1. © Hortonworks Inc. 2014
Apache Hadoop YARN
Present and Future
Vinod Kumar Vavilapalli
vinodkv [at] apache.org
@tshooter
Jian He
jianhe [at] apache.org
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2. © Hortonworks Inc. 2014
Who are we?
• Vinod Kumar Vavilapalli
– 7 Hadoop-years old
– Previously @Yahoo!, now @Hortonworks
– Hadoop MapReduce and YARN Development lead & Architect at Hortonworks
– Apache Hadoop YARN project lead
– Apache Hadoop PMC, Apache Member
– 99% + code in Apache, Hadoop
• Jian He
– Software Engineer @ Hortonworks
– Apache Hadoop Committer
– Masters Degree from Brown University.
– Focus on YARN/MapReduce
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Architecting the Future of Big Data

3. © Hortonworks Inc. 2014
A quick show of hands..
• Hadoop 1
• Hadoop 2 & YARN
• YARN for MapReduce2
• YARN for beyond MR2
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Architecting the Future of Big Data

4. © Hortonworks Inc. 2014
Agenda
• Apache Hadoop 2 : Overview
• Community
• Present
• Future
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Architecting the Future of Big Data

5. © Hortonworks Inc. 2014
Apache Hadoop 2
Next Generation Architecture
Architecting the Future of Big Data
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6. © Hortonworks Inc. 2014
YARN: the Data Operating System
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Architecting the Future of Big Data
• Resource Management Platform
• MapReduce v2
• Beyond MapReduce with Tez, Storm, Spark; in Hadoop!
• Did I mention Services like HBase, Accumulo on YARN with Apache Slider?

7. © Hortonworks Inc. 2014
Why?
• 2.0 >= 2 * 1.0
– YARN: Next generation architecture
• Scale
• Agility
• Return on Investment: 2x throughput on same hardware!
• Ready for improvements in hardware
• Not convinced? Let’s see what others are saying!
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Architecting the Future of Big Data

8. © Hortonworks Inc. 2014
Yahoo!
• Leader/Visionary on all things Hadoop!
• On YARN (0.23.x)
• Moving fast to 2.x
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Architecting the Future of Big Data
http://developer.yahoo.com/blogs/ydn/hadoop-yahoo-more-ever-54421.html

9. © Hortonworks Inc. 2014
Twitter
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Architecting the Future of Big Data
Talk: “ Hadoop 2 @Twitter, Elephant Scale”
By: Lohit Vijayarenu & Gera Shegalov

10. © Hortonworks Inc. 2014
Ebay
• Has one of the largest Hadoop clusters in the industry with tens-
hundreds petabytes of data
• Migrated production clusters to Hadoop-2
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Architecting the Future of Big Data

11. © Hortonworks Inc. 2014
YARN Community
At Apache Software Foundation
Architecting the Future of Big Data
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12. © Hortonworks Inc. 2014
YARN contributions
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Architecting the Future of Big Data
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2.0.x 2.1.x 2.2.x 2.3.x 2.4.x 2.x trunk
YARN Releases - 06/02/14
YARN Releases - 06/02/14

13. © Hortonworks Inc. 2014
Contributors
• 104 and counting
• Few ‘big’ contributors
• And a long tail
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14. © Hortonworks Inc. 2014
Present
Architecting the Future of Big Data
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15. © Hortonworks Inc. 2014
Apache Hadoop releases
• 15 October, 2013
• The 1st GA release of Apache Hadoop 2.x
• YARN
– First stable and supported release of YARN
– YARN level APIs solidified for the future
– Binary Compatibility for MapReduce applications built on hadoop-1.x
– Performance
– Scale!
• Support for running Hadoop on Microsoft Windows
• Substantial amount of integration testing with rest of projects in the
ecosystem
– Pig, Hive, Oozie, HBase..
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Architecting the Future of Big Data
Apache Hadoop 2.2

16. © Hortonworks Inc. 2014
Apache Hadoop releases (contd)
• 24 February, 2014
• First post GA release for the year 2014
• Alpha features in YARN
– ResourceManager High Availability
– Application History Server
– Will be covered in detail in the 2.4 section
• Number of bug-fixes, enhancements
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Architecting the Future of Big Data
Apache Hadoop 2.3

17. © Hortonworks Inc. 2014
Apache Hadoop releases (contd)
• 7 April, 2014
• Most recent release
• Stabilizing features in YARN
– Details follow
– ResourceManager HA
– YARN Timeline Server (beyond history server)
– Preemption in YARN CapacityScheduler
– Container-preserving AM recovery.
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Architecting the Future of Big Data
Apache Hadoop 2.4

18. © Hortonworks Inc. 2014
ResourceManager High Availability
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Architecting the Future of Big Data
• RM – single point of failure
• Goal : Downtime invisible to end-users
– Apps not required to be re-submitted
– NMs to rebind with newly started RM
• Two stories:
– Recovery of state
– Failover

19. © Hortonworks Inc. 2014
ResourceManager High Availability
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Architecting the Future of Big Data
• Active/Standby
o Leader election
(ZooKeeper)
• Standby on transition to
Active loads all the
state from the state
store.
• NM, AM, clients, redirect
to the new RM
o RMProxy lib
Talk: Highly Available Resource Management for YARN
By: Karthik Kambatla, Xuan Gong

20. © Hortonworks Inc. 2014
YARN Timeline Server
• Few MR specific implementations: History and web-UI
• YARN: Not just MR anymore!
• Previous state
– MapReduce specific Job History Server
– YARN level ‘History’ lost beyond ResourceManager Restart
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Architecting the Future of Big Data

21. © Hortonworks Inc. 2014
YARN Timeline Server (contd)
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Entity and Event
collection
RM and Applications periodically send events to
Timeline sever
Pluggable store Depending on site requirements
REST APIs or RPC
Applications and user-interfaces can access
information via REST/ RPC
Visualizations
Users can build tools and visualizations using the
APIs
Apps and System
Applications as well as the system
entities/events

22. © Hortonworks Inc. 2014
YARN Timeline Server (contd)
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Architecting the Future of Big Data
YARN
Timeline
Serv`er
App1
App2
RM
Custom App
monitoring
client
RPC
REST API
Events
Events
AMBARI
Events
Talk: “Analyzing Historical Data of Applications on Hadoop
YARN: for Fun and Profit”
By: Zhijie Shen, Mayank Bansal

23. © Hortonworks Inc. 2014
Capacity Scheduler Preemption
• Enforce
SLAs
• Preempt
across
queues
• Current Capacity
• Guaranteed Capacity
Gather Queue State
STEP1
• Select applications to preempt: Over
cap. Qs
Identify preemptions
STEP2
• Issue preemptions for containers to
application
Issue preemptions
STEP3
• Track containers that have been issued
by not yet executed preemption
• Forcibly kill these containers after
timeout
Kill containers
STEP4

24. © Hortonworks Inc. 2014
Capacity Scheduler Preemption (Contd)
Application Scheduler
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Architecting the Future of Big Data
Premptions
Release Resource
Premptions
Kill containers forcibly
after timeout
x

25. © Hortonworks Inc. 2014
Container-preserving AM restart
• Problem
– Containers are killed when AM goes down.
– New AM needs to know where the previous containers are running
– Previous containers need to know about the new AM. (WIP)
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Architecting the Future of Big Data
Container1
Container2
Container3
AM1
AM2
restart

26. © Hortonworks Inc. 2014
Apache Hadoop releases (contd)
• Next releases
– 2.4.1
– 2.5.x
• YARN
– Details follow in future’s section
– ResourceManager work-preserving restart for High Availability
– YARN Timeline Server security & enhancement.
– Lots more
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Architecting the Future of Big Data
Apache Hadoop 2.5.x

27. © Hortonworks Inc. 2014
Future
Architecting the Future of Big Data
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28. © Hortonworks Inc. 2014
Future: Operational enhancements
• Rolling upgrades
– No/minimal impact to users
– Ideal: Always rolling!
• HDFS upgrades effort is in
• YARN
– RM restart
– NM restart
– Upgrades
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Architecting the Future of Big Data
Talk: “Hadoop Rolling Upgrades – Taking Availability to the Next Level”
By: Suresh Srinvias, Hortonworks & Jason Lowe Yahoo!

29. © Hortonworks Inc. 2014
Future: Enabling apps
• Beyond MapReduce
– Apache Tez, Apache Slider, Apache Storm.
• Discussing next
– Long running services
– Multi-dimensional resource scheduling
– Isolation
– Web services
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Architecting the Future of Big Data

30. © Hortonworks Inc. 2014
Future: Long running services
• You can run them already!
• Few enhancements needed
– Logs
– Security
– Management/monitoring
• Resource sharing across workload types
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Architecting the Future of Big Data
Talk: “ Bring your Service to YARN”
By: Sumit Mohanty

31. © Hortonworks Inc. 2014
Multi-resource scheduling
• Today – memory & cpu
– Physical memory / virtual memory
– CPU Cores – Virtual cores
• CPU stuff: More bake in
• Disks
– Space
– IOPS
• Network
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Architecting the Future of Big Data

32. © Hortonworks Inc. 2014
Fine-grain isolation for multi-tenancy
• Custom memory-monitoring
• Cgroups
• Linux Containers
• VMs
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Architecting the Future of Big Data

33. © Hortonworks Inc. 2014
Other features
• Application SLAs
– Run my application at 6:00 AM tomorrow and guarantee capacity for me!
• Node labels
– Some of the nodes in my cluster have specialized hardware, give them to me!
• Node affinity/anti-affinity
– Get me on to the nodes where my data is
– Get me off of this node
• Better online queue-management
– Centralized
– Quality feedback
• Web-services
– RESTful APIs for submitting, monitoring and killing apps
– Beyond java-only clients
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Architecting the Future of Big Data

34. © Hortonworks Inc. 2014
YARN Ecosystem
Beyond the core YARN project: Briefly
Architecting the Future of Big Data
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35. © Hortonworks Inc. 2014
Eco-system
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Classic Apache Hadoop
MapReduce – Batch
Batch & Interactive
• Apache Tez –
Batch/Interactive
Stream Processing
• Apache Storm
• Apache Samza
Apache Spark – Iterative
applications
YARN Frameworks
• Apache Twill
• Microsoft REEF
There's an app for that...
YARN App Marketplace!
Existing apps
• Apache Slider
Graph Processing
• Apache Giraph
Applications Powered by YARN
Talk: Apache Tez - A New Chapter in Hadoop Data Processing”
By Bikas Saha, Hitesh Shah

36. © Hortonworks Inc. 2014
Recap
Architecting the Future of Big Data
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37. © Hortonworks Inc. 2014
Recap
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Architecting the Future of Big Data
• YARN helps Apache Hadoop 2 to be twice as good!
• Exciting journey with Hadoop for this decade…
– Hadoop is no longer a one-trick pony, err elephant
– Beyond just MapReduce
• Hadoop 2: Architecture for the future
– Centralized data, multiple apps
• Lots of exciting new features
– Exciting spectrum of application types, workloads and use-cases

38. © Hortonworks Inc. 2014
Couple more things..
Architecting the Future of Big Data
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39. © Hortonworks Inc. 2014
The Book is out!
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Architecting the Future of Big Data

40. © Hortonworks Inc. 2014
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Architecting the Future of Big Data

41. © Hortonworks Inc. 2014
Thank you!
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Download Sandbox: Experience Apache Hadoop
Both 2.x and 1.x Versions Available!
http://hortonworks.com/products/hortonworks-sandbox/
Questions Time!