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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 Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.

  4. Cascading (software) - Wikipedia

    en.wikipedia.org/wiki/Cascading_(software)

    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. It is open source and available under the Apache License.

  5. Apache Pig - Wikipedia

    en.wikipedia.org/wiki/Apache_Pig

    Apache Pig [1] is a high-level platform for creating programs that run on Apache Hadoop. The language for this platform is called Pig Latin . [ 1 ] Pig can execute its Hadoop jobs in MapReduce , Apache Tez, or Apache Spark . [ 2 ]

  6. Apache Hive - Wikipedia

    en.wikipedia.org/wiki/Apache_Hive

    An optimizer called YSmart [23] is a part of Apache Hive. This correlated optimizer merges correlated MapReduce jobs into a single MapReduce job, significantly reducing the execution time. Executor: After compilation and optimization, the executor executes the tasks. It interacts with the job tracker of Hadoop to schedule tasks to be run.

  7. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    The Hadoop MapReduce architecture is functionally similar to the Google implementation except that the base programming language for Hadoop is Java instead of C++. The implementation is intended to execute on clusters of commodity processors. Hadoop implements a distributed data processing scheduling and execution environment and framework for ...

  8. Bigtable - Wikipedia

    en.wikipedia.org/wiki/Bigtable

    Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]

  9. Parallelization contract - Wikipedia

    en.wikipedia.org/wiki/Parallelization_contract

    In contract, MapReduce programs have a static structure (Map -> Reduce). Data Model: PACT's data model are records of arbitrary many fields of arbitrary types. MapReduce's KeyValue-Pairs can be considered as records with two fields. Apache Flink, an open-source parallel data processing platform has implemented PACTs. Flink allows users to ...