Apache Hadoop MapReduce has undergone a complete re-haul to emerge as Apache Hadoop YARN, a generic compute fabric to support MapReduce and other application paradigms. This really changes the game to recast Hadoop as a much more powerful data-processing system. As a result Hadoop looks very different from itself 12 months ago. Now, ever wonder what it might look like in 12 months or 24 months or longer? This talk will take you through some ideas for both the compute framework itself (multi-tenancy, security, isolation, virtualization, enhanced scheduling etc.) and the runtime for applications like MapReduce, MPI, stream processing and real-time data processing.
Arun C Murthy is Founder and Architect at Hortonworks, a software company focussed on focused on accelerating the development and adoption of Apache Hadoop. He also leads next generation MapReduce project in Apache Hadoop and has contributed full-time to Hadoop for 6 years now. In the community, Arun is the VP, Apache Hadoop, at the ASF i.e. the Chair of the Hadoop PMC. Prior to co-founding Hortonworks, Arun was responsible for all Hadoop MapReduce code and configuration deployed across the 42,000+ servers at Yahoo!. In essence, he was responsible for running Apache Hadoop’s MapReduce as a service for Yahoo. He jointly holds the current world sorting record using Apache Hadoop.
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