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  2. MapReduce - Wikipedia

    en.wikipedia.org/wiki/MapReduce

    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 ...

  3. Apache Hive - Wikipedia

    en.wikipedia.org/wiki/Apache_Hive

    The query CREATE TABLE word_counts AS SELECT word, count(1) AS count creates a table called word_counts with two columns: word and count. This query draws its input from the inner query (SELECT explode (split (line, '\s')) AS word FROM docs) temp ". This query serves to split the input words into different rows of a temporary table aliased as temp.

  4. Apache Pig - Wikipedia

    en.wikipedia.org/wiki/Apache_Pig

    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 .

  5. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Apache Spark was developed in 2012 in response to limitations in the MapReduce paradigm, as it adds in-memory processing and the ability to set up many operations (not just map followed by reducing). MIKE2.0 is an open approach to information management that acknowledges the need for revisions due to big data implications identified in an ...

  6. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    Apache Spark is an open-source unified ... orders of magnitude compared to Apache Hadoop MapReduce ... top 10 words. Swap word and count to sort by count. ...

  7. Apache CouchDB - Wikipedia

    en.wikipedia.org/wiki/Apache_CouchDB

    Apache CouchDB is an open-source document-oriented NoSQL database, implemented in Erlang. CouchDB uses multiple formats and protocols to store, transfer, and process its data. It uses JSON to store data, JavaScript as its query language using MapReduce , and HTTP for an API .

  8. Collective operation - Wikipedia

    en.wikipedia.org/wiki/Collective_operation

    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.

  9. Module:Word count - Wikipedia

    en.wikipedia.org/wiki/Module:Word_count

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