MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that goodness to go around. This article gets you started with Hadoop, ...

Late at night at your desk. You are completely stuck in front of a massive, complex project that could elevate your market ...

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 ...

The USPTO awarded search giant Google a software method patent that covers the principle of distributed MapReduce, a strategy for parallel processing that is used by the search giant. If Google ...

When the Big Data moniker is applied to a discussion, it’s often assumed that Hadoop is, or should be, involved. But perhaps that’s just doctrinaire. Hadoop, at its core, consists of HDFS (the Hadoop ...

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

There's been a lot of buzz lately about Google's MapReduce framework for speeding up the processing of large datasets. It makes you wonder, did Google just dream this up in last couple years while all ...