MapReduce


Also found in: Dictionary, Thesaurus, Financial, Wikipedia.

MapReduce

A programming model from Google for processing huge data sets on large clusters of servers. The "map" process transforms the input into key-value pairs, and the "reduce" procedure groups, sorts, filters and summarizes the data. See Hadoop and key-value pair.
Copyright © 1981-2019 by The Computer Language Company Inc. All Rights reserved. THIS DEFINITION IS FOR PERSONAL USE ONLY. All other reproduction is strictly prohibited without permission from the publisher.
Mentioned in ?
References in periodicals archive ?
Finally, we conducted experiments to compare the MapReduce implementation of the M2 algorithm running on the Hadoop cluster (denoted MRC), the MapReduce implementation of the M2 algorithm running on a standalone single-node server (denoted as MRS), the Java implementation of the M2 algorithm running on a single-node server, and the R implementation of the related time-delayed mutual information algorithm, TimeDelay-ARACNE [23].
Additionally, MapReduce implementations of several popular computer vision algorithms, such as clustering for image data and classifier training are described in [7].
The MapReduce model has become a de facto standard for Big Data analytics by capitalizing on clusters of inexpensive commodity computers.
It comprised innovative technologies like the Hadoop HDFS with MapReduce programming and a NoSQL database.
In order to follow this trend and enhance the capabilities of a standard QPSO, the MapReduce quantum-behaved particle swarm optimization is developed.
To realize this, a SPARK MapReduce based algorithm has been developed, which splits the data and performs various algorithm processes in parallel in the map phase and then combines the solutions in the reduce phase to merge the results.
MapReduce is a distributed parallel programming model or framework proposed by Google lab, which is mainly used for the parallel processing of large scale data.
In the second step, the Apache Hadoop and the MapReduce (with Hadoop Streaming) was used for distribute computing for volatility forecasting model.
To calculate the market size, the report considers revenue generated from the sales of Hadoop solutions with functionalities such as MapReduce, integrated solutions, and services (consultation, training, and maintenance).
In that, a combination between MapReduce of Hadoop [1] and MarkLogic NoSQL database [2] with xQuery supported [3] is suggested for experiment.
It was inspired by Google's MapReduce and Google File System and cultivated at Yahoo.