We need add https://github.com/apache/spark/pull/36556 to RC2.
在 2022-05-17 17:37:13，"Hyukjin Kwon" <gurwls...@gmail.com> 写道： That seems like a test-only issue. I made a quick followup at https://github.com/apache/spark/pull/36576. On Tue, 17 May 2022 at 03:56, Sean Owen <sro...@gmail.com> wrote: I'm still seeing failures related to the function registry, like: ExpressionsSchemaSuite: - Check schemas for expression examples *** FAILED *** 396 did not equal 398 Expected 396 blocks in result file but got 398. Try regenerating the result files. (ExpressionsSchemaSuite.scala:161) - SPARK-14415: All functions should have own descriptions *** FAILED *** "Function: bloom_filter_aggClass: org.apache.spark.sql.catalyst.expressions.aggregate.BloomFilterAggregateUsage: N/A." contained "N/A." Failed for [function_desc: string] (N/A. existed in the result) (QueryTest.scala:54) There seems to be consistently a difference of 2 in the list of expected functions and actual. I haven't looked closely, don't know this code. I'm on Ubuntu 22.04. Anyone else seeing something like this? Wondering if it's something weird to do with case sensitivity, hidden files lurking somewhere, etc. I suspect it's not a 'real' error as the Linux-based testers work fine, but I also can't think of why this is failing. On Mon, May 16, 2022 at 7:44 AM Maxim Gekk <maxim.g...@databricks.com.invalid> wrote: Please vote on releasing the following candidate as Apache Spark version 3.3.0. The vote is open until 11:59pm Pacific time May 19th and passes if a majority +1 PMC votes are cast, with a minimum of 3 +1 votes. [ ] +1 Release this package as Apache Spark 3.3.0 [ ] -1 Do not release this package because ... To learn more about Apache Spark, please see http://spark.apache.org/ The tag to be voted on is v3.3.0-rc2 (commit c8c657b922ac8fd8dcf9553113e11a80079db059): https://github.com/apache/spark/tree/v3.3.0-rc2 The release files, including signatures, digests, etc. can be found at: https://dist.apache.org/repos/dist/dev/spark/v3.3.0-rc2-bin/ Signatures used for Spark RCs can be found in this file: https://dist.apache.org/repos/dist/dev/spark/KEYS The staging repository for this release can be found at: https://repository.apache.org/content/repositories/orgapachespark-1403 The documentation corresponding to this release can be found at: https://dist.apache.org/repos/dist/dev/spark/v3.3.0-rc2-docs/ The list of bug fixes going into 3.3.0 can be found at the following URL: https://issues.apache.org/jira/projects/SPARK/versions/12350369 This release is using the release script of the tag v3.3.0-rc2. FAQ ========================= How can I help test this release? ========================= If you are a Spark user, you can help us test this release by taking an existing Spark workload and running on this release candidate, then reporting any regressions. If you're working in PySpark you can set up a virtual env and install the current RC and see if anything important breaks, in the Java/Scala you can add the staging repository to your projects resolvers and test with the RC (make sure to clean up the artifact cache before/after so you don't end up building with a out of date RC going forward). =========================================== What should happen to JIRA tickets still targeting 3.3.0? =========================================== The current list of open tickets targeted at 3.3.0 can be found at: https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 3.3.0 Committers should look at those and triage. Extremely important bug fixes, documentation, and API tweaks that impact compatibility should be worked on immediately. Everything else please retarget to an appropriate release. ================== But my bug isn't fixed? ================== In order to make timely releases, we will typically not hold the release unless the bug in question is a regression from the previous release. That being said, if there is something which is a regression that has not been correctly targeted please ping me or a committer to help target the issue. Maxim Gekk Software Engineer Databricks, Inc.
