[
https://issues.apache.org/jira/browse/SPARK-32300?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Bryan Cutler resolved SPARK-32300.
----------------------------------
Fix Version/s: 2.4.7
Resolution: Fixed
Issue resolved by pull request 29098
[https://github.com/apache/spark/pull/29098]
> toPandas with no partitions should work
> ---------------------------------------
>
> Key: SPARK-32300
> URL: https://issues.apache.org/jira/browse/SPARK-32300
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.6
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Fix For: 2.4.7
>
>
> {code}
> >>> spark.sparkContext.emptyRDD().toDF("col1 int").toPandas()
> An error occurred while calling o158.getResult.
> : org.apache.spark.SparkException: Exception thrown in awaitResult:
> at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
> at
> org.apache.spark.api.python.PythonServer.getResult(PythonRDD.scala:874)
> at
> org.apache.spark.api.python.PythonServer.getResult(PythonRDD.scala:870)
> 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:238)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: java.lang.NegativeArraySizeException
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1$$anonfun$apply$17.apply(Dataset.scala:3293)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1$$anonfun$apply$17.apply(Dataset.scala:3287)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withAction(Dataset.scala:3369)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1.apply(Dataset.scala:3287)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1.apply(Dataset.scala:3286)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply$mcV$sp(PythonRDD.scala:456)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply(PythonRDD.scala:456)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply(PythonRDD.scala:456)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7.apply(PythonRDD.scala:457)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7.apply(PythonRDD.scala:453)
> at
> org.apache.spark.api.python.SocketFuncServer.handleConnection(PythonRDD.scala:994)
> at
> org.apache.spark.api.python.SocketFuncServer.handleConnection(PythonRDD.scala:988)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11$$anonfun$apply$9.apply(PythonRDD.scala:853)
> at scala.util.Try$.apply(Try.scala:192)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11.apply(PythonRDD.scala:853)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11.apply(PythonRDD.scala:852)
> at
> org.apache.spark.api.python.PythonServer$$anon$1.run(PythonRDD.scala:908)
> warnings.warn(msg)
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File
> "/Users/hyukjin.kwon/workspace/forked/spark/python/pyspark/sql/dataframe.py",
> line 2132, in toPandas
> batches = self.toDF(*tmp_column_names)._collectAsArrow()
> File
> "/Users/hyukjin.kwon/workspace/forked/spark/python/pyspark/sql/dataframe.py",
> line 2223, in _collectAsArrow
> jsocket_auth_server.getResult() # Join serving thread and raise any
> exceptions
> File
> "/Users/hyukjin.kwon/workspace/forked/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py",
> line 1257, in __call__
> File
> "/Users/hyukjin.kwon/workspace/forked/spark/python/pyspark/sql/utils.py",
> line 63, in deco
> return f(*a, **kw)
> File
> "/Users/hyukjin.kwon/workspace/forked/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py",
> line 328, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o158.getResult.
> : org.apache.spark.SparkException: Exception thrown in awaitResult:
> at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
> at
> org.apache.spark.api.python.PythonServer.getResult(PythonRDD.scala:874)
> at
> org.apache.spark.api.python.PythonServer.getResult(PythonRDD.scala:870)
> 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:238)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: java.lang.NegativeArraySizeException
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1$$anonfun$apply$17.apply(Dataset.scala:3293)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1$$anonfun$apply$17.apply(Dataset.scala:3287)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withAction(Dataset.scala:3369)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1.apply(Dataset.scala:3287)
> at
> org.apache.spark.sql.Dataset$$anonfun$collectAsArrowToPython$1.apply(Dataset.scala:3286)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply$mcV$sp(PythonRDD.scala:456)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply(PythonRDD.scala:456)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7$$anonfun$apply$3.apply(PythonRDD.scala:456)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7.apply(PythonRDD.scala:457)
> at
> org.apache.spark.api.python.PythonRDD$$anonfun$7.apply(PythonRDD.scala:453)
> at
> org.apache.spark.api.python.SocketFuncServer.handleConnection(PythonRDD.scala:994)
> at
> org.apache.spark.api.python.SocketFuncServer.handleConnection(PythonRDD.scala:988)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11$$anonfun$apply$9.apply(PythonRDD.scala:853)
> at scala.util.Try$.apply(Try.scala:192)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11.apply(PythonRDD.scala:853)
> at
> org.apache.spark.api.python.PythonServer$$anonfun$11.apply(PythonRDD.scala:852)
> at
> org.apache.spark.api.python.PythonServer$$anon$1.run(PythonRDD.scala:908)
> {code}
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