Apache Beam

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Apache Beam
Beam-logo-full-color-name-right-200-autocrop.png
Developer(s)Apache Software Foundation
Initial releaseJune 15, 2016; 2 years ago (2016-06-15)
Stable release
2.7.0 / October 3, 2018; 44 days ago (2018-10-03)
Repository Edit this at Wikidata
Written inJava, Python
Operating systemCross-platform
LicenseApache License 2.0
Websitebeam.apache.org

Apache Beam is an open source unified programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing.[1] Beam Pipelines are defined using one of the provided SDKs and executed in one of the Beam’s supported runners (distributed processing back-ends) including Apache Apex, Apache Flink, Apache Gearpump (incubating), Apache Samza, Apache Spark, and Google Cloud Dataflow[2]

It has been termed an "uber-API for big data".[3]

History[edit]

Apache Beam[2] is one implementation of the Dataflow model paper.[4] The Dataflow model is based on previous work on distributed processing abstractions at Google, in particular on FlumeJava[5] and Millwheel.[6][7]

Google released an open SDK implementation of the Dataflow model in 2014 and an environment to execute Dataflows locally (non-distributed) as well as in the Google Cloud Platform service.

In 2016 Google donated the core SDK as well as the implementation of a local runner, and a set of IOs (data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. Other companies and members of the community have contributed runners for existing distributed execution platforms, as well as new IOs to integrate the Beam Runners with existing Databases, Key-Value stores and Message systems. Additionally new DSLs have been proposed to support specific domain needs on top of the Beam Model.

Timeline[edit]

Version Release date
Current stable version: 2.8.0 2018-10-29
Older version, yet still supported: 2.7.0 2018-10-03
Older version, yet still supported: 2.6.0 2018-08-08
Older version, yet still supported: 2.5.0 2018-06-26
Older version, yet still supported: 2.4.0 2018-03-20
Older version, yet still supported: 2.3.0 2018-01-30
Older version, yet still supported: 2.2.0 2017-12-02
Old version, no longer supported: 2.1.0 2017-08-23
Old version, no longer supported: 2.0.0 2017-05-17
Old version, no longer supported: 0.6.0 2017-03-11
Old version, no longer supported: 0.5.0 2017-02-02
Old version, no longer supported: 0.4.0 2016-12-29
Old version, no longer supported: 0.3.0 2016-10-31
Old version, no longer supported: 0.2.0 2016-08-08
Old version, no longer supported: 0.1.0 2016-06-15
Legend:
Old version
Older version, still supported
Latest version
Latest preview version
Future release

See also[edit]

References[edit]

  1. ^ Woodie, Alex (22 April 2016). "Apache Beam's Ambitious Goal: Unify Big Data Development". Datanami. Retrieved 4 August 2016.
  2. ^ a b "Cloud Dataflow - Batch & Stream Data Processing".
  3. ^ Ian Pointer (April 14, 2016). "Apache Beam wants to be uber-API for big data". InfoWorld.
  4. ^ Akidau, Tyler; Schmidt, Eric; Whittle, Sam; Bradshaw, Robert; Chambers, Craig; Chernyak, Slava; Fernández-Moctezuma, Rafael J.; Lax, Reuven; McVeety, Sam; Mills, Daniel; Perry, Frances (1 August 2015). "The dataflow model" (PDF). Proceedings of the VLDB Endowment. 8 (12): 1792–1803. doi:10.14778/2824032.2824076. Retrieved 4 August 2016.
  5. ^ Chambers, Craig; Raniwala, Ashish; Perry, Frances; Adams, Stephen; Henry, Robert R.; Bradshaw, Robert; Weizenbaum, Nathan (1 January 2010). "FlumeJava: Easy, Efficient Data-parallel Pipelines" (PDF). Proceedings of the 31st ACM SIGPLAN Conference on Programming Language Design and Implementation. ACM: 363–375. doi:10.1145/1806596.1806638. Archived from the original (PDF) on 23 September 2016. Retrieved 4 August 2016.
  6. ^ Akidau, Tyler; Whittle, Sam; Balikov, Alex; Bekiroğlu, Kaya; Chernyak, Slava; Haberman, Josh; Lax, Reuven; McVeety, Sam; Mills, Daniel; Nordstrom, Paul (27 August 2013). "MillWheel" (PDF). Proceedings of the VLDB Endowment. 6 (11): 1033–1044. doi:10.14778/2536222.2536229. Archived from the original (PDF) on 1 February 2016. Retrieved 4 August 2016.
  7. ^ Pointer, Ian. "Apache Beam wants to be uber-API for big data". InfoWorld. Retrieved 4 August 2016.