About MapReduce 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 ...

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 ...

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

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 now that we are all swimming in Big Data, MapReduce implemented on Hadoop is being packaged as a way for the rest of the world to get the power of this programming model and parallel computing ...

Google today pledged that it will not sue any users, distributors or developers who have implemented open-source versions of its MapReduce programming model for processing large data sets, even ...

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

Hadoop Streaming allows developers to use virtually any programming language to create MapReduce jobs, but it’s a bit of a kludge. The MapReduce programming environment needs to be pluggable.

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.

Aster Data is providing customers with more than 1,000 new MapReduce-ready features designed to increase the adoption of MapReduce by enterprises dealing with big data applications.