[
https://issues.apache.org/jira/browse/SPARK-30952?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-30952.
----------------------------------
Resolution: Cannot Reproduce
Seems fixed in the Spark master, or upper version combinations of pandas and
Arrow. It works:
{code}
[]
{code}
> Grouped pandas_udf crashed when a group returned an empty DataFrame
> --------------------------------------------------------------------
>
> Key: SPARK-30952
> URL: https://issues.apache.org/jira/browse/SPARK-30952
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.0
> Reporter: bruce_zhao
> Priority: Major
>
> We are trying to apply three-sigma rule in grouped data to detect anomaly
> data. We found that it's always crashed when a group returns an empty
> DataFrame (empty means no anomaly).
>
> Sample Code:
> {code:java}
> from pyspark.sql.functions import pandas_udf, PandasUDFType
> from pyspark.sql.types import StructField, StructType, StringType, LongType
> import pandas as pd
> from pyspark.sql import SparkSession
> import numpy as np
> def check_pdf():
> schema = StructType([
> StructField("customer_id", StringType(), True),
> StructField("count", LongType(), True)
> ])
> @pandas_udf(schema, PandasUDFType.GROUPED_MAP)
> def handler(pdf):
> mean = float(np.mean(pdf["count"]))
> sigma = float(np.std(pdf["count"], ddof=1))
> return pdf[pdf["count"] > mean + 3 * sigma]
> return handler
> def main():
> spark = SparkSession.builder \
> .appName("AppTest") \
> .master("local[4]") \
> .config("spark.driver.host", "localhost") \
> .config("spark.sql.shuffle.partitions", 2) \
> .getOrCreate()
> df = spark.createDataFrame([
> {
> "count": 15,
> "customer_id": "c1"
> },
> {
> "count": 11,
> "customer_id": "c1"
> },
> {
> "count": 11,
> "customer_id": "c2"
> }
> ])
> result = df.groupby("customer_id").apply(check_pdf()).collect()
> print(result)
> spark.stop()
> if __name__ == '__main__':
> main()
> {code}
> Exception:
> {code:java}
> 2020-02-26 10:56:45 ERROR Executor:91 - Exception in task 0.0 in stage 1.0
> (TID 4)
> org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$3.applyOrElse(PythonRunner.scala:486)
>
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$3.applyOrElse(PythonRunner.scala:475)
>
> at
> scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
> at
> org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:178)
>
> at
> org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:122)
>
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
>
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
>
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
>
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:121)
> at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)Caused by: java.io.EOFException at
> java.io.DataInputStream.readInt(DataInputStream.java:392) at
> org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:159)
>
> ... 20 more
> {code}
>
>
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
