[jira] [Updated] (SPARK-34646) TreeNode bind issue for duplicate column name.
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Description: I received a Spark {{TreeNodeException}} executing a union of two data frames. When I assign the union results to a DataFrame that will be returned by a function, this error occurs. However, I am able to assign the union results to a DataFrame that will not be returned. I have examined the schema for all the data frames participating in the code. The PT_Id is being duplicated. The PT_Id is duplicated and results in the failed search. {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 (TID 5557) org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: PT_ID#140575 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) at scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Caused by: java.lang.RuntimeException: Couldn't find PT_Id#140575 in [Name#34180,PT_Id#34181,PT_Id#127|#34180,PT_Id#34181,PT_Id#127] at
[jira] [Updated] (SPARK-34646) TreeNode bind issue for duplicate column name.
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Description: I received a Spark {{TreeNodeException}} executing a union of two data frames. When I assign the union results to a DataFrame that will be returned by a function, this error occurs. However, I am able to assign the union results to a DataFrame that will not be returned. I have examined schema for all the data frames participating in the code. The PT_Id is being duplicated. The PT_Id is duplicated and results in the failed search. {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 (TID 5557) org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: PT_ID#140575 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) at scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Caused by: java.lang.RuntimeException: Couldn't find PT_Id#140575 in [Name#34180,PT_Id#34181,PT_Id#127|#34180,PT_Id#34181,PT_Id#127] at
[jira] [Updated] (SPARK-34646) TreeNode bind issue for duplicate column name.
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Description: I received a Spark {{TreeNodeException}} executing a union of two data frames. When I assign the union results to a DataFrame that will be returned from by a function, this error occurs. However, I am able to assign the union results to a DataFrame that will not be returned. I have examined schema for all the data frames participating in the code. The PT_Id is being duplicated. The PT_Id is duplicated and results in the failed search. {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 (TID 5557) org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: PT_ID#140575 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) at scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Caused by: java.lang.RuntimeException: Couldn't find PT_Id#140575 in [Name#34180,PT_Id#34181,PT_Id#127|#34180,PT_Id#34181,PT_Id#127] at
[jira] [Updated] (SPARK-34646) TreeNode bind issue for duplicate column name.
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Summary: TreeNode bind issue for duplicate column name. (was: TreeNode bind issue) > TreeNode bind issue for duplicate column name. > -- > > Key: SPARK-34646 > URL: https://issues.apache.org/jira/browse/SPARK-34646 > Project: Spark > Issue Type: Bug > Components: Spark Submit >Affects Versions: 2.4.3 > Environment: Spark 2.4.3, Scala 2.11.8, Hadoop 3.2.1 >Reporter: loc nguyen >Priority: Major > Labels: spark > > I received a Spark {{TreeNodeException}} executing a union of two data > frames. When I assign the union results to a DataFrame that will be returned > from by a function, this error occurs. However, I am able to assign the union > results to a DataFrame that will not be returned. I have examined schema for > all the data frames participating in the code. The PT_Id is being duplicated. > The PT_Id is duplicated and results in the failed search. > > > {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 > (TID 5557) > org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding > attribute, tree: DP_Acct_Identifier#140575 at > org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) > at > org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) > at > org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) > at > org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) > at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) > at > org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) > at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) > at > scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) > at > scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) > at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) > at > org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) > at > org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) > at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) > at
[jira] [Updated] (SPARK-34646) TreeNode bind issue
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Description: I received a Spark {{TreeNodeException}} executing a union of two data frames. When I assign the union results to a DataFrame that will be returned from by a function, this error occurs. However, I am able to assign the union results to a DataFrame that will not be returned. I have examined schema for all the data frames participating in the code. The PT_Id is being duplicated. The PT_Id is duplicated and results in the failed search. {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 (TID 5557) org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: DP_Acct_Identifier#140575 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) at scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Caused by: java.lang.RuntimeException: Couldn't find PT_Id#140575 in
[jira] [Updated] (SPARK-34646) TreeNode bind issue
[ https://issues.apache.org/jira/browse/SPARK-34646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] loc nguyen updated SPARK-34646: --- Description: I received a Spark {{TreeNodeException}} executing a union of two data frames. When I assign the union results to a DataFrame that will be returned from by a function, this error occurs. However, I am able to assign the union results to a DataFrame that will not be returned. I have examined schema for all the data frames participating in the code. The PT_Id is being duplicated. I am not sure why the PT_Id is duplicated and results in the failed search. {{21/03/04 19:58:28 ERROR Executor: Exception in task 2.0 in stage 2281.0 (TID 5557) org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: DP_Acct_Identifier#140575 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:79) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:326) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:324) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:261) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:245) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:78) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:45) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.bind(GeneratePredicate.scala:40) at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1190) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:403) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition$lzycompute(BroadcastNestedLoopJoinExec.scala:87) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec.org$apache$spark$sql$execution$joins$BroadcastNestedLoopJoinExec$$boundCondition(BroadcastNestedLoopJoinExec.scala:85) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2$$anonfun$apply$3.apply(BroadcastNestedLoopJoinExec.scala:191) at scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38) at scala.collection.IndexedSeqOptimized$class.exists(IndexedSeqOptimized.scala:46) at scala.collection.mutable.ArrayOps$ofRef.exists(ArrayOps.scala:186) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:191) at org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoinExec$$anonfun$4$$anonfun$apply$2.apply(BroadcastNestedLoopJoinExec.scala:190) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Caused by: java.lang.RuntimeException: Couldn't find PT_Id#140575 in