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.

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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 ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

In the vast universe of IT, data is categorized as being either structured or unstructured, from a macro perspective. Generation of unstructured data is orders of magnitude higher than that generated ...

The MapReduce paradigm has emerged as a transformative framework for processing vast datasets by decomposing complex tasks into simpler map and reduce functions. This approach has been instrumental in ...

Hadoop has been known as MapReduce running on HDFS, but with YARN, Hadoop 2.0 broadens pool of potential applications Hadoop has always been a catch-all for disparate open source initiatives that ...

Facebook has shared some more behind-the-scenes information about just how the social network is built, this time centered around the enormous amount of data that it collects. Over half a petabyte of ...

Google on Wednesday launched Cloud Dataflow, a big data analytics service to crunch information in either streaming or batch mode. The announcement, made at Google's I/O keynote in San Francisco, ...

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 ...