A programming model for processing large datasets across many machines in parallel, splitting the work into a map step that transforms input records independently and a reduce step that aggregates the mapped results by key.
Facts
Core PrincipleA MapReduce program is composed of a map procedure that performs filtering and sorting, and a reduce procedure that performs a summary operation, allowing large data sets to be processed across many machines in parallel. 1 Connections
In Field
Invented By
Jeff Dean co-authored the 2004 paper with Sanjay Ghemawat that introduced the MapReduce programming model at Google.
Sanjay Ghemawat co-authored the 2004 paper with Jeff Dean that introduced the MapReduce programming model at Google.
Sources
1. Wikipedia: MapReduce
Wikimedia FoundationLead section
A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary operation (such as counting the number of students in each queue, yielding name frequencies).
Patents section, 2004 filing date
In 2010 Google was granted what is described as a patent on MapReduce. The patent, filed in 2004, may cover use of MapReduce by open source software such as Hadoop, CouchDB, and others.
In Group: System Architecture and Data Models, Lead
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster.
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