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Defining Hadoop

By   /  May 31, 2013  /  No Comments

hadby Angela Guess

Brian Proffitt of ReadWrite recently explained what Hadoop is and how it works. He writes, “You can’t have a conversation about Big Data for very long without running into the elephant in the room: Hadoop. This open source software platform managed by the Apache Software Foundation has proven to be very helpful in storing and managing vast amounts of data cheaply and efficiently. But what exactly is Hadoop, and what makes it so special? Basically, it’s a way of storing enormous data sets across distributed clusters of servers and then running ‘distributed’ analysis applications in each cluster. It’s designed to be robust, in that your Big Data applications will continue to run even when individual servers — or clusters — fail. And it’s also designed to be efficient, because it doesn’t require your applications to shuttle huge volumes of data across your network.”

Proffitt continues, “Here’s how Apache formally describes it: ‘The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly available service on top of a cluster of computers, each of which may be prone to failures.’ Look deeper, though, and there’s even more magic at work. Hadoop is almost completely modular, which means that you can swap out almost any of its components for a different software tool. That makes the architecture incredibly flexible, as well as robust and efficient.”

Read more here.

photo credit: Hadoop

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