[
https://issues.apache.org/jira/browse/SPARK-22641?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andrew Duffy updated SPARK-22641:
---------------------------------
Description:
We seem to have found an issue with PySpark UDFs interacting with
{{withColumn}} when the UDF depends on the column added in {{withColumn}}, but
_only_ if {{withColumn}} is performed after a {{distinct()}}.
Simplest repro in a local PySpark shell:
{code}
import pyspark.sql.functions as F
@F.udf
def ident(x):
return x
spark.createDataFrame([{'a': '1'}]) \
.distinct() \
.withColumn('b', F.lit('qq')) \
.withColumn('fails_here', ident('b')) \
.collect()
{code}
This fails with the following exception:
{code}
py4j.protocol.Py4JJavaError: An error occurred while calling
o263.collectToPython.
: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding
attribute, tree: pythonUDF0#97
at
org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:91)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:90)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:90)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$38.apply(HashAggregateExec.scala:514)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$38.apply(HashAggregateExec.scala:513)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.generateResultFunction(HashAggregateExec.scala:513)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduceWithKeys(HashAggregateExec.scala:659)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduce(HashAggregateExec.scala:164)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:85)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:80)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:141)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:138)
at
org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:80)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.produce(HashAggregateExec.scala:38)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:374)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:422)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:113)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:141)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:138)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
at
org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:233)
at
org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:280)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:3088)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3085)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3085)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:3118)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3085)
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:282)
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:748)
Caused by: java.lang.RuntimeException: Couldn't find pythonUDF0#97 in [a#84]
at scala.sys.package$.error(package.scala:27)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:97)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:91)
at
org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 58 more
{code}
The odd part is that if you run the code, but remove the {{.distinct()}}, or
place it after either of the {{.withColumn}} lines, we don't get the error.
was:
We seem to have found an issue with PySpark UDFs interacting with
{{withColumn}} when the UDF depends on the column added in {{withColumn}}, but
_only_ if {{withColumn}} is performed after a {{distinct()}}.
Simplest repro in a local PySpark shell:
{code}
import pyspark.sql.functions as F
@F.udf
def ident(x):
return x
spark.createDataFrame([{'a': '1'}]) \
.distinct() \
.withColumn('b', F.lit('qq')) \
.withColumn('fails_here', ident('b')) \
.collect()
{code}
This fails with the following exception:
{code}
Py4JJavaError: An error occurred while calling o1321.collectToPython.
: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding
attribute, tree: pythonUDF0#306
at
org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:88)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:87)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:87)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$33.apply(HashAggregateExec.scala:475)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$33.apply(HashAggregateExec.scala:474)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.generateResultCode(HashAggregateExec.scala:474)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduceWithKeys(HashAggregateExec.scala:612)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduce(HashAggregateExec.scala:148)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:85)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:80)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at
org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:80)
at
org.apache.spark.sql.execution.aggregate.HashAggregateExec.produce(HashAggregateExec.scala:38)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:331)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:372)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at
org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:228)
at
org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2872)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2869)
at
org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2869)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2892)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2869)
at sun.reflect.GeneratedMethodAccessor60.invoke(Unknown Source)
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:748)
Caused by: java.lang.RuntimeException: Couldn't find pythonUDF0#306 in [a#293]
at scala.sys.package$.error(package.scala:27)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:94)
at
org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:88)
at
org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 58 more
{code}
The odd part is that if you run the code, but remove the {{.distinct()}}, or
place it after either of the {{.withColumn}} lines, we don't get the error.
> Pyspark UDF relying on column added with withColumn after distinct
> ------------------------------------------------------------------
>
> Key: SPARK-22641
> URL: https://issues.apache.org/jira/browse/SPARK-22641
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Andrew Duffy
>
> We seem to have found an issue with PySpark UDFs interacting with
> {{withColumn}} when the UDF depends on the column added in {{withColumn}},
> but _only_ if {{withColumn}} is performed after a {{distinct()}}.
> Simplest repro in a local PySpark shell:
> {code}
> import pyspark.sql.functions as F
> @F.udf
> def ident(x):
> return x
> spark.createDataFrame([{'a': '1'}]) \
> .distinct() \
> .withColumn('b', F.lit('qq')) \
> .withColumn('fails_here', ident('b')) \
> .collect()
> {code}
> This fails with the following exception:
> {code}
> py4j.protocol.Py4JJavaError: An error occurred while calling
> o263.collectToPython.
> : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding
> attribute, tree: pythonUDF0#97
> at
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
> at
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:91)
> at
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:90)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
> at
> org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:90)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$38.apply(HashAggregateExec.scala:514)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec$$anonfun$38.apply(HashAggregateExec.scala:513)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.generateResultFunction(HashAggregateExec.scala:513)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduceWithKeys(HashAggregateExec.scala:659)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.doProduce(HashAggregateExec.scala:164)
> at
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:85)
> at
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:80)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:141)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:138)
> at
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:80)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.produce(HashAggregateExec.scala:38)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:374)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:422)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:113)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:141)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:138)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:233)
> at
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:280)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:3088)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3085)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3085)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
> at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:3118)
> at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3085)
> 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:282)
> 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:748)
> Caused by: java.lang.RuntimeException: Couldn't find pythonUDF0#97 in [a#84]
> at scala.sys.package$.error(package.scala:27)
> at
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:97)
> at
> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:91)
> at
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
> ... 58 more
> {code}
> The odd part is that if you run the code, but remove the {{.distinct()}}, or
> place it after either of the {{.withColumn}} lines, we don't get the error.
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