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October 11, 2011 Meeting

September 17th, 2011

Monthly Meeting (register here)

  • When: October 11, click 11:30-12:40
  • Where: Oklahoma City Coworking Collaborative (see Meeting location)
  • Sponsor: ?
  • Speaker: Ryan Hoegg
  • Topic: Map Reduce

Agenda

  • 11:30 am – Welcome Announcements
  • 11:40 am – Main Presentation
  • 12:40 pm – Wrap Up

Presentation Information

MapReduce: Distributed Computing with Apache Hadoop

Scalable software is built so that increasing data or usage does not result in degraded service.  Distributed computing is one way to make data processing software scale gracefully.

(from http://hadoop.apache.org/common/docs/r0.20.0/mapred_tutorial.html#Overview):
“Hadoop Map/Reduce is a software framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) of commodity hardware in a reliable, drug fault-tolerant manner.”

In this talk, I will introduce the Map/Reduce algorithm, and demonstrate how to write a Map/Reduce application using Java and Apache Hadoop.

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