Another place where I've seen MapReduce is Nokia's QtConcurrent framework, an extremely elegant parallel programming library for Qt desktop applications. It's unclear what Google's patent will ...

Enter MapReduce, the goal of which was to provide a “trivially parallelizable framework so that even novice developers (a.k.a interns) could write programs in a variety of languages (Java/C/C++ ...

Google announced on Wednesday that the company is open sourcing a MapReduce framework that will let users run native C and C++ code in their Hadoop environments. Depending on how much traction ...

MapReduce: A programming model that simplifies distributed data processing by dividing tasks into map and reduce functions operating in a parallel, fault-tolerant manner.

MapReduce is a distributed programming model intended for parallel processing of massive amounts of data. This article describes a MapReduce implementation built with off-the-shelf, open-source ...

The market for software related to the Hadoop and MapReduce programming frameworks for large-scale data analysis will jump from US$77 million in 2011 to $812.8 million in 2016, a compound annual ...

The MapReduce and MPP worlds have been pretty separate, but are now starting to collide. And that’s a good thing. To many, Big Data goes hand-in-hand with Hadoop + MapReduce.

We don't have to bother with how execution will proceed and how many instances of map.py and reduce.py will run. We just follow the MapReduce pattern and Hadoop does the rest. MapReduce with Hadoop.