Open main menu

Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily on linear algebra. In the past, many of the implementations use the Apache Hadoop platform, however today it is primarily focused on Apache Spark.[3][4] Mahout also provides Java/Scala libraries for common maths operations (focused on linear algebra and statistics) and primitive Java collections. Mahout is a work in progress; a number of algorithms have been implemented,[5].

Apache Mahout
Apache Mahout Logo
Developer(s)Apache Software Foundation
Initial release7 April 2009 (2009-04-07)[1]
Stable release
0.14.0 / 6 March 2019; 7 months ago (2019-03-06)[2]
RepositoryMahout Repository
Written inJava, Scala
Operating systemCross-platform
TypeMachine learning
LicenseApache License 2.0
Websitemahout.apache.org

While Mahout's core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm, it does not restrict contributions to Hadoop-based implementations. Contributions that run on a single node or on a non-Hadoop cluster are also welcomed. For example, the 'Taste' collaborative-filtering recommender component of Mahout was originally a separate project and can run stand-alone without Hadoop.

Starting with the release 0.10.0, the project shifted its focus to building a backend-independent programming environment, code named "Samsara".[6][7][8] The environment consists of an algebraic backend-independent optimizer and an algebraic Scala DSL unifying in-memory and distributed algebraic operators. Supported algebraic platforms are Apache Spark, H2O, and Apache Flink.[citation needed] Support for MapReduce algorithms started being gradually phased out in 2014.[9]

ReferencesEdit

  1. ^ "Apache Mahout: First release 0.1 released".
  2. ^ "Apache Mahout: Scalable machine learning and data mining". Retrieved 6 March 2019.
  3. ^ "Introducing Apache Mahout". ibm.com. 2011. Retrieved 13 September 2011.
  4. ^ "InfoQ: Apache Mahout: Highly Scalable Machine Learning Algorithms". infoq.com. 2011. Retrieved 13 September 2011.
  5. ^ "Algorithms - Apache Mahout - Apache Software Foundation". cwiki.apache.org. 2011. Retrieved 13 September 2011.
  6. ^ "Mahout-Samsara's In-Core Linear Algebra DSL Reference".
  7. ^ "Mahout-Samsara's Distributed Linear Algebra DSL Reference".
  8. ^ "Mahout 0.10.x: first Mahout release as a programming environment". www.weatheringthroughtechdays.com. Archived from the original on 9 October 2016. Retrieved 29 February 2016.
  9. ^ "MAHOUT-1510 ("Good-bye MapReduce")".

External linksEdit