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MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Apache Pig was originally [4] developed at Yahoo Research around 2006 for researchers to have an ad hoc way of creating and executing MapReduce jobs on very large data sets. In 2007, [ 5 ] it was moved into the Apache Software Foundation .
The initial code that was factored out of Nutch consisted of about 5,000 lines of code for HDFS and about 6,000 lines of code for MapReduce. In March 2006, Owen O'Malley was the first committer to add to the Hadoop project; [ 21 ] Hadoop 0.1.0 was released in April 2006. [ 22 ]
Cascading is a software abstraction layer for Apache Hadoop and Apache Flink.Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language (Java, JRuby, Clojure, etc.), hiding the underlying complexity of MapReduce jobs.
Information flow of Reduce operation performed on three nodes. f is the associative operator and α is the result of the reduction. The reduce pattern [4] is used to collect data or partial results from different processing units and to combine them into a global result by a chosen operator.
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This framework allows applications based on the MapReduce paradigm to be run on large clusters of commodity hardware. Cutting was an employee of Yahoo! , where he led the Hadoop project full-time; he later went on to work for Cloudera .