Parallel Programming and MapReduce
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Introduction
MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key.
Documents• MapReduce HTML Slides• MapReduce PDF Version 
Lectures and Reading Material• Introduction to Parallel Programming
• Advanced MapReduce Lecture #1
• Advanced MapReduce Lecture #2
• Advanced MapReduce Lecture #3
Quiz and Reading Questions• Advanced MapReduce Quiz
• Advanced MapReduce Reading Questions
Coding Projects• Advanced MapReduce Project #1
• Advanced MapReduce Project #2
• MapReduce Codelab
• Advanced MapReduce Group Exercises
University of Washington Lectures• Lecture 1 - Introduction & Parallelization
• Lecture 2 - MapReduce: Theory and Implementation
• Lecture 3 - Networks and Distributed Systems
• Lecture 4 - Distributed File Systems
• Lecture 5 - Other Distributed Systems
University of Washington Labs• Lab 1 - Introduction to MapReduce
• Lab 2 - A Simple Inverted Index
• Lab 3 - PageRank on the Wikipedia Corpus
• Lab 4 - Clustering the Netflix Movie Data
Links• Open Source MapReduce: http://lucene.apache.org/hadoop/ |