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An Introduction to Apache Hadoop Yarn, what is it and why is it important ? What does it improve in Apache Hadoop ?
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Apache Hadoop Yarn • What is Yarn • Problems with Hadoop • What does Yarn Do ? • Old Architecture • New Architecture • Yarn Example • Additions
Hadoop Yarn – What is it ? • Next Generation MapReduce MRv2 • Split Job Tracker into • Resource Manager • Scheduling / Monitoring • Improves scaling • Improves resource management • Already used by Yahoo
Problems with Hadoop 1.0 • Problems with large scaling • > 4000 nodes • > 40k concurrent tasks • Problems with resource utilization • Slots only for Map or Reduce • Single NameNode, single point of failure • Clients and Cluster must be at same version
What does Yarn do ? • Provides a cluster level resource manager • Adds application level resource management • Provides slots for jobs other than Map / Reduce • Improves resource utilization
Old Architecture • Cluster level Job Tracker, Task Tracker on data node
New Architecture • Resource Manager • Cluster level resource manager • Long life • Node Manager • One per data server • Monitors resources on node • Application Master • One per application • Short life • Manages task / scheduling
Yarn Example • 1) Client -> Resource Manager • Submit App Master • 2) Resource Manager -> Node Manager • Start App Master • 3) Application Master -> Resource Manager • Request and release containers • 4) Resource Manager -> Node Manager • Start tasks in containers
Additions • Consider Weave • Simplifies the use of Yarn • Reduced development effort • Simplified API
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