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https://issues.apache.org/jira/browse/HADOOP-18887?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18003738#comment-18003738
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karan kumar commented on HADOOP-18887:
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[[email protected]] [~pulparindo] Wanted to check the current update here. In
Apache Druid, we wanted a move to java 17 runtime to get performance benefits
and move off EOL binaries.
> Java 17 Runtime Support
> -----------------------
>
> Key: HADOOP-18887
> URL: https://issues.apache.org/jira/browse/HADOOP-18887
> Project: Hadoop Common
> Issue Type: New Feature
> Components: build
> Reporter: Bruno Ramirez
> Priority: Major
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> This JIRA feature aims to extend the Java runtime support for Hadoop to
> include Java 17 in addition to Java 8 and Java 11. Currently Hadoop version
> 3.3.6 supports Java 8 compile and Java 8/11 runtime. The goal is to make
> Hadoop compatible with Java 17 runtime as well.
> The plan for this release is to allow Hadoop to default to Java 11/Java 17,
> while still providing the flexibility for customers to configure Hadoop to
> use Java 8, Java 11, or Java 17 based on their specific needs. This project's
> objectives include:
> # Certifying that Hadoop works seamlessly on Java 8/11/17 for common use
> cases.
> # Ensuring that running Hadoop on Java 11/17 does not disrupt other
> applications and libraries such as Spark, Hive, Flink, Presto/Trino, and
> HBase.
> The decision to support Java 17 runtime is motivated by customer requests and
> significant performance improvements observed in downstream applications like
> Apache Hive and Apache Spark. The testing process encompasses unit tests,
> integration tests, and performance tests, as well as verifying the proper
> functioning of all Hadoop daemons with Java 17.
> The project will address compile time issues across various Hadoop
> components, ensuring that Hadoop remains compatible with Java 17 throughout
> the entire codebase.
> This ticket serves as a vital step in enhancing Hadoop's capabilities,
> providing customers with more choices and improved performance for their big
> data processing needs.
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