Inject hype together with the sadly oh-so-predicatable predictable post-modern label
Are you amazed by the fast response you get while searching the Web with Google or Yahoo? Have you ever wondered how these services manage to search millions of pages and return your results in milliseconds or less? The algorithms that drive both of these major-league search services originated with Google's MapReduce framework.
Java World ![]()
hyperbole, 2008
In essence, it allows massive data sets to be processed in a distributed fashion by breaking the processing into many small computations of two types: a map operation that transforms the input into an intermediate representation, and a reduce function that recombines the intermediate representation into the final output.
Tom White ![]()
, 2005
Applications:
See Also:
Power Through Simplicity
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. Many real world tasks are expressible in this model, as shown in the paper.
Google Research , Map Reduce
Map Reduce As Platform
Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of partitioning the input data, scheduling the program's execution across a set of machines, handling machine failures, and managing the required inter-machine communication. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a large distributed system.
Google Research , Map Reduce
