Hadoop has been widely embraced for its ability to economically store and analyze large data sets. Using parallel computing techniques like MapReduce, Hadoop can reduce long computation times to hours ...

What are some of the cool things in the 2.0 release of Hadoop? To start, how about a revamped MapReduce? And what would you think of a high availability (HA) implementation of the Hadoop Distributed ...

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As the undisputed pioneer of big data, Google established most of the key technologies underlying Hadoop and many of the NoSQL databases. The Google File System (GFS) allowed clusters of commodity ...

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 ...

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 ...

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 proposed ...

With the latest update to its Apache Hadoop distribution, Cloudera has provided the possibility of using data processing algorithms beyond the customary MapReduce, the company announced Tuesday.

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

Over the past few years there have been numerous eulogies given for Hadoop – the powerful, open-source framework for storing and processing data named after a toy elephant. Of course, one could argue ...