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Transcript of Hortonworks Eric Baldeschwieler – CEO twitter: @jeric14 (@hortonworks) © Hortonworks Inc. 2011...
Hortonworks
Eric Baldeschwieler – CEOtwitter: @jeric14 (@hortonworks)
© Hortonworks Inc. 2011
Architecting the Future of Big Data
June 29, 2011
© Hortonworks Inc. 2011
About Hortonworks
• Mission: Revolutionize and commoditize the storage and processing of big data via open source
• Vision: Half of the world’s data will be stored in Apache Hadoop within five years
• Strategy: Grow the Apache Hadoop Ecosystem by making Apache Hadoop easier to consume, profit by providing training, support and certification
An independent company Focused on making Apache Hadoop great Hold nothing back, Apache Hadoop will be complete
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© Hortonworks Inc. 2011
Credentials
• Technical: key architects and committers from Yahoo! Hadoop engineering team
−Highest concentration of Apache Hadoop committers−Contributed >70% of the code in Hadoop, Pig and ZooKeeper−Delivered every major/stable Apache Hadoop release since 0.1−History of driving innovation across entire Apache Hadoop stack−Experience managing world’s largest deployment
• Business operations: team of highly successful open source veterans
−Led by Rob Bearden, former COO of SpringSource & JBoss
• Investors: backed by Benchmark Capital and Yahoo!
−Benchmark was key investor in Red Hat, MySQL, SpringSource, Twitter & eBay
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Hortonworks and Yahoo!
• Yahoo! is a development partner−Leverage large Yahoo! development, testing & operations team
More than 1,000 active & sophisticated users of Apache Hadoop Access to the Yahoo! grid for testing large workloads Only organization that has delivered a stable release of Apache Hadoop
−Yahoo will continue to contribute Apache Hadoop code too!
• Yahoo! is a customer−Hortonworks provides level 3 support and training to Yahoo!−Yahoo deploys Apache Hadoop releases across its 42,000 grid
• Yahoo! is an investor
© Hortonworks Inc. 2011 4
Current State of Adoption
Vendor Ecosystem Adoption
Enterprise Adoption
• Early adopters• Technology is hard to install,
manage & use• Technology lacks enterprise
robustness• Requires significant
investment in technical staff or consulting
• Hard to find & hire experienced developer & operations talent
• Early in vendor adoption lifecycle
• Hadoop is hard to integrate and extend
• Hard to find & hire experienced developer & operations talent
Technology & Knowledge Gaps Prevent Apache
Hadoop from Reaching Full Potential
Customers are asking their vendors for help with
Hadoop!
“We’re seeing Hadoop in all of our fortune 2000 data
accounts”
© Hortonworks Inc. 2011 5
Hortonworks Role & Opportunity
Vendor Ecosystem Adoption
Enterprise Adoption
Bridge the Gap!Grow Market
Sell training and support via
Partners
Fundamental shift in enterprise data architecture strategy• Apache Hadoop becomes standard for managing new types & scale of data• New applications & solutions will be created to leverage data in Apache Hadoop• Creates massive big data technology and services opportunity for ecosystem
© Hortonworks Inc. 2011 6
Hortonworks Objectives
• Make Apache Hadoop projects easier to install, manage & use−Regular sustaining releases−Compiled code for each project (e.g. RPMs)−Testing at scale
• Make Apache Hadoop more robust−Performance gains−High availability−Administration & monitoring
• Make Apache Hadoop easier to integrate & extend−Open APIs for extension & experimentation
All done within Apache Hadoop community
• Develop collaboratively with community
• Complete transparency• All code contributed
back to Apache
Anyone should be able to easily deploy the Hadoop projects directly from Apache
© Hortonworks Inc. 2011 7
Technology Roadmap
Phase 1 – Making Apache Hadoop Accessible• Release the most stable version of Hadoop ever• Release directly usable code via Apache (RPMs, .debs…)• Frequent sustaining releases off of the stable branches
2011
Phase 2 – Next Generation Apache Hadoop• Address key product gaps (Hbase support, HA, Management…)• Enable community & partner innovation via modular architecture &
open APIs• Work with community to define integrated stack
2012(Alphas starting Oct 2011)
© Hortonworks Inc. 2011 8
© Hortonworks Inc. 2011
Phase 2 - Next Generation Apache Hadoop
• Core−HDFS Federation−Next Gen MapReduce−New Write Pipeline (HBase support)−HA (no SPOF) and Wire compatibility
• Data - HCatalog 0.3−Pig, Hive, MapReduce and Streaming as clients−HDFS and HBase as storage systems−Performance and storage improvements
• Management & Ease of use−All components fully tested and deployable as a stack−Stack installation and centralized config management−REST and GUI for user tasks
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Phase 2 – Core - MapReduce
• Complete rewrite of the resource management layer
• Performance and Scale improvements
• 6,000+ nodes / 100,000 concurrent tasks
• Supports better availability and fail-over
• Supports new frameworks beyond MapReduce© Hortonworks Inc. 2011 10
Phase 2 – Core – HDFS Federation
• Multiple independent Namenodes and Namespace Volumes in a cluster
− Scalability (6K nodes, 100K clients, 120PB disk), Workload isolation support− Client side mount tables for Global Namespace
• Block storage as a generic shared storage service
− DataNodes store blocks for all Namespace volumes – no partitioning− Non-HDFS namespaces (HBase, MR tmp and others) can share the same storage
Datanode 1 Datanode 2 Datanode m... ... ...
NS1Foreign
NS n... ...
NS k
Balancer
Block Pools
Pool nPool kPool 1
NN-1 NN-k NN-n
Common Storage
Nam
espa
ceBl
ock
stor
age
© Hortonworks Inc. 2011 11
• Limitations of HDFS write pipeline in 0.20−Broken Flush, Sync, Append−Node failures can cause data loss for slow writers
• Hadoop.Next−Flush, Sync, and Append support−New replicas are added dynamically on failures
Phase 2 – Core – HDFS Write Pipeline
DNDN DNClient
Flush Ack
© Hortonworks Inc. 2011 12
Phase 2 – Data – HCatalog
HDFS HBase
HCatalog
MapReduce Pig Hive Streaming
= Phase 1
= Phase 2
• Shared schema and data model• Data can be shared between tool users• Data located by table rather than file• Clients independent of storage details
• format, compression, …• Only one adaptor for new formats
• not one per tool• Notifications when new data is
available
© Hortonworks Inc. 2011 13
Confidential Information
Hortonworks Value
For Enterprises
• Make Apache Hadoop easier to consume
• Extend to broader developer audience
• Foster vibrant technology and services ecosystem
• Access to Hortonworks’ technical expertise
For Vendors
• Create larger market for Apache Hadoop technology and services
• Simplify process for supporting Hadoop
• Access to Hortonworks’ technical expertise
For Community
• Ensure Apache Hadoop remains unified and strong
• Expand value provided by core Apache projects
• Foster additional participation & contributions from ecosystem
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Hortonworks Differentiation
• Unmatched domain expertise−Delivered every major release of Apache Hadoop to date−Critical mass of committers
• Community leadership role −Setting direction for core projects
• Yahoo! commitment and backing−Access to 1,000+ Hadoop engineers, Yahoo! grid
• Absolute dedication to Apache & open source−Focused on making Apache Hadoop the standard
• Focus on delivering significant value to technology vendors−ISVs, OEMs, Systems Integrators and other service providers
Confidential Information 15
Thank You.
© Hortonworks Inc. 2011