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Apache Hadoop™ was born out of a need to process an avalanche of Big Data. The web was generating more and more information on a daily basis, and it was becoming very difficult to index over one billion pages of content. In order to cope, Google invented a new style of data processing known as MapReduce. A year after Google published a white paper describing the MapReduce framework, Doug Cutting and Mike Cafarella, inspired by the white paper, created Hadoop to apply these concepts to an open-source software framework to support distribution for the Nutch search engine project. Given the original case, Hadoop was designed with a simple write-once storage infrastructure.

Hadoop has moved far beyond its beginnings in web indexing and is now used in many industries for a huge variety of tasks that all share the common theme of lots of variety, volume and velocity of data ¨C both structured and unstructured. It is now widely usedacross industries, including finance, media and entertainment, government, healthcare, information services, retail, and other industries with Big Data requirements but the limitations of the original storage infrastructure remain.