When: October 11, 11:30-12:40
Where: Oklahoma City Coworking Collaborative (see Meeting location)
Sponsor: ?
Speaker: Ryan Hoegg
Topic: Map Reduce
11:30 am - Welcome Announcements
11:40 am - Main Presentation
12:40 pm - Wrap Up
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, 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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