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From "mandar uapdhye (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (ATTRIBUTES-17) pyspark - Invalid PythonUDF
Date Fri, 24 Mar 2017 14:42:41 GMT

     [ https://issues.apache.org/jira/browse/ATTRIBUTES-17?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

mandar uapdhye updated ATTRIBUTES-17:
-------------------------------------
    Description: 
Invalid PythonUDF < .. >, requires attributes from more than one child.

UDF tries to operate on multiple columns. 



```
at scala.sys.package$.error(package.scala:27)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract$2.apply(ExtractPythonUDFs.scala:150)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract$2.apply(ExtractPythonUDFs.scala:149)
	at scala.collection.immutable.Stream.foreach(Stream.scala:594)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract(ExtractPythonUDFs.scala:149)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:114)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:113)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:309)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:113)
	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:93)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:94)
	at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:94)
	at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
	at scala.collection.immutable.List.foldLeft(List.scala:84)
	at org.apache.spark.sql.execution.QueryExecution.prepareForExecution(QueryExecution.scala:94)
	at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:84)
	at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:84)
	at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2791)
	at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
	at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
	at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
	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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:280)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:214)
	at java.lang.Thread.run(Thread.java:745)

```

  was:
Invalid PythonUDF < .. >, requires attributes from more than one child.

UDF tries to operate on multiple columns. 


> pyspark - Invalid PythonUDF
> ---------------------------
>
>                 Key: ATTRIBUTES-17
>                 URL: https://issues.apache.org/jira/browse/ATTRIBUTES-17
>             Project: Commons Attributes
>          Issue Type: Bug
>    Affects Versions: 2.1
>         Environment: mac OSX El Capitan
>            Reporter: mandar uapdhye
>              Labels: newbie
>
> Invalid PythonUDF < .. >, requires attributes from more than one child.
> UDF tries to operate on multiple columns. 
> ```
> at scala.sys.package$.error(package.scala:27)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract$2.apply(ExtractPythonUDFs.scala:150)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract$2.apply(ExtractPythonUDFs.scala:149)
> 	at scala.collection.immutable.Stream.foreach(Stream.scala:594)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract(ExtractPythonUDFs.scala:149)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:114)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:113)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
> 	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:309)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:331)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:113)
> 	at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:93)
> 	at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:94)
> 	at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:94)
> 	at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> 	at scala.collection.immutable.List.foldLeft(List.scala:84)
> 	at org.apache.spark.sql.execution.QueryExecution.prepareForExecution(QueryExecution.scala:94)
> 	at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:84)
> 	at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:84)
> 	at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2791)
> 	at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
> 	at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
> 	at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
> 	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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> 	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> 	at py4j.Gateway.invoke(Gateway.java:280)
> 	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> 	at py4j.commands.CallCommand.execute(CallCommand.java:79)
> 	at py4j.GatewayConnection.run(GatewayConnection.java:214)
> 	at java.lang.Thread.run(Thread.java:745)
> ```



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