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org email address to prepare a Spark release with the Release Apache Spark GitHub action
from the top result below

Working with component leads to clean up JIRA

https://spark.apache.org/release-process.html
org email address to prepare a Spark release with the Release Apache Spark GitHub action

Security

https://spark.apache.org/security.html
Security For information on what security properties to expect from Apache Spark and how to configure the various security features, see the Spark Security documentation

Bryan Cutler

https://spark.apache.org/committers.html
Unlike apache/spark, this repository uses asf-site as its default branch, and there is no master branch

StackOverflow

https://spark.apache.org/community.html
org Always use the apache-spark tag when asking questions Please also use a secondary tag to specify components so subject matter experts can more easily find them

Contributing to Spark

https://spark.apache.org/contributing.html
org/docs/), edit the Markdown source files in Spark’s docs/ directory, whose README file shows how to build the documentation locally to test your changes

GitHub Actions

https://spark.apache.org/developer-tools.html
jar - lib_managed\jars In the event of “Could not find resource path for Web UI: org/apache/spark/ui/static”, it’s due to a classpath issue (some classes were probably not compiled)

v4.2.0-->

https://spark.apache.org/docs/latest/sql-ref-ansi-compliance.html
enabled=true` SELECT 2147483647 + 1; org

Trademark Guidelines

https://spark.apache.org/trademarks.html
Trademark Guidelines Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation (ASF)

Project and product names using "Spark"

https://spark.apache.org/powered-by.html
org with your organization name, URL, a list of which Spark components you are using, and a short description of your use case

Versioning Policy

https://spark.apache.org/versioning-policy.html
Release cadence Starting with Apache Spark 4

v4.2.0-->

https://spark.apache.org/docs/latest/quick-start.html
first() # First row in this DataFrame Row(value=u'# Apache Spark') Now let’s transform this DataFrame to a new one

Popular libraries with PySpark integrations

https://spark.apache.org/third-party-projects.html
ScaleDP - An Open-Source Library for Processing Documents using AI/ML in Apache Spark

July 16, 2026

https://spark.apache.org/news/
July 16, 2026 We are happy to announce the availability of Apache Spark 3