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Apache Beam - Wikipedia

From Wikipedia, the free encyclopedia

Unified programming model for data processing pipelines

Apache Beam is an open source unified programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing.[2] 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 Flink, Apache Samza, Apache Spark, and Google Cloud Dataflow.[3]

Apache Beam[3] 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.

Apache Beam makes minor releases every 6 weeks.[8]

Version Release date Latest version: 2.64.0 2025-03-31 Old version, still maintained: 2.63.0 2025-02-18 Old version, still maintained: 2.62.0 2025-01-21 Old version, still maintained: 2.61.0 2024-11-25 Old version, still maintained: 2.60.0 2024-10-17 Old version, still maintained: 2.59.0 2024-09-11 Old version, still maintained: 2.58.1 2024-08-15 Old version, still maintained: 2.58.0 2024-08-06 Old version, still maintained: 2.57.0 2024-06-26 Old version, still maintained: 2.56.0 2024-05-01

Legend:

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Old version, still maintained

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 Older versions Version Release date Old version, not maintained: 2.55.0 2024-03-25 Old version, not maintained: 2.54.0 2024-02-14 Old version, not maintained: 2.53.0 2024-01-04 Old version, not maintained: 2.52.0 2023-11-17 Old version, not maintained: 2.51.0 2023-10-11 Old version, not maintained: 2.50.0 2023-08-30 Old version, not maintained: 2.49.0 2023-07-17 Old version, not maintained: 2.48.0 2023-05-31 Old version, not maintained: 2.47.0 2023-05-10 Old version, not maintained: 2.46.0 2023-03-10 Old version, not maintained: 2.45.0 2023-02-15 Old version, not maintained: 2.44.0 2023-01-12 Old version, not maintained: 2.43.0 2022-11-17 Old version, not maintained: 2.42.0 2022-10-17 Old version, not maintained: 2.41.0 2022-08-23 Old version, not maintained: 2.40.0 2022-06-27 Old version, not maintained: 2.39.0 2022-05-25 Old version, not maintained: 2.38.0 2022-04-20 Old version, not maintained: 2.37.0 2022-03-04 Old version, not maintained: 2.36.0 2022-02-07 Old version, not maintained: 2.35.0 2021-12-29 Old version, not maintained: 2.34.0 2021-11-11 Old version, not maintained: 2.33.0 2021-10-07 Old version, not maintained: 2.32.0 2021-08-25 Old version, not maintained: 2.31.0 2021-07-08 Old version, not maintained: 2.30.0 2021-06-09 Old version, not maintained: 2.29.0 2021-04-27 Old version, not maintained: 2.28.0 2021-02-22 Old version, not maintained: 2.27.0 2021-01-08 Old version, not maintained: 2.26.0 2020-12-11 Old version, not maintained: 2.25.0 2020-10-23 Old version, not maintained: 2.24.0 2020-09-18 Old version, not maintained: 2.23.0 2020-07-29 Old version, not maintained: 2.22.0 2020-06-08 Old version, not maintained: 2.21.0 2020-05-27 Old version, not maintained: 2.20.0 2020-04-15 Old version, not maintained: 2.19.0 2020-02-04 Old version, not maintained: 2.18.0 2020-01-23 Old version, not maintained: 2.17.0 2020-01-06 Old version, not maintained: 2.16.0 2019-10-07 Old version, not maintained: 2.15.0 2019-08-22 Old version, not maintained: 2.14.0 2019-08-01 Old version, not maintained: 2.13.0 2019-05-22 Old version, not maintained: 2.12.0 2019-04-25 Old version, not maintained: 2.11.0 2019-02-26 Old version, not maintained: 2.10.0 2019-02-01 Old version, not maintained: 2.9.0 2018-12-13 Old version, not maintained: 2.8.0 2018-10-29 Old version, not maintained: 2.7.0 (LTS) 2018-10-03 Old version, not maintained: 2.6.0 2018-08-08 Old version, not maintained: 2.5.0 2018-06-26 Old version, not maintained: 2.4.0 2018-03-20 Old version, not maintained: 2.3.0 2018-01-30 Old version, not maintained: 2.2.0 2017-12-02 Old version, not maintained: 2.1.0 2017-08-23 Old version, not maintained: 2.0.0 2017-05-17 Old version, not maintained: 0.6.0 2017-03-11 Old version, not maintained: 0.5.0 2017-02-02 Old version, not maintained: 0.4.0 2016-12-29 Old version, not maintained: 0.3.0 2016-10-31 Old version, not maintained: 0.2.0 2016-08-08 Old version, not maintained: 0.1.0 2016-06-15

Legend:

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Latest version

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  1. ^ "Blogs". beam.apache.org. The Apache Software Foundation. Retrieved 2024-08-06.
  2. ^ Woodie, Alex (22 April 2016). "Apache Beam's Ambitious Goal: Unify Big Data Development". Datanami. Retrieved 4 August 2016.
  3. ^ a b "Cloud Dataflow - Batch & Stream Data Processing".
  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". Proceedings of the 31st ACM SIGPLAN Conference on Programming Language Design and Implementation (PDF). ACM. pp. 363–375. doi:10.1145/1806596.1806638. ISBN 9781450300193. S2CID 14888571. 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 (14 April 2016). "Apache Beam wants to be uber-API for big data". InfoWorld. Retrieved 4 August 2016.
  8. ^ "Policies". beam.apache.org. Retrieved 21 April 2022.

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