Apache Spark · Lifecycle Status

Apache Spark End of Life (EOL) Dates & Support Timeline

Complete end-of-life dates, support windows, and security status for all Apache Spark versions. Data sourced from endoflife.date and official vendor documentation. Updated at every deploy.

Apache Spark 4.0 reaches end of life on November 23, 2026. Plan your migration now — 60 days remaining.

Apache Spark 4.2 is supported until January 11, 2028, its end-of-support date. The next Apache Spark version to reach end of life is 4.0, on November 23, 2026. 17 of 21 tracked Apache Spark versions are past end of life; the most recent to reach it, 3.4, did so on October 21, 2024. The full Apache Spark lifecycle, with every version's release and end-of-support date, is in the table below.

Running an EOL version? Get matched with support options — free ↓
📅 Get reminded before Apache Spark 4.0 reaches EOL on November 23, 2026 — alerts 90, 30 & 7 days out.
Google →
✉️ Or get it by email — alerts at 90 / 60 / 30 / 7 days and on the day: Free · one-click unsubscribe in every email · no other mail, ever
Latest Active
4.2.0
4.2 series
Next EOL
4.0
Nov 23, 2026
Active Versions
3
of 21 total
EOL Versions
17
no longer patched
65 / 100
High Risk
EOL Risk Score™  How is this calculated? →
EOL Recency
35/40
Attack Surface
10/30 Medium tier
CISA KEV Exposure
20/20 Named in CISA KEV
Extended Support
0/10 Available
EOL Risk Score™ — proprietary methodology by endoflife.ai. Factors: EOL recency, attack surface breadth, CISA KEV catalog presence, extended support availability. Updated at every build. Methodology →
CPE Identifier
cpe:2.3:a:apache:spark
The Common Platform Enumeration name vulnerability scanners and CVE records use for Apache Spark. Verified against the NIST CPE dictionary. Machine-readable for all products: cpe-map.json
Package URLs (purl)
pkg:github/apache/spark
pkg:docker/library/spark
The package URL identifiers SBOM tools emit for Apache Spark, so a CycloneDX or SPDX component resolves to this page by exact identifier rather than by name. Machine-readable for all products: purl-map.json; whole-SBOM checks: POST /v1/sbom or the Stack Scanner.
Release Cycle Timeline
EOL   Warning   Active   Today
Release cycle timeline 201520162017201820192020202120222023202420252026202720281.01.11.21.31.41.51.62.02.12.22.32.43.03.13.23.33.43.54.04.14.2TODAY
17 versions of Apache Spark are past end of life — security patches have stopped. Get matched with support →
All Versions
VersionLatest ReleaseRelease DateEOL DateDaysStatus
1.0 1.0.2 May 26, 2014 Sep 3, 2014 4404 days past EOL EOL
1.1 1.1.1 Sep 3, 2014 Dec 10, 2014 4306 days past EOL EOL
1.2 1.2.2 Dec 10, 2014 Apr 5, 2015 4190 days past EOL EOL
1.3 1.3.1 Mar 5, 2015 Jun 2, 2015 4132 days past EOL EOL
1.4 1.4.1 Jun 2, 2015 Sep 8, 2015 4034 days past EOL EOL
1.5 1.5.2 Sep 8, 2015 Dec 21, 2015 3930 days past EOL EOL
1.6 1.6.3 Dec 21, 2015 Jul 19, 2016 3719 days past EOL EOL
2.0 2.0.2 Jul 19, 2016 Dec 15, 2016 3570 days past EOL EOL
2.1 2.1.3 Dec 15, 2016 Jun 26, 2018 3012 days past EOL EOL
2.2 2.2.3 Jun 30, 2017 Jan 30, 2019 2794 days past EOL EOL
2.3 2.3.4 Feb 22, 2018 Aug 25, 2019 2587 days past EOL EOL
2.4 LTS 2.4.8 Oct 29, 2018 May 9, 2021 1964 days past EOL EOL
3.0 3.0.3 Jun 6, 2020 Dec 6, 2021 1753 days past EOL EOL
3.1 3.1.3 Feb 22, 2021 Aug 22, 2022 1494 days past EOL EOL
3.2 3.2.4 Oct 6, 2021 Apr 9, 2023 1264 days past EOL EOL
3.3 3.3.4 Jun 9, 2022 Dec 9, 2023 1020 days past EOL EOL
3.4 3.4.4 Apr 7, 2023 Oct 21, 2024 703 days past EOL EOL
3.5 LTS 3.5.9 Sep 9, 2023 Nov 30, 2027 432 days remaining Active
4.0 4.0.4 May 19, 2025 Nov 23, 2026 60 days remaining Warning
4.1 4.1.3 Dec 11, 2025 Jun 11, 2027 260 days remaining Active
4.2 4.2.0 Jul 14, 2026 Jan 11, 2028 474 days remaining Active
Apache Spark EOL status badge Live EOL badge for your README — updates automatically at every build. [![Apache Spark EOL](https://img.shields.io/endpoint?url=https%3A%2F%2Fendoflife.ai%2Fbadge%2Fapache-spark.json)](https://endoflife.ai/apache-spark)

Apache Spark release and support pattern

Across the 21 release lines with a published release date, Apache Spark has shipped a new line roughly every 7 months (median interval). A line typically stays supported for about 1.5 years from its release to its end-of-life date. 2 of the 21 tracked lines are designated long-term support, which is where the longer windows sit.

Of the 21 release lines tracked, 17 are past end of life and 4 are still within support. The newest line, 4.2, was released July 14, 2026. The next scheduled end of life is 4.0 on November 23, 2026 — 60 days from this build. The longest-supported line currently published is 4.2, to January 11, 2028.

Computed from the tracked release data at every build — the figures above are the dates in the table, restated, not an editorial estimate.

Apache Spark security intelligence

CISA KEV history: Apache Spark is named in CISA's Known Exploited Vulnerabilities catalog 1 time, most recently on 2023-03-07. Derived from CISA's live catalog at every build.

What does Apache Spark end of life mean for your organization?

When a version of Apache Spark reaches end of life, the maintainers stop issuing security patches. Vulnerabilities discovered after this date are publicly disclosed on the National Vulnerability Database, exploit code appears on GitHub, and your systems remain permanently exposed.

The CVE blind spot: A CVE-based scan does not show the accumulation of unpatched vulnerabilities in EOL software. Some scanners flag unsupported versions of common products, but coverage varies, and none of them give you the date in advance. With a zero-day, nobody knows about the vulnerability. With EOL software, the vulnerability is public — listed, rated, and often weaponized — but no vendor patch is coming. This is one of the most dangerous gaps in enterprise security posture.

Organizations running EOL Apache Spark should treat it as a vulnerability class in their risk register, apply compensating controls (network segmentation, enhanced monitoring, access restriction), and prioritize migration to a supported version.

Your options when Apache Spark reaches end of life

There are four realistic paths. Which one is right depends far more on how long the system needs to keep running than on the version you are on today.

OptionBest whenWatch out for
Move to a supported version The system will outlive the current version's support window and you can schedule the work Budget for compatibility testing, not just the upgrade itself — that is where the real cost sits
Replace the component The project is unmaintained, or a better-supported alternative exists The replacement has its own lifecycle and its own end-of-life date — you are changing vendors, not escaping the problem
Buy extended support Migration is genuinely underway but cannot finish before the deadline, or the workload is frozen by certification or a third-party application A bridge, not a destination — every year purchased is a year the migration still has to happen
Document accepted risk The system is isolated, short-lived, or scheduled for retirement Only defensible with real compensating controls and a written decision — auditors treat undocumented end-of-life software as a finding

How to choose, in one question: how many more years does this system need to run? Under a year, extended support (where it exists) is usually cheaper than an emergency migration. One to three years, migrate — support purchased repeatedly costs more than doing the project once, and the project only gets harder as the version ages. Indefinitely, migrate now and plan the next migration before it surprises you.

Worth saying plainly, because vendors selling extended support rarely will: extended support is often the more expensive choice over a multi-year horizon. It is the right answer when a deadline is genuinely unreachable, not as a default. Compare the annual fee against the one-time cost of migrating before committing to either.

Formalizing decisions like this across your estate? Our free EOL policy template is a ready-to-adopt policy with risk tiers, remediation SLAs, and audit mapping — no signup, free to use and share.

Extended Support Options

If you cannot migrate immediately, extended support vendors provide continued security patches for EOL Apache Spark versions. This is a bridge, not a permanent solution — plan your migration in parallel.

endoflife.ai
Get Apache Spark Support Options

Apache Spark has 17 versions past end of life — security patches have stopped, but CVE disclosures haven't. Extended support past the official date exists for many products in this position — whether it exists for Apache Spark is exactly what we check. Tell us where to reach you and we'll reply with matched options and pricing guidance — or an honest "no vendor covers this."

Free · No obligation · Independent — we track the dates, vendors don't pay for placement · Dates verified against vendor sources
Frequently Asked Questions
What is the end-of-life date for Apache Spark?
The next Apache Spark version reaching EOL is 4.0 on November 23, 2026. See the full table above for all version EOL dates.
When is the Apache Spark support end date?
The next Apache Spark support end date is November 23, 2026, when version 4.0 reaches end of support. Each version has its own support end date — see the table above for every version's date.
What is the latest supported version of Apache Spark?
The latest active version of Apache Spark is 4.2.0. Always verify against the table above as support windows can change.
What happens when Apache Spark reaches end of life?
When Apache Spark reaches end of life, the vendor stops issuing security patches. Any CVEs disclosed after the EOL date accumulate with no vendor patch path — a growing attack surface that a CVE-based scan does not show. Some scanners flag unsupported versions of common products, but coverage varies, and none of them give the date in advance.
How do I check if I'm running an EOL version of Apache Spark?
Check your current version against the table above. If your version's EOL date has passed, you are running unsupported software. You can also use the endoflife.ai Stack Scanner to check your entire dependency file at once.
Is there extended support available for EOL Apache Spark versions?
Some vendors offer extended support for EOL software. Contact the original vendor or check with enterprise support providers for options.

Related Products

Upstream dataset: endoflife.date API · endoflife.date · Generated at build time · How we source data →
Apache Spark end-of-life status badge