[jira] [Commented] (SPARK-33106) Fix sbt resolvers clash
[
https://issues.apache.org/jira/browse/SPARK-33106?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266706#comment-17266706
]
Alexander Bessonov commented on SPARK-33106:
My bad. I had the following in my environment that caused the issue. Builds
fine without it.
{code:java}
SBT_OPTS="-Dsbt.override.build.repos=true"{code}
> Fix sbt resolvers clash
> ---
>
> Key: SPARK-33106
> URL: https://issues.apache.org/jira/browse/SPARK-33106
> Project: Spark
> Issue Type: Improvement
> Components: Build
>Affects Versions: 3.1.0
>Reporter: Denis Pyshev
>Assignee: Denis Pyshev
>Priority: Minor
> Fix For: 3.1.0
>
>
> During sbt upgrade from 0.13 to 1.x, exact resolvers list was used as is.
> That leads to local resolvers name clashing, which is observed as warning
> from SBT:
> {code:java}
> [warn] Multiple resolvers having different access mechanism configured with
> same name 'local'. To avoid conflict, Remove duplicate project resolvers
> (`resolvers`) or rename publishing resolve
> r (`publishTo`).
> {code}
> This needs to be fixed to avoid potential errors and reduce log noise.
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[jira] [Commented] (SPARK-34142) Support Fallback Storage Cleanup during stopping SparkContext
[ https://issues.apache.org/jira/browse/SPARK-34142?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266704#comment-17266704 ] Apache Spark commented on SPARK-34142: -- User 'dongjoon-hyun' has created a pull request for this issue: https://github.com/apache/spark/pull/31215 > Support Fallback Storage Cleanup during stopping SparkContext > - > > Key: SPARK-34142 > URL: https://issues.apache.org/jira/browse/SPARK-34142 > Project: Spark > Issue Type: New Feature > Components: Spark Core >Affects Versions: 3.2.0 >Reporter: Dongjoon Hyun >Priority: Major > > SPARK-33545 added `Support Fallback Storage during worker decommission` for > the managed cloud-storage with TTL support. This issue aims to add additional > clean-up feature during stopping SparkContext to save some money before TTL > or the other HDFS-compatible storage which doesn't have TTL support. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34142) Support Fallback Storage Cleanup during stopping SparkContext
[ https://issues.apache.org/jira/browse/SPARK-34142?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34142: Assignee: Apache Spark > Support Fallback Storage Cleanup during stopping SparkContext > - > > Key: SPARK-34142 > URL: https://issues.apache.org/jira/browse/SPARK-34142 > Project: Spark > Issue Type: New Feature > Components: Spark Core >Affects Versions: 3.2.0 >Reporter: Dongjoon Hyun >Assignee: Apache Spark >Priority: Major > > SPARK-33545 added `Support Fallback Storage during worker decommission` for > the managed cloud-storage with TTL support. This issue aims to add additional > clean-up feature during stopping SparkContext to save some money before TTL > or the other HDFS-compatible storage which doesn't have TTL support. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34142) Support Fallback Storage Cleanup during stopping SparkContext
[ https://issues.apache.org/jira/browse/SPARK-34142?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266703#comment-17266703 ] Apache Spark commented on SPARK-34142: -- User 'dongjoon-hyun' has created a pull request for this issue: https://github.com/apache/spark/pull/31215 > Support Fallback Storage Cleanup during stopping SparkContext > - > > Key: SPARK-34142 > URL: https://issues.apache.org/jira/browse/SPARK-34142 > Project: Spark > Issue Type: New Feature > Components: Spark Core >Affects Versions: 3.2.0 >Reporter: Dongjoon Hyun >Priority: Major > > SPARK-33545 added `Support Fallback Storage during worker decommission` for > the managed cloud-storage with TTL support. This issue aims to add additional > clean-up feature during stopping SparkContext to save some money before TTL > or the other HDFS-compatible storage which doesn't have TTL support. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34142) Support Fallback Storage Cleanup during stopping SparkContext
[ https://issues.apache.org/jira/browse/SPARK-34142?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34142: Assignee: (was: Apache Spark) > Support Fallback Storage Cleanup during stopping SparkContext > - > > Key: SPARK-34142 > URL: https://issues.apache.org/jira/browse/SPARK-34142 > Project: Spark > Issue Type: New Feature > Components: Spark Core >Affects Versions: 3.2.0 >Reporter: Dongjoon Hyun >Priority: Major > > SPARK-33545 added `Support Fallback Storage during worker decommission` for > the managed cloud-storage with TTL support. This issue aims to add additional > clean-up feature during stopping SparkContext to save some money before TTL > or the other HDFS-compatible storage which doesn't have TTL support. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-34142) Support Fallback Storage Cleanup during stopping SparkContext
Dongjoon Hyun created SPARK-34142: - Summary: Support Fallback Storage Cleanup during stopping SparkContext Key: SPARK-34142 URL: https://issues.apache.org/jira/browse/SPARK-34142 Project: Spark Issue Type: New Feature Components: Spark Core Affects Versions: 3.2.0 Reporter: Dongjoon Hyun SPARK-33545 added `Support Fallback Storage during worker decommission` for the managed cloud-storage with TTL support. This issue aims to add additional clean-up feature during stopping SparkContext to save some money before TTL or the other HDFS-compatible storage which doesn't have TTL support. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34111) Deconflict the jars jakarta.servlet-api-4.0.3.jar and javax.servlet-api-3.1.0.jar
[
https://issues.apache.org/jira/browse/SPARK-34111?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266702#comment-17266702
]
Apache Spark commented on SPARK-34111:
--
User 'yaooqinn' has created a pull request for this issue:
https://github.com/apache/spark/pull/31214
> Deconflict the jars jakarta.servlet-api-4.0.3.jar and
> javax.servlet-api-3.1.0.jar
> -
>
> Key: SPARK-34111
> URL: https://issues.apache.org/jira/browse/SPARK-34111
> Project: Spark
> Issue Type: Bug
> Components: Build
>Affects Versions: 3.1.0
>Reporter: Hyukjin Kwon
>Priority: Blocker
>
> After SPARK-33705, we now happened to have two jars in the release artifact
> with Hadoop 3:
> {{dev/deps/spark-deps-hadoop-3.2-hive-2.3}}:
> {code}
> ...
> jakarta.servlet-api/4.0.3//jakarta.servlet-api-4.0.3.jar
> ...
> javax.servlet-api/3.1.0//javax.servlet-api-3.1.0.jar
> ...
> {code}
> It can potentially cause an issue, and we should better remove
> {{javax.servlet-api-3.1.0.jar}} which is apparently only required for YARN
> tests.
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[jira] [Commented] (SPARK-34111) Deconflict the jars jakarta.servlet-api-4.0.3.jar and javax.servlet-api-3.1.0.jar
[
https://issues.apache.org/jira/browse/SPARK-34111?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266701#comment-17266701
]
Apache Spark commented on SPARK-34111:
--
User 'yaooqinn' has created a pull request for this issue:
https://github.com/apache/spark/pull/31214
> Deconflict the jars jakarta.servlet-api-4.0.3.jar and
> javax.servlet-api-3.1.0.jar
> -
>
> Key: SPARK-34111
> URL: https://issues.apache.org/jira/browse/SPARK-34111
> Project: Spark
> Issue Type: Bug
> Components: Build
>Affects Versions: 3.1.0
>Reporter: Hyukjin Kwon
>Priority: Blocker
>
> After SPARK-33705, we now happened to have two jars in the release artifact
> with Hadoop 3:
> {{dev/deps/spark-deps-hadoop-3.2-hive-2.3}}:
> {code}
> ...
> jakarta.servlet-api/4.0.3//jakarta.servlet-api-4.0.3.jar
> ...
> javax.servlet-api/3.1.0//javax.servlet-api-3.1.0.jar
> ...
> {code}
> It can potentially cause an issue, and we should better remove
> {{javax.servlet-api-3.1.0.jar}} which is apparently only required for YARN
> tests.
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[jira] [Commented] (SPARK-34141) ExtractGenerator analyzer should handle lazy projectlists
[ https://issues.apache.org/jira/browse/SPARK-34141?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266683#comment-17266683 ] Apache Spark commented on SPARK-34141: -- User 'tanelk' has created a pull request for this issue: https://github.com/apache/spark/pull/31213 > ExtractGenerator analyzer should handle lazy projectlists > - > > Key: SPARK-34141 > URL: https://issues.apache.org/jira/browse/SPARK-34141 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.2.0 >Reporter: Tanel Kiis >Priority: Major > > With the dataframe api it is possible to have a lazy sequence as the output > field on a LogicalPlan class. When exploding a column on this dataframe using > the withColumn method, the ExtractGenerator does not extract the generator. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34141) ExtractGenerator analyzer should handle lazy projectlists
[ https://issues.apache.org/jira/browse/SPARK-34141?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266682#comment-17266682 ] Apache Spark commented on SPARK-34141: -- User 'tanelk' has created a pull request for this issue: https://github.com/apache/spark/pull/31213 > ExtractGenerator analyzer should handle lazy projectlists > - > > Key: SPARK-34141 > URL: https://issues.apache.org/jira/browse/SPARK-34141 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.2.0 >Reporter: Tanel Kiis >Priority: Major > > With the dataframe api it is possible to have a lazy sequence as the output > field on a LogicalPlan class. When exploding a column on this dataframe using > the withColumn method, the ExtractGenerator does not extract the generator. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34141) ExtractGenerator analyzer should handle lazy projectlists
[ https://issues.apache.org/jira/browse/SPARK-34141?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34141: Assignee: Apache Spark > ExtractGenerator analyzer should handle lazy projectlists > - > > Key: SPARK-34141 > URL: https://issues.apache.org/jira/browse/SPARK-34141 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.2.0 >Reporter: Tanel Kiis >Assignee: Apache Spark >Priority: Major > > With the dataframe api it is possible to have a lazy sequence as the output > field on a LogicalPlan class. When exploding a column on this dataframe using > the withColumn method, the ExtractGenerator does not extract the generator. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34141) ExtractGenerator analyzer should handle lazy projectlists
[ https://issues.apache.org/jira/browse/SPARK-34141?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34141: Assignee: (was: Apache Spark) > ExtractGenerator analyzer should handle lazy projectlists > - > > Key: SPARK-34141 > URL: https://issues.apache.org/jira/browse/SPARK-34141 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.2.0 >Reporter: Tanel Kiis >Priority: Major > > With the dataframe api it is possible to have a lazy sequence as the output > field on a LogicalPlan class. When exploding a column on this dataframe using > the withColumn method, the ExtractGenerator does not extract the generator. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-34141) ExtractGenerator analyzer should handle lazy projectlists
Tanel Kiis created SPARK-34141: -- Summary: ExtractGenerator analyzer should handle lazy projectlists Key: SPARK-34141 URL: https://issues.apache.org/jira/browse/SPARK-34141 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 3.2.0 Reporter: Tanel Kiis With the dataframe api it is possible to have a lazy sequence as the output field on a LogicalPlan class. When exploding a column on this dataframe using the withColumn method, the ExtractGenerator does not extract the generator. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors
[ https://issues.apache.org/jira/browse/SPARK-34140?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266672#comment-17266672 ] Apache Spark commented on SPARK-34140: -- User 'imback82' has created a pull request for this issue: https://github.com/apache/spark/pull/31212 > Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to > org/apache/spark/sql/errors > --- > > Key: SPARK-34140 > URL: https://issues.apache.org/jira/browse/SPARK-34140 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 3.2.0 >Reporter: Terry Kim >Priority: Minor > > QueryCompilationErrors.scala and QueryExecutionErrors.scala use the > org.apache.spark.sql.errors package, but these files are reside in > org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors
[ https://issues.apache.org/jira/browse/SPARK-34140?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266658#comment-17266658 ] Apache Spark commented on SPARK-34140: -- User 'imback82' has created a pull request for this issue: https://github.com/apache/spark/pull/31211 > Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to > org/apache/spark/sql/errors > --- > > Key: SPARK-34140 > URL: https://issues.apache.org/jira/browse/SPARK-34140 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 3.2.0 >Reporter: Terry Kim >Priority: Minor > > QueryCompilationErrors.scala and QueryExecutionErrors.scala use the > org.apache.spark.sql.errors package, but these files are reside in > org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors
[ https://issues.apache.org/jira/browse/SPARK-34140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34140: Assignee: Apache Spark > Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to > org/apache/spark/sql/errors > --- > > Key: SPARK-34140 > URL: https://issues.apache.org/jira/browse/SPARK-34140 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 3.2.0 >Reporter: Terry Kim >Assignee: Apache Spark >Priority: Minor > > QueryCompilationErrors.scala and QueryExecutionErrors.scala use the > org.apache.spark.sql.errors package, but these files are reside in > org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors
[ https://issues.apache.org/jira/browse/SPARK-34140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34140: Assignee: (was: Apache Spark) > Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to > org/apache/spark/sql/errors > --- > > Key: SPARK-34140 > URL: https://issues.apache.org/jira/browse/SPARK-34140 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 3.2.0 >Reporter: Terry Kim >Priority: Minor > > QueryCompilationErrors.scala and QueryExecutionErrors.scala use the > org.apache.spark.sql.errors package, but these files are reside in > org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors
[ https://issues.apache.org/jira/browse/SPARK-34140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Terry Kim updated SPARK-34140: -- Summary: Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to org/apache/spark/sql/errors (was: Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to Create org/apache/spark/sql/errors) > Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to > org/apache/spark/sql/errors > --- > > Key: SPARK-34140 > URL: https://issues.apache.org/jira/browse/SPARK-34140 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 3.2.0 >Reporter: Terry Kim >Priority: Minor > > QueryCompilationErrors.scala and QueryExecutionErrors.scala use the > org.apache.spark.sql.errors package, but these files are reside in > org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-34140) Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to Create org/apache/spark/sql/errors
Terry Kim created SPARK-34140: - Summary: Move QueryCompilationErrors.scala and QueryExecutionErrors.scala to Create org/apache/spark/sql/errors Key: SPARK-34140 URL: https://issues.apache.org/jira/browse/SPARK-34140 Project: Spark Issue Type: Improvement Components: SQL Affects Versions: 3.2.0 Reporter: Terry Kim QueryCompilationErrors.scala and QueryExecutionErrors.scala use the org.apache.spark.sql.errors package, but these files are reside in org/apache/spark/sql directory. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34139) UnresolvedRelation should retain SQL text position
[
https://issues.apache.org/jira/browse/SPARK-34139?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266650#comment-17266650
]
Apache Spark commented on SPARK-34139:
--
User 'imback82' has created a pull request for this issue:
https://github.com/apache/spark/pull/31209
> UnresolvedRelation should retain SQL text position
> --
>
> Key: SPARK-34139
> URL: https://issues.apache.org/jira/browse/SPARK-34139
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.2.0
>Reporter: Terry Kim
>Priority: Major
>
> UnresolvedRelation should retain SQL text position. The following commands
> will be handled:
> {code:java}
> CACHE TABLE unknown
> UNCACHE TABLE unknown
> DELETE FROM unknown
> UPDATE unknown SET name='abc'
> MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col =
> source.col WHEN MATCHED THEN DELETE
> INSERT INTO TABLE unknown SELECT 1
> INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
> {code}
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[jira] [Assigned] (SPARK-34139) UnresolvedRelation should retain SQL text position
[
https://issues.apache.org/jira/browse/SPARK-34139?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-34139:
Assignee: (was: Apache Spark)
> UnresolvedRelation should retain SQL text position
> --
>
> Key: SPARK-34139
> URL: https://issues.apache.org/jira/browse/SPARK-34139
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.2.0
>Reporter: Terry Kim
>Priority: Major
>
> UnresolvedRelation should retain SQL text position. The following commands
> will be handled:
> {code:java}
> CACHE TABLE unknown
> UNCACHE TABLE unknown
> DELETE FROM unknown
> UPDATE unknown SET name='abc'
> MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col =
> source.col WHEN MATCHED THEN DELETE
> INSERT INTO TABLE unknown SELECT 1
> INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
> {code}
--
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[jira] [Assigned] (SPARK-34139) UnresolvedRelation should retain SQL text position
[
https://issues.apache.org/jira/browse/SPARK-34139?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-34139:
Assignee: Apache Spark
> UnresolvedRelation should retain SQL text position
> --
>
> Key: SPARK-34139
> URL: https://issues.apache.org/jira/browse/SPARK-34139
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.2.0
>Reporter: Terry Kim
>Assignee: Apache Spark
>Priority: Major
>
> UnresolvedRelation should retain SQL text position. The following commands
> will be handled:
> {code:java}
> CACHE TABLE unknown
> UNCACHE TABLE unknown
> DELETE FROM unknown
> UPDATE unknown SET name='abc'
> MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col =
> source.col WHEN MATCHED THEN DELETE
> INSERT INTO TABLE unknown SELECT 1
> INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
> {code}
--
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[jira] [Commented] (SPARK-34139) UnresolvedRelation should retain SQL text position
[
https://issues.apache.org/jira/browse/SPARK-34139?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266649#comment-17266649
]
Apache Spark commented on SPARK-34139:
--
User 'imback82' has created a pull request for this issue:
https://github.com/apache/spark/pull/31209
> UnresolvedRelation should retain SQL text position
> --
>
> Key: SPARK-34139
> URL: https://issues.apache.org/jira/browse/SPARK-34139
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.2.0
>Reporter: Terry Kim
>Priority: Major
>
> UnresolvedRelation should retain SQL text position. The following commands
> will be handled:
> {code:java}
> CACHE TABLE unknown
> UNCACHE TABLE unknown
> DELETE FROM unknown
> UPDATE unknown SET name='abc'
> MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col =
> source.col WHEN MATCHED THEN DELETE
> INSERT INTO TABLE unknown SELECT 1
> INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
> {code}
--
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[jira] [Created] (SPARK-34139) UnresolvedRelation should retain SQL text position
Terry Kim created SPARK-34139:
-
Summary: UnresolvedRelation should retain SQL text position
Key: SPARK-34139
URL: https://issues.apache.org/jira/browse/SPARK-34139
Project: Spark
Issue Type: Sub-task
Components: SQL
Affects Versions: 3.2.0
Reporter: Terry Kim
UnresolvedRelation should retain SQL text position. The following commands will
be handled:
{code:java}
CACHE TABLE unknown
UNCACHE TABLE unknown
DELETE FROM unknown
UPDATE unknown SET name='abc'
MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col =
source.col WHEN MATCHED THEN DELETE
INSERT INTO TABLE unknown SELECT 1
INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
{code}
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[jira] [Commented] (SPARK-34138) Keep dependants cached while refreshing v1 tables
[ https://issues.apache.org/jira/browse/SPARK-34138?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266611#comment-17266611 ] Apache Spark commented on SPARK-34138: -- User 'MaxGekk' has created a pull request for this issue: https://github.com/apache/spark/pull/31206 > Keep dependants cached while refreshing v1 tables > - > > Key: SPARK-34138 > URL: https://issues.apache.org/jira/browse/SPARK-34138 > Project: Spark > Issue Type: Sub-task > Components: SQL >Affects Versions: 3.2.0 >Reporter: Maxim Gekk >Priority: Major > > Keeping dependants cached while refreshing v1 tables should allow to improve > user experience with table/view caching. For example, let's imagine that an > user has cached v1 table and cached view based on the table. And the user > passed the table to external library which drops/renames/adds partitions in > the v1 table. Unfortunately, the user gets the view uncached after that even > he/she hasn't uncached the view explicitly. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-34138) Keep dependants cached while refreshing v1 tables
[ https://issues.apache.org/jira/browse/SPARK-34138?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-34138: Assignee: (was: Apache Spark) > Keep dependants cached while refreshing v1 tables > - > > Key: SPARK-34138 > URL: https://issues.apache.org/jira/browse/SPARK-34138 > Project: Spark > Issue Type: Sub-task > Components: SQL >Affects Versions: 3.2.0 >Reporter: Maxim Gekk >Priority: Major > > Keeping dependants cached while refreshing v1 tables should allow to improve > user experience with table/view caching. For example, let's imagine that an > user has cached v1 table and cached view based on the table. And the user > passed the table to external library which drops/renames/adds partitions in > the v1 table. Unfortunately, the user gets the view uncached after that even > he/she hasn't uncached the view explicitly. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-34138) Keep dependants cached while refreshing v1 tables
Maxim Gekk created SPARK-34138: -- Summary: Keep dependants cached while refreshing v1 tables Key: SPARK-34138 URL: https://issues.apache.org/jira/browse/SPARK-34138 Project: Spark Issue Type: Sub-task Components: SQL Affects Versions: 3.2.0 Reporter: Maxim Gekk Keeping dependants cached while refreshing v1 tables should allow to improve user experience with table/view caching. For example, let's imagine that an user has cached v1 table and cached view based on the table. And the user passed the table to external library which drops/renames/adds partitions in the v1 table. Unfortunately, the user gets the view uncached after that even he/she hasn't uncached the view explicitly. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34137) The tree string does not contain statistics for nested scalar sub queries
[
https://issues.apache.org/jira/browse/SPARK-34137?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266610#comment-17266610
]
Yuming Wang commented on SPARK-34137:
-
cc [~maxgekk]
> The tree string does not contain statistics for nested scalar sub queries
> -
>
> Key: SPARK-34137
> URL: https://issues.apache.org/jira/browse/SPARK-34137
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.2.0
>Reporter: Yuming Wang
>Priority: Major
>
> How to reproduce:
> {code:scala}
> spark.sql("create table t1 using parquet as select id as a, id as b from
> range(1000)")
> spark.sql("create table t2 using parquet as select id as c, id as d from
> range(2000)")
> spark.sql("ANALYZE TABLE t1 COMPUTE STATISTICS FOR ALL COLUMNS")
> spark.sql("ANALYZE TABLE t2 COMPUTE STATISTICS FOR ALL COLUMNS")
> spark.sql("set spark.sql.cbo.enabled=true")
> spark.sql(
> """
> |WITH max_store_sales AS
> | (SELECT max(csales) tpcds_cmax
> | FROM (SELECT
> |sum(b) csales
> | FROM t1 WHERE a < 100 ) x),
> |best_ss_customer AS
> | (SELECT
> |c
> | FROM t2
> | WHERE d > (SELECT * FROM max_store_sales))
> |
> |SELECT c FROM best_ss_customer
> |""".stripMargin).explain("cost")
> {code}
> Output:
> {noformat}
> == Optimized Logical Plan ==
> Project [c#4263L], Statistics(sizeInBytes=31.3 KiB, rowCount=2.00E+3)
> +- Filter (isnotnull(d#4264L) AND (d#4264L > scalar-subquery#4262 [])),
> Statistics(sizeInBytes=46.9 KiB, rowCount=2.00E+3)
>: +- Aggregate [max(csales#4260L) AS tpcds_cmax#4261L]
>: +- Aggregate [sum(b#4266L) AS csales#4260L]
>:+- Project [b#4266L]
>: +- Filter ((a#4265L < 100) AND isnotnull(a#4265L))
>: +- Relation default.t1[a#4265L,b#4266L] parquet,
> Statistics(sizeInBytes=23.4 KiB, rowCount=1.00E+3)
>+- Relation default.t2[c#4263L,d#4264L] parquet,
> Statistics(sizeInBytes=46.9 KiB, rowCount=2.00E+3)
> {noformat}
> Another case is TPC-DS q23a.
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[jira] [Created] (SPARK-34137) The tree string does not contain statistics for nested scalar sub queries
Yuming Wang created SPARK-34137:
---
Summary: The tree string does not contain statistics for nested
scalar sub queries
Key: SPARK-34137
URL: https://issues.apache.org/jira/browse/SPARK-34137
Project: Spark
Issue Type: Sub-task
Components: SQL
Affects Versions: 3.2.0
Reporter: Yuming Wang
How to reproduce:
{code:scala}
spark.sql("create table t1 using parquet as select id as a, id as b from
range(1000)")
spark.sql("create table t2 using parquet as select id as c, id as d from
range(2000)")
spark.sql("ANALYZE TABLE t1 COMPUTE STATISTICS FOR ALL COLUMNS")
spark.sql("ANALYZE TABLE t2 COMPUTE STATISTICS FOR ALL COLUMNS")
spark.sql("set spark.sql.cbo.enabled=true")
spark.sql(
"""
|WITH max_store_sales AS
| (SELECT max(csales) tpcds_cmax
| FROM (SELECT
|sum(b) csales
| FROM t1 WHERE a < 100 ) x),
|best_ss_customer AS
| (SELECT
|c
| FROM t2
| WHERE d > (SELECT * FROM max_store_sales))
|
|SELECT c FROM best_ss_customer
|""".stripMargin).explain("cost")
{code}
Output:
{noformat}
== Optimized Logical Plan ==
Project [c#4263L], Statistics(sizeInBytes=31.3 KiB, rowCount=2.00E+3)
+- Filter (isnotnull(d#4264L) AND (d#4264L > scalar-subquery#4262 [])),
Statistics(sizeInBytes=46.9 KiB, rowCount=2.00E+3)
: +- Aggregate [max(csales#4260L) AS tpcds_cmax#4261L]
: +- Aggregate [sum(b#4266L) AS csales#4260L]
:+- Project [b#4266L]
: +- Filter ((a#4265L < 100) AND isnotnull(a#4265L))
: +- Relation default.t1[a#4265L,b#4266L] parquet,
Statistics(sizeInBytes=23.4 KiB, rowCount=1.00E+3)
+- Relation default.t2[c#4263L,d#4264L] parquet, Statistics(sizeInBytes=46.9
KiB, rowCount=2.00E+3)
{noformat}
Another case is TPC-DS q23a.
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[jira] [Assigned] (SPARK-34136) Support complex types in pyspark.sql.functions.lit
[
https://issues.apache.org/jira/browse/SPARK-34136?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-34136:
Assignee: (was: Apache Spark)
> Support complex types in pyspark.sql.functions.lit
> --
>
> Key: SPARK-34136
> URL: https://issues.apache.org/jira/browse/SPARK-34136
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
>Affects Versions: 3.2.0, 3.1.1
>Reporter: Maciej Szymkiewicz
>Priority: Major
>
> At the moment, Python users have to use dedicated function to create complex
> literal column. For example to create an array:
> {code:python}
> from pyspark.sql.functions import array, lit
> xs = [1, 2, 3]
> array(*[lit(x) for x in xs])
> {code}
> or map
> {code:python}
> from pyspark.sql.functions import create_map, lit, map_from_arrays
> from itertools import chain
> kvs = {"a": 1, "b": 2}
> create_map(*chain.from_iterable(
> (lit(k), lit(v)) for k, v in kvs.items()
> ))
> # or
> map_from_arrays(
> array(*[lit(k) for k in kvs.keys()]),
> array(*[lit(v) for v in kvs.values()])
> )
> {code}
> This is very verbose for such simple task.
> In Scala we have `typedLit` that addresses such cases
> {code:scala}
> scala> typedLit(Map("a" -> 1, "b" -> 2))
> res0: org.apache.spark.sql.Column = keys: [a,b], values: [1,2]
> scala> typedLit(Array(1, 2, 3))
> res1: org.apache.spark.sql.Column = [1,2,3]
> {code}
> but its API is not Python-friendly.
> It would be nice if {{lit}} could cover at least basic complex types.
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[jira] [Commented] (SPARK-34136) Support complex types in pyspark.sql.functions.lit
[
https://issues.apache.org/jira/browse/SPARK-34136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266609#comment-17266609
]
Apache Spark commented on SPARK-34136:
--
User 'zero323' has created a pull request for this issue:
https://github.com/apache/spark/pull/31207
> Support complex types in pyspark.sql.functions.lit
> --
>
> Key: SPARK-34136
> URL: https://issues.apache.org/jira/browse/SPARK-34136
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
>Affects Versions: 3.2.0, 3.1.1
>Reporter: Maciej Szymkiewicz
>Priority: Major
>
> At the moment, Python users have to use dedicated function to create complex
> literal column. For example to create an array:
> {code:python}
> from pyspark.sql.functions import array, lit
> xs = [1, 2, 3]
> array(*[lit(x) for x in xs])
> {code}
> or map
> {code:python}
> from pyspark.sql.functions import create_map, lit, map_from_arrays
> from itertools import chain
> kvs = {"a": 1, "b": 2}
> create_map(*chain.from_iterable(
> (lit(k), lit(v)) for k, v in kvs.items()
> ))
> # or
> map_from_arrays(
> array(*[lit(k) for k in kvs.keys()]),
> array(*[lit(v) for v in kvs.values()])
> )
> {code}
> This is very verbose for such simple task.
> In Scala we have `typedLit` that addresses such cases
> {code:scala}
> scala> typedLit(Map("a" -> 1, "b" -> 2))
> res0: org.apache.spark.sql.Column = keys: [a,b], values: [1,2]
> scala> typedLit(Array(1, 2, 3))
> res1: org.apache.spark.sql.Column = [1,2,3]
> {code}
> but its API is not Python-friendly.
> It would be nice if {{lit}} could cover at least basic complex types.
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[jira] [Assigned] (SPARK-34136) Support complex types in pyspark.sql.functions.lit
[
https://issues.apache.org/jira/browse/SPARK-34136?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-34136:
Assignee: Apache Spark
> Support complex types in pyspark.sql.functions.lit
> --
>
> Key: SPARK-34136
> URL: https://issues.apache.org/jira/browse/SPARK-34136
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
>Affects Versions: 3.2.0, 3.1.1
>Reporter: Maciej Szymkiewicz
>Assignee: Apache Spark
>Priority: Major
>
> At the moment, Python users have to use dedicated function to create complex
> literal column. For example to create an array:
> {code:python}
> from pyspark.sql.functions import array, lit
> xs = [1, 2, 3]
> array(*[lit(x) for x in xs])
> {code}
> or map
> {code:python}
> from pyspark.sql.functions import create_map, lit, map_from_arrays
> from itertools import chain
> kvs = {"a": 1, "b": 2}
> create_map(*chain.from_iterable(
> (lit(k), lit(v)) for k, v in kvs.items()
> ))
> # or
> map_from_arrays(
> array(*[lit(k) for k in kvs.keys()]),
> array(*[lit(v) for v in kvs.values()])
> )
> {code}
> This is very verbose for such simple task.
> In Scala we have `typedLit` that addresses such cases
> {code:scala}
> scala> typedLit(Map("a" -> 1, "b" -> 2))
> res0: org.apache.spark.sql.Column = keys: [a,b], values: [1,2]
> scala> typedLit(Array(1, 2, 3))
> res1: org.apache.spark.sql.Column = [1,2,3]
> {code}
> but its API is not Python-friendly.
> It would be nice if {{lit}} could cover at least basic complex types.
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[jira] [Created] (SPARK-34136) Support complex types in pyspark.sql.functions.lit
Maciej Szymkiewicz created SPARK-34136:
--
Summary: Support complex types in pyspark.sql.functions.lit
Key: SPARK-34136
URL: https://issues.apache.org/jira/browse/SPARK-34136
Project: Spark
Issue Type: Improvement
Components: PySpark, SQL
Affects Versions: 3.2.0, 3.1.1
Reporter: Maciej Szymkiewicz
At the moment, Python users have to use dedicated function to create complex
literal column. For example to create an array:
{code:python}
from pyspark.sql.functions import array, lit
xs = [1, 2, 3]
array(*[lit(x) for x in xs])
{code}
or map
{code:python}
from pyspark.sql.functions import create_map, lit, map_from_arrays
from itertools import chain
kvs = {"a": 1, "b": 2}
create_map(*chain.from_iterable(
(lit(k), lit(v)) for k, v in kvs.items()
))
# or
map_from_arrays(
array(*[lit(k) for k in kvs.keys()]),
array(*[lit(v) for v in kvs.values()])
)
{code}
This is very verbose for such simple task.
In Scala we have `typedLit` that addresses such cases
{code:scala}
scala> typedLit(Map("a" -> 1, "b" -> 2))
res0: org.apache.spark.sql.Column = keys: [a,b], values: [1,2]
scala> typedLit(Array(1, 2, 3))
res1: org.apache.spark.sql.Column = [1,2,3]
{code}
but its API is not Python-friendly.
It would be nice if {{lit}} could cover at least basic complex types.
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[jira] [Closed] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Kevin Pis closed SPARK-34135. - it just a test > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: test >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > test -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Kevin Pis resolved SPARK-34135. --- Resolution: Not A Problem it just a test > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: test >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > test -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Kevin Pis updated SPARK-34135: -- Environment: test (was: fsdfdsf) > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: test >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > test -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Kevin Pis updated SPARK-34135: -- Docs Text: test (was: fdsfsdf) > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: fsdfdsf >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > fsfs -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Kevin Pis updated SPARK-34135: -- Description: test (was: fsfs) > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: fsdfdsf >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > test -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-34135) hello world
[ https://issues.apache.org/jira/browse/SPARK-34135?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17266537#comment-17266537 ] Kevin Pis commented on SPARK-34135: --- I just want to test the feature about creating a issue, how can i delete the issue ? > hello world > --- > > Key: SPARK-34135 > URL: https://issues.apache.org/jira/browse/SPARK-34135 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 3.0.1 > Environment: fsdfdsf >Reporter: Kevin Pis >Priority: Major > Fix For: 2.4.8 > > Original Estimate: 504h > Remaining Estimate: 504h > > fsfs -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-34135) hello world
Kevin Pis created SPARK-34135: - Summary: hello world Key: SPARK-34135 URL: https://issues.apache.org/jira/browse/SPARK-34135 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 3.0.1 Environment: fsdfdsf Reporter: Kevin Pis Fix For: 2.4.8 fsfs -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
