[jira] [Assigned] (SPARK-23177) PySpark parameter-less UDFs raise exception if applied after distinct

2018-01-23 Thread Hyukjin Kwon (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-23177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon reassigned SPARK-23177:


Assignee: Liang-Chi Hsieh

> PySpark parameter-less UDFs raise exception if applied after distinct
> -
>
> Key: SPARK-23177
> URL: https://issues.apache.org/jira/browse/SPARK-23177
> Project: Spark
>  Issue Type: Bug
>  Components: PySpark
>Affects Versions: 2.1.2, 2.2.0, 2.2.1
>Reporter: Jakub Wasikowski
>Assignee: Liang-Chi Hsieh
>Priority: Major
> Fix For: 2.4.0
>
>
> It seems there is an issue with UDFs that take no arguments, but only if UDF 
> is applied after {{distinct()}} operation.
> Here is the short example, that allows reproduce an issue in PySpark shell:
> {code:java}
> import pyspark.sql.functions as f
> import uuid
> df = spark.createDataFrame([(1,2), (3,4)])
> f_udf = f.udf(lambda: str(uuid.uuid4()))
> df.distinct().withColumn("a", f_udf()).show()
> {code}
> and it raises the following exception:
> {noformat}
> Traceback (most recent call last):
>   File "", line 1, in 
>   File "/opt/spark/python/pyspark/sql/dataframe.py", line 336, in show
> print(self._jdf.showString(n, 20))
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 
> 1133, in __call__
>   File "/opt/spark/python/pyspark/sql/utils.py", line 63, in deco
> return f(*a, **kw)
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 
> 319, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o54.showString.
> : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding 
> attribute, tree: pythonUDF0#16
>   at 
> org.apache.spark.sql.catalyst.errors.package$.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 
>

[jira] [Assigned] (SPARK-23177) PySpark parameter-less UDFs raise exception if applied after distinct

2018-01-22 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-23177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-23177:


Assignee: (was: Apache Spark)

> PySpark parameter-less UDFs raise exception if applied after distinct
> -
>
> Key: SPARK-23177
> URL: https://issues.apache.org/jira/browse/SPARK-23177
> Project: Spark
>  Issue Type: Bug
>  Components: PySpark
>Affects Versions: 2.1.2, 2.2.0, 2.2.1
>Reporter: Jakub Wasikowski
>Priority: Major
>
> It seems there is an issue with UDFs that take no arguments, but only if UDF 
> is applied after {{distinct()}} operation.
> Here is the short example, that allows reproduce an issue in PySpark shell:
> {code:java}
> import pyspark.sql.functions as f
> import uuid
> df = spark.createDataFrame([(1,2), (3,4)])
> f_udf = f.udf(lambda: str(uuid.uuid4()))
> df.distinct().withColumn("a", f_udf()).show()
> {code}
> and it raises the following exception:
> {noformat}
> Traceback (most recent call last):
>   File "", line 1, in 
>   File "/opt/spark/python/pyspark/sql/dataframe.py", line 336, in show
> print(self._jdf.showString(n, 20))
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 
> 1133, in __call__
>   File "/opt/spark/python/pyspark/sql/utils.py", line 63, in deco
> return f(*a, **kw)
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 
> 319, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o54.showString.
> : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding 
> attribute, tree: pythonUDF0#16
>   at 
> org.apache.spark.sql.catalyst.errors.package$.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)
>

[jira] [Assigned] (SPARK-23177) PySpark parameter-less UDFs raise exception if applied after distinct

2018-01-22 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-23177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-23177:


Assignee: Apache Spark

> PySpark parameter-less UDFs raise exception if applied after distinct
> -
>
> Key: SPARK-23177
> URL: https://issues.apache.org/jira/browse/SPARK-23177
> Project: Spark
>  Issue Type: Bug
>  Components: PySpark
>Affects Versions: 2.1.2, 2.2.0, 2.2.1
>Reporter: Jakub Wasikowski
>Assignee: Apache Spark
>Priority: Major
>
> It seems there is an issue with UDFs that take no arguments, but only if UDF 
> is applied after {{distinct()}} operation.
> Here is the short example, that allows reproduce an issue in PySpark shell:
> {code:java}
> import pyspark.sql.functions as f
> import uuid
> df = spark.createDataFrame([(1,2), (3,4)])
> f_udf = f.udf(lambda: str(uuid.uuid4()))
> df.distinct().withColumn("a", f_udf()).show()
> {code}
> and it raises the following exception:
> {noformat}
> Traceback (most recent call last):
>   File "", line 1, in 
>   File "/opt/spark/python/pyspark/sql/dataframe.py", line 336, in show
> print(self._jdf.showString(n, 20))
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 
> 1133, in __call__
>   File "/opt/spark/python/pyspark/sql/utils.py", line 63, in deco
> return f(*a, **kw)
>   File "/opt/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 
> 319, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o54.showString.
> : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding 
> attribute, tree: pythonUDF0#16
>   at 
> org.apache.spark.sql.catalyst.errors.package$.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 
>