[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15418817#comment-15418817
]
Wenchen Fan commented on SPARK-16955:
-
this bug is already fixed by https://github.com/apache/spark/pull/14595 by
accident.
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
> at
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15418288#comment-15418288
]
Apache Spark commented on SPARK-16955:
--
User 'clockfly' has created a pull request for this issue:
https://github.com/apache/spark/pull/14616
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15412893#comment-15412893
]
Dongjoon Hyun commented on SPARK-16955:
---
Hi, [~yhuai].
Could you review the PR?
The root cause was `ResolveAggregateFunctions` removed the ordinal sort orders
too early.
After improving the `if` condition to check the resolution is completed, the
case works well.
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15412551#comment-15412551
]
Apache Spark commented on SPARK-16955:
--
User 'dongjoon-hyun' has created a pull request for this issue:
https://github.com/apache/spark/pull/14546
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15412475#comment-15412475
]
Dongjoon Hyun commented on SPARK-16955:
---
`ResolveAggregateFunctions` seems to have a bug to drop the ordinals. I'll make
a PR after some testing.
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15412265#comment-15412265
]
Dongjoon Hyun commented on SPARK-16955:
---
Sure! Thank you, [~yhuai]. I'll take a look this.
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
> at
>
[jira] [Commented] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals
[
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15412263#comment-15412263
]
Yin Huai commented on SPARK-16955:
--
[~dongjoon] Will have time to take a look?
> Using ordinals in ORDER BY causes an analysis error when the query has a
> GROUP BY clause using ordinals
> ---
>
> Key: SPARK-16955
> URL: https://issues.apache.org/jira/browse/SPARK-16955
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0
>Reporter: Yin Huai
>
> The following queries work
> {code}
> select a from (select 1 as a) tmp order by 1
> select a, count(*) from (select 1 as a) tmp group by 1
> select a, count(*) from (select 1 as a) tmp group by 1 order by a
> {code}
> However, the following query does not
> {code}
> select a, count(*) from (select 1 as a) tmp group by 1 order by 1
> {code}
> {code}
> org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to
> Group by position: '1' exceeds the size of the select list '0'. on unresolved
> object, tree:
> Aggregate [1]
> +- SubqueryAlias tmp
>+- Project [1 AS a#82]
> +- OneRowRelation$
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:749)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11$$anonfun$34.apply(Analyzer.scala:739)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:739)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$$anonfun$apply$11.applyOrElse(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:715)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveOrdinalInOrderByAndGroupBy$.apply(Analyzer.scala:714)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1237)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$$anonfun$apply$20.applyOrElse(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveAggregateFunctions$.apply(Analyzer.scala:1181)
> at
>
