vertica?
- 30. u What do you see as the sweet spot for this architecture (by sector & company size)? Where might it be overkill? u In respect to scale, what is your largest implementation of Hadoop/Flex Zone/Vertica by data volume? u Who do you see as closest in direct competition?
- 31. Twitter Tag: #briefr The Briefing Room
- 32. This Month: BIG DATA ECOSYSTEM September: INTEGRATION & DATA FLOW October: ANALYTIC PLATFORMS www.insideanalysis.com/webcasts/the-briefing-room Twitter Tag: #briefr The Briefing Room Upcoming Topics 2014 Editorial Calendar at www.insideanalysis.com
- 33. Twitter Tag: #briefr THANK YOU for your ATTENTION! Opening slide image courtesy of Wikimedia Commons The Briefing Room