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Posted to issues@spark.apache.org by "Josh Sean (JIRA)" <ji...@apache.org> on 2019/03/13 11:02:00 UTC
[jira] [Updated] (SPARK-27150) Scheduling Within an Application :
Spark SQL randomly failed on UDF
[ https://issues.apache.org/jira/browse/SPARK-27150?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Josh Sean updated SPARK-27150:
------------------------------
Description:
I run this (reduced) following code multiples times under the same exact input files (about 100) :
{code:java}
def myUdf(input : java.lang.String) : Option[Long] = {
None
}
...
val sparkMain = ... .getOrCreate()
val d = inputPaths.toList.par
val p = new scala.concurrent.forkjoin.ForkJoinPool(12)
try {
d.tasksupport = new scala.collection.parallel.ForkJoinTaskSupport(p)
d.foreach {
case (inputPath) => {
val spark = sparkMain.newSession()
spark.udf.register("myUdf",udf(myUdf _))
val df = spark.read.format("csv").option("inferSchema", "false").option("mode", "DROPMALFORMED").schema(mySchema).load(inputPath)
df.createOrReplaceTempView("mytable")
val sql = spark.sql(""" SELECT CAST( myUdf(updated_date) as long) FROM mytable """)
sql.write.parquet( ... )
}
}
}{code}
Once in ten application submit, the driver failed with an Exception related to Spark SQL and the UDF. However, as you can see, I have reduced the UDF to minimum, it's only return None everytime, and the problem still occurs.
The exception is as follow :
{code:java}
Exception in thread "main" java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:65)
at org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
Caused by: org.apache.spark.sql.AnalysisException: cannot resolve 'CAST(UDF(updated_date) AS BIGINT)' due to data type mismatch: cannot cast struct<> to bigint; line 5 pos 10;
...
at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:93)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
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.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:106)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:118)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1$1.apply(QueryPlan.scala:122)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:122)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:127)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:92)
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:74)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:641)
...
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.parallel.ParIterableLike$Foreach.leaf(ParIterableLike.scala:972)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Foreach.tryLeaf(ParIterableLike.scala:969)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:159)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
{code}
Thanks for investigating
was:
I run this (reduced) following code multiples times under the same exact input files (about 100) :
{code:java}
def myUdf(input : java.lang.String) : Option[Long] = {
None
}
...
val sparkMain = ... .getOrCreate()
val d = inputPaths.toList.par
val p = new scala.concurrent.forkjoin.ForkJoinPool(12)
try {
d.tasksupport = new scala.collection.parallel.ForkJoinTaskSupport(p)
d.foreach {
case (inputPath) => {
val spark = sparkMain.newSession()
spark.udf.register("myUdf",udf(myUdf _)) val df = spark.read
.format("csv") .option("inferSchema", "false")
.option("mode", "DROPMALFORMED")
.schema(mySchema)
.load(inputPath)
df.createOrReplaceTempView("mytable")
val sql = spark.sql(""" SELECT CAST( myUdf(updated_date) as long) FROM mytable """)
sql
.write
.parquet( ... )
}
}
}{code}
Once in ten application submit, the driver failed with an Exception related to Spark SQL and the UDF. However, as you can see, I have reduced the UDF to minimum, it's only return None everytime, and the problem still occurs.
The exception is that :
{code:java}
Exception in thread "main" java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:65)
at org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
Caused by: org.apache.spark.sql.AnalysisException: cannot resolve 'CAST(UDF(updated_date) AS BIGINT)' due to data type mismatch: cannot cast struct<> to bigint; line 5 pos 10;
...
at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:93)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:106)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:118)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1$1.apply(QueryPlan.scala:122)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:122)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:127)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:92)
at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:105)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:641)
...
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.parallel.ParIterableLike$Foreach.leaf(ParIterableLike.scala:972)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Foreach.tryLeaf(ParIterableLike.scala:969)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:159)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
{code}
Thanks for investigating
> Scheduling Within an Application : Spark SQL randomly failed on UDF
> -------------------------------------------------------------------
>
> Key: SPARK-27150
> URL: https://issues.apache.org/jira/browse/SPARK-27150
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 2.3.1
> Reporter: Josh Sean
> Priority: Major
>
>
> I run this (reduced) following code multiples times under the same exact input files (about 100) :
>
>
> {code:java}
> def myUdf(input : java.lang.String) : Option[Long] = {
> None
> }
> ...
> val sparkMain = ... .getOrCreate()
> val d = inputPaths.toList.par
> val p = new scala.concurrent.forkjoin.ForkJoinPool(12)
> try {
> d.tasksupport = new scala.collection.parallel.ForkJoinTaskSupport(p)
> d.foreach {
> case (inputPath) => {
> val spark = sparkMain.newSession()
>
> spark.udf.register("myUdf",udf(myUdf _))
> val df = spark.read.format("csv").option("inferSchema", "false").option("mode", "DROPMALFORMED").schema(mySchema).load(inputPath)
> df.createOrReplaceTempView("mytable")
> val sql = spark.sql(""" SELECT CAST( myUdf(updated_date) as long) FROM mytable """)
> sql.write.parquet( ... )
> }
> }
> }{code}
> Once in ten application submit, the driver failed with an Exception related to Spark SQL and the UDF. However, as you can see, I have reduced the UDF to minimum, it's only return None everytime, and the problem still occurs.
> The exception is as follow :
> {code:java}
> Exception in thread "main" java.lang.reflect.InvocationTargetException
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:65)
> at org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
> Caused by: org.apache.spark.sql.AnalysisException: cannot resolve 'CAST(UDF(updated_date) AS BIGINT)' due to data type mismatch: cannot cast struct<> to bigint; line 5 pos 10;
> ...
> at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:93)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
> 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.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:107)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:106)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:118)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1$1.apply(QueryPlan.scala:122)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.immutable.List.map(List.scala:285)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:122)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:127)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:127)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:95)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:92)
> 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:74)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:641)
> ...
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at scala.collection.parallel.ParIterableLike$Foreach.leaf(ParIterableLike.scala:972)
> at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
> at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
> at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
> at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
> at scala.collection.parallel.ParIterableLike$Foreach.tryLeaf(ParIterableLike.scala:969)
> at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:159)
> at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
> at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
> at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
> at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {code}
> Thanks for investigating
>
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