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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2018/07/02 17:57:00 UTC
[jira] [Created] (SPARK-24721) Failed to call PythonUDF whose input
is the output of another PythonUDF
Xiao Li created SPARK-24721:
-------------------------------
Summary: Failed to call PythonUDF whose input is the output of another PythonUDF
Key: SPARK-24721
URL: https://issues.apache.org/jira/browse/SPARK-24721
Project: Spark
Issue Type: Improvement
Components: PySpark
Affects Versions: 2.3.1
Reporter: Xiao Li
{code}
import random
from pyspark.sql.functions import *
from pyspark.sql.types import *
def random_probability(label):
if label == 1.0:
return random.uniform(0.5, 1.0)
else:
return random.uniform(0.0, 0.4999)
def randomize_label(ratio):
if random.random() >= ratio:
return 1.0
else:
return 0.0
random_probability = udf(random_probability, DoubleType())
randomize_label = udf(randomize_label, DoubleType())
spark.range(10).write.mode("overwrite").format('csv').save("/tmp/tab3")
babydf = spark.read.csv("/tmp/tab3")
data_modified_label = babydf.withColumn(
'random_label', randomize_label(lit(1 - 0.1))
)
data_modified_random = data_modified_label.withColumn(
'random_probability',
random_probability(col('random_label'))
)
data_modified_label.filter(col('random_label') == 0).show()
{code}
The above code will generate the following exception:
{code}
Py4JJavaError: An error occurred while calling o446.showString.
: java.lang.RuntimeException: Invalid PythonUDF randomize_label(0.9), requires attributes from more than one child.
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:166)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract$2.apply(ExtractPythonUDFs.scala:165)
at scala.collection.immutable.Stream.foreach(Stream.scala:594)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract(ExtractPythonUDFs.scala:165)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:116)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:112)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:310)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:77)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:309)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:327)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:208)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:325)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:327)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:208)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:325)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:327)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:208)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:325)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:307)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:327)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:208)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:325)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:112)
at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:92)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:119)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:119)
at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at org.apache.spark.sql.execution.QueryExecution.prepareForExecution(QueryExecution.scala:119)
at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:109)
at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:109)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3016)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2216)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2429)
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:380)
at py4j.Gateway.invoke(Gateway.java:293)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:226)
at java.lang.Thread.run(Thread.java:748)
{code}
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