Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.

Release Released Support Latest
3.5 1 year and 3 months ago
(09 Sep 2023)
Ends in 2 months and 3 weeks
(09 Mar 2025)
3.5.3
(09 Sep 2024)
3.4 1 year and 8 months ago
(07 Apr 2023)
Yes 3.4.4
(21 Oct 2024)
3.3 2 years and 6 months ago
(09 Jun 2022)
Ended 1 year ago
(09 Dec 2023)
3.3.4
(08 Dec 2023)
3.2 3 years ago
(06 Oct 2021)
Ended 1 year and 8 months ago
(09 Apr 2023)
3.2.4
(09 Apr 2023)
3.1 3 years and 9 months ago
(22 Feb 2021)
Ended 2 years and 3 months ago
(22 Aug 2022)
3.1.3
(06 Feb 2022)
3.0 4 years and 6 months ago
(06 Jun 2020)
Ended 3 years ago
(06 Dec 2021)
3.0.3
(15 Jun 2021)
2.4 (LTS) 6 years ago
(29 Oct 2018)
Ended 3 years and 7 months ago
(09 May 2021)
2.4.8
(09 May 2021)
2.3 6 years and 9 months ago
(22 Feb 2018)
Ended 5 years ago
(25 Aug 2019)
2.3.4
(25 Aug 2019)
2.2 7 years ago
(30 Jun 2017)
Ended 5 years and 10 months ago
(30 Jan 2019)
2.2.3
(07 Jan 2019)
2.1 8 years ago
(15 Dec 2016)
Ended 6 years ago
(26 Jun 2018)
2.1.3
(26 Jun 2018)
2.0 8 years ago
(19 Jul 2016)
Ended 8 years ago
(15 Dec 2016)
2.0.2
(07 Nov 2016)
1.6 8 years and 12 months ago
(21 Dec 2015)
Ended 8 years ago
(19 Jul 2016)
1.6.3
(02 Nov 2016)
1.5 9 years ago
(08 Sep 2015)
Ended 8 years and 12 months ago
(21 Dec 2015)
1.5.2
(09 Nov 2015)
1.4 9 years ago
(02 Jun 2015)
Ended 9 years ago
(08 Sep 2015)
1.4.1
(08 Jul 2015)
1.3 9 years ago
(05 Mar 2015)
Ended 9 years ago
(02 Jun 2015)
1.3.1
(11 Apr 2015)
1.2 10 years ago
(10 Dec 2014)
Ended 9 years ago
(05 Apr 2015)
1.2.2
(05 Apr 2015)
1.1 10 years ago
(03 Sep 2014)
Ended 10 years ago
(10 Dec 2014)
1.1.1
(19 Nov 2014)
1.0 10 years ago
(26 May 2014)
Ended 10 years ago
(03 Sep 2014)
1.0.2
(25 Jul 2014)

Apache Spark follows semantic versioning. Minor releases happen roughly every 6 months and are maintained with bug and security fixes for a period of 18 months.

The last minor release within a major release will typically be maintained for longer as an LTS release. For example, 2.4 was released in November 2nd 2018 and have been maintained for 31 months.

More information is available on the Apache Spark website.

You should be running one of the supported release numbers listed above in the rightmost column.

You can check the version that you are currently using by running:
spark-shell --version
Show Product Identifiers

You can submit an improvement to this page on GitHub :octocat: . This page has a corresponding Talk Page.

A JSON version of this page is available at /api/apache-spark.json. See the API Documentation for more information. You can subscribe to the iCalendar feed at /calendar/apache-spark.ics.