MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “MapReduce: Simplified data ...

Spotting Big Data trends, without MapReduce As Trendspottr shows us, sometimes hardcore algorithms, even older ones, provide new breakthroughs. Written by Andrew Brust, Contributor June 4, 2012 at ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day ...

Hadoop’s MapReduce programming model facilitates parallel processing. Developers specify a map function to process input data and produce intermediate key-value pairs.

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

But there are downsides. The MapReduce programming model that accesses and analyses data in HDFS can be difficult to learn and is designed for batch processing.

Cloud and grid software provider Platform Computing has announced support for the Apache Hadoop MapReduce programming model.

Scaleout Software, a provider of in-memory data grids (IMDGs), announced the availability of ScaleOut hServer V2, which incorporates new technology to run Hadoop MapReduce on live data. This new ...

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...