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From Dongjoon Hyun <dongjoon.h...@gmail.com>
Subject Apache Spark 3.1 Preparation Status (Oct. 2020)
Date Sun, 04 Oct 2020 00:17:05 GMT
Hi, All.

As of today, master branch (Apache Spark 3.1.0) resolved
852+ JIRA issues and 606+ issues are 3.1.0-only patches.
According to the 3.1.0 release window, branch-3.1 will be
created on November 1st and enters QA period.

Here are some notable updates I've been monitoring.

*Language*
01. SPARK-25075 Support Scala 2.13
      - Since SPARK-32926, Scala 2.13 build test has
        become a part of GitHub Action jobs.
      - After SPARK-33044, Scala 2.13 test will be
        a part of Jenkins jobs.
02. SPARK-29909 Drop Python 2 and Python 3.4 and 3.5
03. SPARK-32082 Project Zen: Improving Python usability
      - 7 of 16 issues are resolved.
04. SPARK-32073 Drop R < 3.5 support
      - This is done for Spark 3.0.1 and 3.1.0.

*Dependency*
05. SPARK-32058 Use Apache Hadoop 3.2.0 dependency
      - This changes the default dist. for better cloud support
06. SPARK-32981 Remove hive-1.2 distribution
07. SPARK-20202 Remove references to org.spark-project.hive
      - This will remove Hive 1.2.1 from source code
08. SPARK-29250 Upgrade to Hadoop 3.2.1 (WIP)

*Core*
09. SPARK-27495 Support Stage level resource conf and scheduling
      - 11 of 15 issues are resolved
10. SPARK-25299 Use remote storage for persisting shuffle data
      - 8 of 14 issues are resolved

*Resource Manager*
11. SPARK-33005 Kubernetes GA preparation
      - It is on the way and we are waiting for more feedback.

*SQL*
12. SPARK-30648/SPARK-32346 Support filters pushdown
      to JSON/Avro
13. SPARK-32948/SPARK-32958 Add Json expression optimizer
14. SPARK-12312 Support JDBC Kerberos w/ keytab
      - 11 of 17 issues are resolved
15. SPARK-27589 DSv2 was mostly completed in 3.0
      and added more features in 3.1 but still we missed
      - All built-in DataSource v2 write paths are disabled
        and v1 write is used instead.
      - Support partition pruning with subqueries
      - Support bucketing

We still have one month before the feature freeze
and starting QA. If you are working for 3.1,
please consider the timeline and share your schedule
with the Apache Spark community. For the other stuff,
we can put it into 3.2 release scheduled in June 2021.

Last not but least, I want to emphasize (7) once again.
We need to remove the forked unofficial Hive eventually.
Please let us know your reasons if you need to build
from Apache Spark 3.1 source code for Hive 1.2.

https://github.com/apache/spark/pull/29936

As I wrote in the above PR description, for old releases,
Apache Spark 2.4(LTS) and 3.0 (~2021.12) will provide
Hive 1.2-based distribution.

Bests,
Dongjoon.

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