[VOTE] SPARK 2.4.0 (RC5)

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[VOTE] SPARK 2.4.0 (RC5)

cloud0fan
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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you don't end up building with a out of date RC going forward).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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Xiao Li-2
+1 

On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.


--
Spark+AI Summit North America 2019
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Re: [VOTE] SPARK 2.4.0 (RC5)

Sean Owen-2
In reply to this post by cloud0fan
+1

Same result as in RC4 from me, and the issues I know of that were
raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.

These items are still targeted to 2.4.0; Xiangrui I assume these
should just be untargeted now, or resolved?
SPARK-25584 Document libsvm data source in doc site
SPARK-25346 Document Spark builtin data sources
SPARK-24464 Unit tests for MLlib's Instrumentation
On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:

>
> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>
> The vote is open until November 1 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 2.4.0
> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
> https://github.com/apache/spark/tree/v2.4.0-rc5
>
> The release files, including signatures, digests, etc. can be found at:
> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>
> The documentation corresponding to this release can be found at:
> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>
> The list of bug fixes going into 2.4.0 can be found at the following URL:
> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>
> 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 2.4.0?
> ===========================================
>
> The current list of open tickets targeted at 2.4.0 can be found at:
> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>
> 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.

---------------------------------------------------------------------
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Re: [VOTE] SPARK 2.4.0 (RC5)

Gengliang
+1

> 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>
> +1
>
> Same result as in RC4 from me, and the issues I know of that were
> raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>
> These items are still targeted to 2.4.0; Xiangrui I assume these
> should just be untargeted now, or resolved?
> SPARK-25584 Document libsvm data source in doc site
> SPARK-25346 Document Spark builtin data sources
> SPARK-24464 Unit tests for MLlib's Instrumentation
> On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>>
>> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>>
>> The vote is open until November 1 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 2.4.0
>> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> https://github.com/apache/spark/tree/v2.4.0-rc5
>>
>> The release files, including signatures, digests, etc. can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>>
>> The documentation corresponding to this release can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>>
>> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>>
>> 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 2.4.0?
>> ===========================================
>>
>> The current list of open tickets targeted at 2.4.0 can be found at:
>> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>>
>> 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.
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: [hidden email]
>


---------------------------------------------------------------------
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Re: [VOTE] SPARK 2.4.0 (RC5)

Hyukjin Kwon
+1

2018년 10월 30일 (화) 오전 11:03, Gengliang Wang <[hidden email]>님이 작성:
+1

> 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>
> +1
>
> Same result as in RC4 from me, and the issues I know of that were
> raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>
> These items are still targeted to 2.4.0; Xiangrui I assume these
> should just be untargeted now, or resolved?
> SPARK-25584 Document libsvm data source in doc site
> SPARK-25346 Document Spark builtin data sources
> SPARK-24464 Unit tests for MLlib's Instrumentation
> On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>>
>> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>>
>> The vote is open until November 1 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 2.4.0
>> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> https://github.com/apache/spark/tree/v2.4.0-rc5
>>
>> The release files, including signatures, digests, etc. can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>>
>> The documentation corresponding to this release can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>>
>> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>>
>> 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 2.4.0?
>> ===========================================
>>
>> The current list of open tickets targeted at 2.4.0 can be found at:
>> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>>
>> 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.
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: [hidden email]
>


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Re: [VOTE] SPARK 2.4.0 (RC5)

DB Tsai-6
+0

I understand that schema pruning is an experimental feature in Spark
2.4, and this can help a lot in read performance as people are trying
to keep the hierarchical data in nested format.

We just found a serious bug---it could fail parquet reader if a nested
field and top level field are selected simultaneously.
https://issues.apache.org/jira/browse/SPARK-25879

If we decide to not fix it in 2.4, we should at least document it in
the release note to let users know.

Sincerely,

DB Tsai
----------------------------------------------------------
Web: https://www.dbtsai.com
PGP Key ID: 0x5CED8B896A6BDFA0
On Mon, Oct 29, 2018 at 8:42 PM Hyukjin Kwon <[hidden email]> wrote:

>
> +1
>
> 2018년 10월 30일 (화) 오전 11:03, Gengliang Wang <[hidden email]>님이 작성:
>>
>> +1
>>
>> > 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>> >
>> > +1
>> >
>> > Same result as in RC4 from me, and the issues I know of that were
>> > raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>> >
>> > These items are still targeted to 2.4.0; Xiangrui I assume these
>> > should just be untargeted now, or resolved?
>> > SPARK-25584 Document libsvm data source in doc site
>> > SPARK-25346 Document Spark builtin data sources
>> > SPARK-24464 Unit tests for MLlib's Instrumentation
>> > On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>> >>
>> >> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>> >>
>> >> The vote is open until November 1 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 2.4.0
>> >> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> >> https://github.com/apache/spark/tree/v2.4.0-rc5
>> >>
>> >> The release files, including signatures, digests, etc. can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>> >>
>> >> The documentation corresponding to this release can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>> >>
>> >> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> >> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>> >>
>> >> 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 2.4.0?
>> >> ===========================================
>> >>
>> >> The current list of open tickets targeted at 2.4.0 can be found at:
>> >> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>> >>
>> >> 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.
>> >
>> > ---------------------------------------------------------------------
>> > To unsubscribe e-mail: [hidden email]
>> >
>>
>>
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: [hidden email]
>>

---------------------------------------------------------------------
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Re: [VOTE] SPARK 2.4.0 (RC5)

Xiao Li-2
Yes, this is not a blocker. "spark.sql.optimizer.nestedSchemaPruning.enabled" is intentionally off by default. As DB Tsai said, column pruning of nested schema for Parquet tables is experimental. In this release, we encourage the whole community to try this new feature but it might have bugs like what the JIRA SPARK-25879 reports. 

We still can fix the issues in the minor release of Spark 2.4, as long as the risk is not high.

Thanks,

Xiao


On Mon, Oct 29, 2018 at 11:49 PM DB Tsai <[hidden email]> wrote:
+0

I understand that schema pruning is an experimental feature in Spark
2.4, and this can help a lot in read performance as people are trying
to keep the hierarchical data in nested format.

We just found a serious bug---it could fail parquet reader if a nested
field and top level field are selected simultaneously.
https://issues.apache.org/jira/browse/SPARK-25879

If we decide to not fix it in 2.4, we should at least document it in
the release note to let users know.

Sincerely,

DB Tsai
----------------------------------------------------------
Web: https://www.dbtsai.com
PGP Key ID: 0x5CED8B896A6BDFA0
On Mon, Oct 29, 2018 at 8:42 PM Hyukjin Kwon <[hidden email]> wrote:
>
> +1
>
> 2018년 10월 30일 (화) 오전 11:03, Gengliang Wang <[hidden email]>님이 작성:
>>
>> +1
>>
>> > 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>> >
>> > +1
>> >
>> > Same result as in RC4 from me, and the issues I know of that were
>> > raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>> >
>> > These items are still targeted to 2.4.0; Xiangrui I assume these
>> > should just be untargeted now, or resolved?
>> > SPARK-25584 Document libsvm data source in doc site
>> > SPARK-25346 Document Spark builtin data sources
>> > SPARK-24464 Unit tests for MLlib's Instrumentation
>> > On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>> >>
>> >> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>> >>
>> >> The vote is open until November 1 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 2.4.0
>> >> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> >> https://github.com/apache/spark/tree/v2.4.0-rc5
>> >>
>> >> The release files, including signatures, digests, etc. can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>> >>
>> >> The documentation corresponding to this release can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>> >>
>> >> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> >> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>> >>
>> >> 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 2.4.0?
>> >> ===========================================
>> >>
>> >> The current list of open tickets targeted at 2.4.0 can be found at:
>> >> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>> >>
>> >> 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.
>> >
>> > ---------------------------------------------------------------------
>> > To unsubscribe e-mail: [hidden email]
>> >
>>
>>
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: [hidden email]
>>

---------------------------------------------------------------------
To unsubscribe e-mail: [hidden email]



--
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Re: [VOTE] SPARK 2.4.0 (RC5)

cloud0fan
Thanks for reporting the bug! I'll list it as a known issue for 2.4.0

I'm adding my own +1, since all the known blockers are resolved.

On Tue, Oct 30, 2018 at 2:56 PM Xiao Li <[hidden email]> wrote:
Yes, this is not a blocker. "spark.sql.optimizer.nestedSchemaPruning.enabled" is intentionally off by default. As DB Tsai said, column pruning of nested schema for Parquet tables is experimental. In this release, we encourage the whole community to try this new feature but it might have bugs like what the JIRA SPARK-25879 reports. 

We still can fix the issues in the minor release of Spark 2.4, as long as the risk is not high.

Thanks,

Xiao


On Mon, Oct 29, 2018 at 11:49 PM DB Tsai <[hidden email]> wrote:
+0

I understand that schema pruning is an experimental feature in Spark
2.4, and this can help a lot in read performance as people are trying
to keep the hierarchical data in nested format.

We just found a serious bug---it could fail parquet reader if a nested
field and top level field are selected simultaneously.
https://issues.apache.org/jira/browse/SPARK-25879

If we decide to not fix it in 2.4, we should at least document it in
the release note to let users know.

Sincerely,

DB Tsai
----------------------------------------------------------
Web: https://www.dbtsai.com
PGP Key ID: 0x5CED8B896A6BDFA0
On Mon, Oct 29, 2018 at 8:42 PM Hyukjin Kwon <[hidden email]> wrote:
>
> +1
>
> 2018년 10월 30일 (화) 오전 11:03, Gengliang Wang <[hidden email]>님이 작성:
>>
>> +1
>>
>> > 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>> >
>> > +1
>> >
>> > Same result as in RC4 from me, and the issues I know of that were
>> > raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>> >
>> > These items are still targeted to 2.4.0; Xiangrui I assume these
>> > should just be untargeted now, or resolved?
>> > SPARK-25584 Document libsvm data source in doc site
>> > SPARK-25346 Document Spark builtin data sources
>> > SPARK-24464 Unit tests for MLlib's Instrumentation
>> > On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>> >>
>> >> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>> >>
>> >> The vote is open until November 1 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 2.4.0
>> >> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> >> https://github.com/apache/spark/tree/v2.4.0-rc5
>> >>
>> >> The release files, including signatures, digests, etc. can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>> >>
>> >> The documentation corresponding to this release can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>> >>
>> >> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> >> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>> >>
>> >> 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 2.4.0?
>> >> ===========================================
>> >>
>> >> The current list of open tickets targeted at 2.4.0 can be found at:
>> >> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>> >>
>> >> 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.
>> >
>> > ---------------------------------------------------------------------
>> > To unsubscribe e-mail: [hidden email]
>> >
>>
>>
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: [hidden email]
>>

---------------------------------------------------------------------
To unsubscribe e-mail: [hidden email]



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Re: [VOTE] SPARK 2.4.0 (RC5)

Ryan Blue
+1

On Tue, Oct 30, 2018 at 4:42 AM Wenchen Fan <[hidden email]> wrote:
Thanks for reporting the bug! I'll list it as a known issue for 2.4.0

I'm adding my own +1, since all the known blockers are resolved.

On Tue, Oct 30, 2018 at 2:56 PM Xiao Li <[hidden email]> wrote:
Yes, this is not a blocker. "spark.sql.optimizer.nestedSchemaPruning.enabled" is intentionally off by default. As DB Tsai said, column pruning of nested schema for Parquet tables is experimental. In this release, we encourage the whole community to try this new feature but it might have bugs like what the JIRA SPARK-25879 reports. 

We still can fix the issues in the minor release of Spark 2.4, as long as the risk is not high.

Thanks,

Xiao


On Mon, Oct 29, 2018 at 11:49 PM DB Tsai <[hidden email]> wrote:
+0

I understand that schema pruning is an experimental feature in Spark
2.4, and this can help a lot in read performance as people are trying
to keep the hierarchical data in nested format.

We just found a serious bug---it could fail parquet reader if a nested
field and top level field are selected simultaneously.
https://issues.apache.org/jira/browse/SPARK-25879

If we decide to not fix it in 2.4, we should at least document it in
the release note to let users know.

Sincerely,

DB Tsai
----------------------------------------------------------
Web: https://www.dbtsai.com
PGP Key ID: 0x5CED8B896A6BDFA0
On Mon, Oct 29, 2018 at 8:42 PM Hyukjin Kwon <[hidden email]> wrote:
>
> +1
>
> 2018년 10월 30일 (화) 오전 11:03, Gengliang Wang <[hidden email]>님이 작성:
>>
>> +1
>>
>> > 在 2018年10月30日,上午10:41,Sean Owen <[hidden email]> 写道:
>> >
>> > +1
>> >
>> > Same result as in RC4 from me, and the issues I know of that were
>> > raised with RC4 are resolved. I tested vs Scala 2.12 and 2.11.
>> >
>> > These items are still targeted to 2.4.0; Xiangrui I assume these
>> > should just be untargeted now, or resolved?
>> > SPARK-25584 Document libsvm data source in doc site
>> > SPARK-25346 Document Spark builtin data sources
>> > SPARK-24464 Unit tests for MLlib's Instrumentation
>> > On Mon, Oct 29, 2018 at 5:22 AM Wenchen Fan <[hidden email]> wrote:
>> >>
>> >> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>> >>
>> >> The vote is open until November 1 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 2.4.0
>> >> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
>> >> https://github.com/apache/spark/tree/v2.4.0-rc5
>> >>
>> >> The release files, including signatures, digests, etc. can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>> >>
>> >> The documentation corresponding to this release can be found at:
>> >> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>> >>
>> >> The list of bug fixes going into 2.4.0 can be found at the following URL:
>> >> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>> >>
>> >> 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 2.4.0?
>> >> ===========================================
>> >>
>> >> The current list of open tickets targeted at 2.4.0 can be found at:
>> >> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>> >>
>> >> 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.
>> >
>> > ---------------------------------------------------------------------
>> > To unsubscribe e-mail: [hidden email]
>> >
>>
>>
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: [hidden email]
>>

---------------------------------------------------------------------
To unsubscribe e-mail: [hidden email]



--
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--
Ryan Blue
Software Engineer
Netflix
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Re: [VOTE] SPARK 2.4.0 (RC5)

Marcelo Vanzin-2
In reply to this post by cloud0fan
+1
On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:

>
> Please vote on releasing the following candidate as Apache Spark version 2.4.0.
>
> The vote is open until November 1 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 2.4.0
> [ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):
> https://github.com/apache/spark/tree/v2.4.0-rc5
>
> The release files, including signatures, digests, etc. can be found at:
> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-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-1291
>
> The documentation corresponding to this release can be found at:
> https://dist.apache.org/repos/dist/dev/spark/v2.4.0-rc5-docs/
>
> The list of bug fixes going into 2.4.0 can be found at the following URL:
> https://issues.apache.org/jira/projects/SPARK/versions/12342385
>
> 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 2.4.0?
> ===========================================
>
> The current list of open tickets targeted at 2.4.0 can be found at:
> https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0
>
> 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.



--
Marcelo

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Re: [VOTE] SPARK 2.4.0 (RC5)

rxin
In reply to this post by cloud0fan
+1

Look forward to the release!



On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Chitral Verma
+1

On Wed, 31 Oct 2018 at 11:56, Reynold Xin <[hidden email]> wrote:
+1

Look forward to the release!



On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Denny Lee
+1

On Wed, Oct 31, 2018 at 12:54 PM Chitral Verma <[hidden email]> wrote:
+1

On Wed, 31 Oct 2018 at 11:56, Reynold Xin <[hidden email]> wrote:
+1

Look forward to the release!



On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Felix Cheung
+1
Checked R doc and all R API changes

 

From: Denny Lee <[hidden email]>
Sent: Wednesday, October 31, 2018 9:13 PM
To: Chitral Verma
Cc: Wenchen Fan; [hidden email]
Subject: Re: [VOTE] SPARK 2.4.0 (RC5)
 
+1

On Wed, Oct 31, 2018 at 12:54 PM Chitral Verma <[hidden email]> wrote:
+1

On Wed, 31 Oct 2018 at 11:56, Reynold Xin <[hidden email]> wrote:
+1

Look forward to the release!



On Mon, Oct 29, 2018 at 3:22 AM Wenchen Fan <[hidden email]> wrote:
Please vote on releasing the following candidate as Apache Spark version 2.4.0.

The vote is open until November 1 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 2.4.0
[ ] -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 v2.4.0-rc5 (commit 0a4c03f7d084f1d2aa48673b99f3b9496893ce8d):

The release files, including signatures, digests, etc. can be found at:

Signatures used for Spark RCs can be found in this file:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:

The list of bug fixes going into 2.4.0 can be found at the following URL:

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 2.4.0?
===========================================

The current list of open tickets targeted at 2.4.0 can be found at:
https://issues.apache.org/jira/projects/SPARK and search for "Target Version/s" = 2.4.0

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.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Dongjoon Hyun-2
+1

Cheers,
Dongjoon.
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Re: [VOTE] SPARK 2.4.0 (RC5)

cloud0fan
This vote passes! I'll follow up with a formal release announcement soon.

+1:
Xiao Li (binding)
Sean Owen (binding)
Gengliang Wang
Hyukjin Kwon
Wenchen Fan (binding)
Ryan Blue
Bryan Cutler
Marcelo Vanzin (binding)
Reynold Xin (binding)
Chitral Verma
Dilip Biswal
Denny Lee
Felix Cheung (binding)
Dongjoon Hyun

+0:
DB Tsai (binding)

-1: None

Thanks, everyone!

On Thu, Nov 1, 2018 at 1:26 PM Dongjoon Hyun <[hidden email]> wrote:
+1

Cheers,
Dongjoon.
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Re: [VOTE] SPARK 2.4.0 (RC5)

Xiangrui Meng-2
Just FYI, not to block the release. We found an issue with PySpark barrier execution mode: https://issues.apache.org/jira/browse/SPARK-25921. We should list it as a known issues in the release notes and get it fixed in 2.4.1. -Xiangrui

On Thu, Nov 1, 2018 at 12:19 AM Wenchen Fan <[hidden email]> wrote:
This vote passes! I'll follow up with a formal release announcement soon.

+1:
Xiao Li (binding)
Sean Owen (binding)
Gengliang Wang
Hyukjin Kwon
Wenchen Fan (binding)
Ryan Blue
Bryan Cutler
Marcelo Vanzin (binding)
Reynold Xin (binding)
Chitral Verma
Dilip Biswal
Denny Lee
Felix Cheung (binding)
Dongjoon Hyun

+0:
DB Tsai (binding)

-1: None

Thanks, everyone!

On Thu, Nov 1, 2018 at 1:26 PM Dongjoon Hyun <[hidden email]> wrote:
+1

Cheers,
Dongjoon.
--

Xiangrui Meng

Software Engineer

Databricks Inc. http://databricks.com

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