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.

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 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 ...

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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 ...

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 ...

A little over a year ago when I started my company, I was able to find a small office in the Empire State Building. I'm on the 72nd floor facing south, so the view is amazing. I wish I had better ...

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 ...

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 ...

Hadoop is the most significant concrete technology behind the so called “Big Data” revolution. Hadoop combines an economical model for storing massive quantities of data – the Hadoop Distributed File ...