MapReduce in Hadoop 2.0, by the way, is sometimes referred to as MapReduce 2.0, other times as MRv2 and, in still different circles, as YARN (Yet Another Resource Negotiator).

While MapReduce is proprietary technology, the Apache Foundation has implemented its own open source map-reduce framework, called Hadoop.

Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

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 ...

To many, Big Data goes hand-in-hand with Hadoop + MapReduce. But MPP (Massively Parallel Processing) and data warehouse appliances are Big Data technologies too. The MapReduce and MPP worlds have ...

Interest in Apache Spark surpassed Apache Hadoop for the first time last month, according to Google Trends. While it’s not a definitive statement of Spark’s actual impact on big data processing in the ...

Google developed a paradigm called MapReduce in 2004, and Yahoo ! eventually started Hadoop as an implementation of MapReduce in 2005 and released it as an open source project in 2007.

Hadoop in a post-MapReduce world Those familiar with MapReduce will wonder how Tez is different. Tez is a broader, more powerful framework that maintains MapReduce’s strengths while overcoming ...

Hadoop is entering a new chapter in its evolution with the launch of an ambitious community effort from Cloudera Inc. that aims to replace MapReduce as its default data processing engine. The ...