[SPARK-28897] Invalid usage of '*' in expression 'coalesce' error when executing dataframe.na.fill(0)

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Duplicate
• Affects Version/s: 2.4.0
• Component/s: Spark Core
• Assignee: Unassigned
• Reporter: Saurabh Santhosh
• Created: 28/Aug/19 10:26
• Updated: 30/Jan/20 10:51
• Resolved: 30/Jan/20 10:47

Description

Getting the following error when trying to execute the given statements

 

var df = spark.sql(s"select * from default.test_table")
df.na.fill(0)

This error happens when the following property is set

spark.sql("set spark.sql.parser.quotedRegexColumnNames=true")

Error :

org.apache.spark.sql.AnalysisException: Invalid usage of '*' in expression 'coalesce';   at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:42)   at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:95)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$expandStarExpression$1.applyOrElse(Analyzer.scala:1021)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$expandStarExpression$1.applyOrElse(Analyzer.scala:997)   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)   at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)   at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:277)   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:275)   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:275)   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326)   at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)   at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324)   at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:275)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.expandStarExpression(Analyzer.scala:997)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveReferences$$buildExpandedProjectList$1.apply(Analyzer.scala:982)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveReferences$$buildExpandedProjectList$1.apply(Analyzer.scala:977)   at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)   at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)   at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)   at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)   at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)   at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveReferences$$buildExpandedProjectList(Analyzer.scala:977)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$9.applyOrElse(Analyzer.scala:905)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$9.applyOrElse(Analyzer.scala:900)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsUp$1$$anonfun$apply$1.apply(AnalysisHelper.scala:90)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsUp$1$$anonfun$apply$1.apply(AnalysisHelper.scala:90)   at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsUp$1.apply(AnalysisHelper.scala:89)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$$anonfun$resolveOperatorsUp$1.apply(AnalysisHelper.scala:86)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:194)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.resolveOperatorsUp(AnalysisHelper.scala:86)   at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUp(LogicalPlan.scala:29)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:900)   at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:758)   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$1.apply(RuleExecutor.scala:76)   at scala.collection.immutable.List.foreach(List.scala:392)   at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)   at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:127)   at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:121)   at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:106)   at org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$executeAndCheck$1.apply(Analyzer.scala:105)   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:201)   at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:105)   at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)   at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)   at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)   at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:79)   at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:3407)   at org.apache.spark.sql.Dataset.select(Dataset.scala:1335)   at org.apache.spark.sql.DataFrameNaFunctions.fillValue(DataFrameNaFunctions.scala:507)

 

Issue Links

• duplicates: SPARK-29890 Unable to fill na with 0 with duplicate columns
• links to: GitHub Pull Request #25628
• links to: GitHub Pull Request #27392