[jira] [Assigned] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals

2016-08-08 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-16955:


Assignee: (was: Apache Spark)

> 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] [Assigned] (SPARK-16955) Using ordinals in ORDER BY causes an analysis error when the query has a GROUP BY clause using ordinals

2016-08-08 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-16955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-16955:


Assignee: Apache Spark

> 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
>Assignee: Apache Spark
>
> 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 
>