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.
Mentioned in ?
References in periodicals archive ?
Section 3 we define our proposed dynamic aggregation and give an overview of the algorithm implemented in MapReduce.
Functional tests include: (i) pre-processed Hadoop verification; (II) The verification of output of Hadoop MapReduce process data; And (iii) validate the data and load it into edw'y.
In order to enable big data processing MapReduce based FCM is proposed.
It is also designed to handle BigData analysis techniques such as MapReduce with or without using a distributed file system.
In the second step, the Apache Hadoop and the MapReduce (with Hadoop Streaming) was used for distribute computing for volatility forecasting model.
In 2003, Google published two papers on distributed file system (GFS and MapReduce programming model, elaborated the inside Google's most important distributed storage platform GFS and distributed computing framework, design idea.
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).
Apache Hive has long played a key role for these workloads, though traditionally leveraging MapReduce as the underlying execution engine.
In that, a combination between MapReduce of Hadoop [1] and MarkLogic NoSQL database [2] with xQuery supported [3] is suggested for experiment.
MapReduce, a part of Hadoop, is especially interesting as a large amount of problems are easily expressible as Hadoop-based MapReduce computations [1].
The Hadoop distributed platform, which uses the MapReduce parallel programming model to realize storage and calculation of large-scale data, is widely applied in current research fields.