Hey Dongjoon, Regarding your questions.
1. If you define a large-ish local relation (which makes us cache it on the serverside) and keep using it, then leak off-heap memory every time it is being used. At some point the OS will OOM kill the driver. While I have a repro, testing it like this in CI is not a good idea. As an alternative I am working on a test that checks buffer clean-up.For the record I don't appreciate the term `claim` here; I am not blocking a release without genuine concern. 2. The root cause is https://databricks.atlassian.net/browse/SPARK-53342 and not the large local relations work. 3. A PR has been open since Friday: https://github.com/apache/spark/pull/53452. I hope that I can get it merged today. 4. I don't see a reason why. Cheers, Herman On Mon, Dec 15, 2025 at 5:47 AM Dongjoon Hyun <[email protected]> wrote: > How can we verify the regression, Herman? > > It's a little difficult for me to evaluate your claim so far due to the > lack of the shared information. Specifically, there is no update for last 3 > days on "SPARK-54696 (Spark Connect LocalRelation support leak off-heap > memory)" after you created it. > > Could you provide us more technical information about your Spark Connect > issue? > > 1. How can we reproduce your claim? Do you have a test case? > > 2. For the root cause, I'm wondering if you are saying literally > SPARK-53917 (Support large local relations) or another JIRA issue. Which > commit is the root cause? > > 3. Since you assigned SPARK-54696 to yourself for last 3 days, do you want > to provide a PR soon? > > 4. If you need more time, shall we simply revert the root cause from > Apache Spark 4.1.0 ? > > Thanks, > Dongjoon > > On 2025/12/14 23:29:59 Herman van Hovell via dev wrote: > > Yes. It is a regression in Spark 4.1. The root cause is a change where we > > fail to clean-up allocated (off-heap) buffers. > > > > On Sun, Dec 14, 2025 at 4:25 AM Dongjoon Hyun <[email protected]> > wrote: > > > > > Hi, Herman. > > > > > > Do you mean that is a regression at Apache Spark 4.1.0? > > > > > > If then, do you know what was the root cause? > > > > > > Dongjoon. > > > > > > On 2025/12/13 23:09:02 Herman van Hovell via dev wrote: > > > > -1. We need to get https://issues.apache.org/jira/browse/SPARK-54696 > > > fixed. > > > > > > > > On Sat, Dec 13, 2025 at 11:07 AM Jules Damji <[email protected]> > > > wrote: > > > > > > > > > +1 non-binding > > > > > — > > > > > Sent from my iPhone > > > > > Pardon the dumb thumb typos :) > > > > > > > > > > > On Dec 11, 2025, at 8:34 AM, [email protected] wrote: > > > > > > > > > > > > Please vote on releasing the following candidate as Apache Spark > > > > > version 4.1.0. > > > > > > > > > > > > The vote is open until Sun, 14 Dec 2025 09:34:31 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 4.1.0 > > > > > > [ ] -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 v4.1.0-rc3 (commit e221b56be7b): > > > > > > https://github.com/apache/spark/tree/v4.1.0-rc3 > > > > > > > > > > > > The release files, including signatures, digests, etc. can be > found > > > at: > > > > > > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-rc3-bin/ > > > > > > > > > > > > Signatures used for Spark RCs can be found in this file: > > > > > > https://downloads.apache.org/spark/KEYS > > > > > > > > > > > > The staging repository for this release can be found at: > > > > > > > > > > https://repository.apache.org/content/repositories/orgapachespark-1508/ > > > > > > > > > > > > The documentation corresponding to this release can be found at: > > > > > > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-rc3-docs/ > > > > > > > > > > > > The list of bug fixes going into 4.1.0 can be found at the > following > > > URL: > > > > > > https://issues.apache.org/jira/projects/SPARK/versions/12355581 > > > > > > > > > > > > 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 via "pip install > > > > > > > > > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-rc3-bin/pyspark-4.1.0.tar.gz > > > > > " > > > > > > and see if anything important breaks. > > > > > > In the Java/Scala, you can add the staging repository to your > > > project's > > > > > resolvers and test > > > > > > with the RC (make sure to clean up the artifact cache > before/after so > > > > > > you don't end up building with an out of date RC going forward). > > > > > > > > > > > > > --------------------------------------------------------------------- > > > > > > To unsubscribe e-mail: [email protected] > > > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > > > > To unsubscribe e-mail: [email protected] > > > > > > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > > To unsubscribe e-mail: [email protected] > > > > > > > > > > --------------------------------------------------------------------- > To unsubscribe e-mail: [email protected] > >
