MAPREDUCE PROGRAMMING TRAINING / PROJECTS

MapReduce
Created at Google in response to the problem of creating web search indexes, the MapReduce framework is the powerhouse behind most of today’s big data processing. In addition to Hadoop, you’ll find MapReduce inside MPP and NoSQL databases such as Vertica or MongoDB.
The important innovation of MapReduce is the ability to take a query over a dataset, divide it, and run it in parallel over multiple nodes. Distributing the computation solves the issue of data too large to fit onto a single machine. Combine this technique with commodity Linux servers and you have a cost-effective alternative to massive computing arrays.
At its core, Hadoop is an open source MapReduce implementation. Funded by Yahoo, it emerged in 2006 and, according to its creator Doug Cutting, reached “web scale” capability in early 2008.
As the Hadoop project matured, it acquired further components to enhance its usability and functionality. The name “Hadoop” has come to represent this entire ecosystem. There are parallels with the emergence of Linux: the name refers strictly to the Linux kernel, but it has gained acceptance as referring to a complete operating system.

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