When your data and work grow, and you still want to produce results in a timely manner, you start to think big. Your one beefy server reaches its limits. You need a way to spread your work across many ...

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, ...

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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.

Data is the new currency of the modern world. Businesses that successfully maximize its value will have a decisive impact on their own value and on their customers’ success. As the de-facto platform ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Leann Chen explains how knowledge graphs ...

Pervasive Software is unveiling on Wednesday version 5.0 of its DataRush parallel application software, which now works with the popular Hadoop MapReduce framework for processing large volumes of data ...

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 Apache Software Foundation unveiled its latest release of its open source data processing program, Hadoop 2. It runs multiple applications simultaneously to enable users to quickly and efficiently ...