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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/08/08 21:58:21 UTC
[jira] [Assigned] (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: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 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$1.apply(RuleExecutor.scala:74)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
> at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:65)
> at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:63)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:582)
> at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:682)
> {code}
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