Yin Huai created SPARK-16955:
--------------------------------
Summary: 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
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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