Correct me if I'm wrong: this is a long-standing Spark bug that is very hard to trigger, but the new Parquet version happens to hit the trigger condition and exposes the bug. If this is the case, I'm +1 to fix the Spark bug instead of downgrading the Parquet version.
Let's move the technical discussions to https://github.com/apache/spark/pull/50594. On Tue, Apr 22, 2025 at 11:20 AM Manu Zhang <owenzhang1...@gmail.com> wrote: > I don't think PARQUET-2432 has any issue itself. It looks to have > triggered a deadlock case like https://github.com/apache/spark/pull/50594. > I'd suggest that we fix forward if possible. > > Thanks, > Manu > > On Mon, Apr 21, 2025 at 11:19 PM Rozov, Vlad <vro...@amazon.com.invalid> > wrote: > >> The deadlock is reproducible without Parquet. Please see >> https://github.com/apache/spark/pull/50594. >> >> Thank you, >> >> Vlad >> >> On Apr 21, 2025, at 1:59 AM, Cheng Pan <pan3...@gmail.com> wrote: >> >> The deadlock is introduced by PARQUET-2432(1.14.0), if we decide >> downgrade, the latest workable version is Parquet 1.13.1. >> >> Thanks, >> Cheng Pan >> >> >> >> On Apr 21, 2025, at 16:53, Wenchen Fan <cloud0...@gmail.com> wrote: >> >> +1 to downgrade to Parquet 1.15.0 for Spark 4.0. According to >> https://github.com/apache/spark/pull/50583#issuecomment-2815243571 , the >> Parquet CVE does not affect Spark. >> >> On Mon, Apr 21, 2025 at 2:45 PM Hyukjin Kwon <gurwls...@apache.org> >> wrote: >> >>> That's nice but we need to wait for them to release, and upgrade right? >>> Let's revert the parquet upgrade out of 4.0 branch since we're not directly >>> affected by the CVE anyway. >>> >>> On Mon, 21 Apr 2025 at 15:42, Yuming Wang <yumw...@apache.org> wrote: >>> >>>> It seems this patch(https://github.com/apache/parquet-java/pull/3196) >>>> can avoid deadlock issue if using Parquet 1.15.1. >>>> >>>> On Wed, Apr 16, 2025 at 5:39 PM Niranjan Jayakar >>>> <n...@databricks.com.invalid> wrote: >>>> >>>>> I found another bug introduced in 4.0 that breaks Spark connect client >>>>> x server compatibility: https://github.com/apache/spark/pull/50604. >>>>> >>>>> Once merged, this should be included in the next RC. >>>>> >>>>> On Thu, Apr 10, 2025 at 5:21 PM Wenchen Fan <cloud0...@gmail.com> >>>>> wrote: >>>>> >>>>>> Please vote on releasing the following candidate as Apache Spark >>>>>> version 4.0.0. >>>>>> >>>>>> The vote is open until April 15 (PST) and passes if a majority +1 PMC >>>>>> votes are cast, with a minimum of 3 +1 votes. >>>>>> >>>>>> [ ] +1 Release this package as Apache Spark 4.0.0 >>>>>> [ ] -1 Do not release this package because ... >>>>>> >>>>>> To learn more about Apache Spark, please see >>>>>> https://spark.apache.org/ >>>>>> >>>>>> The tag to be voted on is v4.0.0-rc4 (commit >>>>>> e0801d9d8e33cd8835f3e3beed99a3588c16b776) >>>>>> https://github.com/apache/spark/tree/v4.0.0-rc4 >>>>>> >>>>>> The release files, including signatures, digests, etc. can be found >>>>>> at: >>>>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc4-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-1480/ >>>>>> >>>>>> The documentation corresponding to this release can be found at: >>>>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc4-docs/ >>>>>> >>>>>> The list of bug fixes going into 4.0.0 can be found at the following >>>>>> URL: >>>>>> https://issues.apache.org/jira/projects/SPARK/versions/12353359 >>>>>> >>>>>> This release is using the release script of the tag v4.0.0-rc4. >>>>>> >>>>>> 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). >>>>>> >>>>> >> >>
