Michel Lemay created SPARK-13493:
------------------------------------
Summary: json to DataFrame to parquet does not respect case
sensitiveness
Key: SPARK-13493
URL: https://issues.apache.org/jira/browse/SPARK-13493
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.6.0
Reporter: Michel Lemay
Priority: Minor
Not sure where the problem should be fixed exactly but here it is:
$ spark-shell --conf spark.sql.caseSensitive=false
scala> sqlContext.getConf("spark.sql.caseSensitive")
res2: String = false
scala> val data = List("""{"field": 1}""","""{"field": 2}""","""{"field":
3}""","""{"field": 4}""","""{"FIELD": 5}""")
scala> val jsonDF = sqlContext.read.json(sc.parallelize(data))
scala> jsonDF.printSchema
root
|-- FIELD: long (nullable = true)
|-- field: long (nullable = true)
And when persisting this as parquet:
scala> jsonDF.write.parquet("out")
org.apache.spark.sql.AnalysisException: Reference 'FIELD' is ambiguous, could
be: FIELD#0L, FIELD#1L.;
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolve(LogicalPlan.scala:287)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:171)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$4$$anonfun$26.apply(Analyzer.scala:471
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$4$$anonfun$26.apply(Analyzer.scala:471
at
org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$4.applyOrElse(Analyzer.scala:471)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$4.applyOrElse(Analyzer.scala:467)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:319)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:319)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:53)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:318)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp$1(QueryPlan.scala:107)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:117)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2$1.apply(QueryPlan.sc
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.immutable.List.foreach(List.scala:318)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:121)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:125)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at
scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:125)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10.applyOrElse(Analyzer.scala:467)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10.applyOrElse(Analyzer.scala:347)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:57)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:57)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:53)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:56)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:347)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:328)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
at
scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
at scala.collection.immutable.List.foreach(List.scala:318)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
at
org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:36)
at
org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:36)
at
org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:52)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:106)
at
org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
at
org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
at
org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
at
org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:256)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
at
org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:329)
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
