Intro to Hadoop MapReduce - Indepth
ÜberConf
Denver · July 12 - 15, 2011
About this Presentation
This talk will introduce the Hadoop MapReduce model and common patterns and algorithms implemented to solve common problems.
In this presentation we will introduce the MapReduce processing model and many of the common patterns implemented on top of MapReduce to achieve common processing functionality like joins and secondary sorting. Finally we will discuss a few optimizations and their tradeoffs developers can utilize when creating raw MapReduce applications.
Author of Cascading Data Processing Open Source Project
Chris Wensel is the founder of Concurrent, Inc., and the author of the Cascading data processing open-source project, an alternative API to MapReduce for Apache Hadoop.
He also co-founded Scale Unlimited, the first Hadoop and “Big Data” related professional services and training company, where he mentored and trained companies like Sun Microsystems, Apple, and numerous startups in the Bay Area.
Chris bootstrapped his first Internet startup in the early 90's, creating an early Web server-side scripting language used in the real estate and insurance verticals. During the late 90's, Chris focused on distributed-agent based systems where he received several patents on
distributed computing. From there he became Chief Architect for the fastest growing business unit at Thomson Reuters. Just prior to Concurrent, Chris was a Consulting Architect to TeleAtlas geo-content management group in Belgium.
Chris also advises several startups in the “Big Data” and “Big Audience” technology space.