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Hadoop Virtualization Extensions
Junping Du
Sr.MTS, VMware, Inc
? 2009 VMware Inc. All rights reserved
Cloud: Big Shifts in Simplification and Optimization
1. Reduce the Complexity
2. Dramatically Lower
Costs
3. Enable Flexible, Agile
IT Service Delivery
to simplify operations
and maintenance
to redirect investment into
value-add opportunities
to meet and anticipate the
needs of the business
2
A Unified Analytics Cloud Significantly Simplifies
. Simplify
? Single Hardware Infrastructure
? Faster/Easier provisioning
SQLCluster
Big SQL NoSQL Hadoop
NoSQL Cluster
Unifed Analytics Infrastructure
Private
Public
Hadoop Cluster
. Optimize
? Shared Resources = higher utilization
? Elastic resources = faster on-demand access
Decision Support Cluster
3
Unifying the Big Data Platform using Virtualization
. Goals
? Make it fast and easy to provision new data clusters on demand
? Allow Mixing of Workloads
? Leverage virtual machines to provide isolation (esp. for Multi-tenant)
? Optimize data performance based on virtual topologies
? Make the system reliable based on virtual topologies
. Leveraging Virtualization
? Elastic scale
? Use high-availability to protect key services, e.g., Hadoop’s namenode/job
tracker
? Resource controls and sharing: re-use underutilized memory, cpu
? Prioritize Workloads: limit or guarantee resource usage in a mixed
environment Cloud Infrastructure
Private Public
4
VMware is committed to be the Best Virtual platform for Hadoop
. Performance Studies and Best Practices
? Studies through 2010-2011 of Hadoop 0.20 on vSphere 5
? White paper, including detailed configurations and recommendations
. Making Hadoop run well on vSphere
? Performance optimizations in vSphere releases
? VMware engagement in Hadoop Community effort
? Supporting key partners with their distributions on vSphere
? Contributing enhancements to Hadoop
? Automate Hadoop deployment on vSphere
. Hadoop Framework Integration
Serengeti
? Spring for Hadoop: Enabling Spring to simplify
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