MapReduce

Author:

Dean Jeffrey1,Ghemawat Sanjay1

Affiliation:

1. Google, Mountain View, CA

Abstract

MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users specify the computation in terms of a map and a reduce function, and the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks. Programmers find the system easy to use: more than ten thousand distinct MapReduce programs have been implemented internally at Google over the past four years, and an average of one hundred thousand MapReduce jobs are executed on Google's clusters every day, processing a total of more than twenty petabytes of data per day.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference17 articles.

1. Hadoop: Open source implementation of MapReduce. http://lucene. apache.org/hadoop/. Hadoop: Open source implementation of MapReduce. http://lucene. apache.org/hadoop/.

2. The Phoenix system for MapReduce programming. http://csl.stanford. edu/~christos/sw/phoenix/. The Phoenix system for MapReduce programming. http://csl.stanford. edu/~christos/sw/phoenix/.

3. High-performance sorting on networks of workstations

4. Web search for a planet: the google cluster architecture

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