Bug: Using value from map in grouping sets result org.apache.spark.sql.AnalysisException
Status: Resolved | Priority: Major | Resolution: Duplicate
Created: 06/Sep/21 05:50
Affects Version/s: 3.1.0

Steps to reproduce：
 # create a table with map
{code:java}
create table test (int_value INT, dims MAP<string, string>) using parquet{code}
 # Run following query:
{code:java}
select int_value, count(1)
from test
group by int_value, dims.dim_x, dims.dim_y
grouping sets ( (int_value, dims.dim_x), (int_value, dims.dim_y)){code}


The call stack:
{noformat}
org.apache.spark.sql.AnalysisException: dims#34[dim_x] AS dim_x#35 doesn't show up in the GROUP BY list ArrayBuffer(int_value#33 AS int_value#41, dims#34[dim_x] AS dim_x#37 AS dim_x#42, dims#34[dim_y] AS dim_y#38 AS dim_y#43);
	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:41)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:92)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19$$anonfun$apply$49$$anonfun$21.apply(Analyzer.scala:387)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19$$anonfun$apply$49$$anonfun$21.apply(Analyzer.scala:387)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19$$anonfun$apply$49.apply(Analyzer.scala:386)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19$$anonfun$apply$49.apply(Analyzer.scala:385)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
	at scala.collection.AbstractTraversable.map(Traversable.scala:104)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19.apply(Analyzer.scala:385)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$19.apply(Analyzer.scala:384)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
	at scala.collection.AbstractTraversable.map(Traversable.scala:104)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$.constructExpand(Analyzer.scala:384)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveGroupingAnalytics$$constructAggregate(Analyzer.scala:448)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$apply$6.applyOrElse(Analyzer.scala:485)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$$anonfun$apply$6.applyOrElse(Analyzer.scala:473)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$.apply(Analyzer.scala:473)
	at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGroupingAnalytics$.apply(Analyzer.scala:287)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:87)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:84)
	at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
	at scala.collection.immutable.List.foldLeft(List.scala:84)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:84)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:76)
	at scala.collection.immutable.List.foreach(List.scala:381)
	at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:124)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:118)
	at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:103)
	at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
	at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
	at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
	at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
	at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:641)
{noformat}