You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xinrong Meng (Jira)" <ji...@apache.org> on 2021/07/14 23:39:00 UTC
[jira] [Created] (SPARK-36141) Support arithmetic operations of
Series containing Decimal(np.nan)
Xinrong Meng created SPARK-36141:
------------------------------------
Summary: Support arithmetic operations of Series containing Decimal(np.nan)
Key: SPARK-36141
URL: https://issues.apache.org/jira/browse/SPARK-36141
Project: Spark
Issue Type: Sub-task
Components: PySpark
Affects Versions: 3.2.0
Reporter: Xinrong Meng
Arithmetic operations of Series containing Decimal(np.nan) raise java.lang.NullPointerException in driver. An example is shown as below:
{code:java}
>>> pser = pd.Series([decimal.Decimal(1.0), decimal.Decimal(2.0), decimal.Decimal(np.nan)])
>>> psser = ps.from_pandas(pser)
>>> pser + 1
0 2
1 3
2 NaN
>>> psser + 1
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2259)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2208)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2207)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2207)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1084)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1084)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1084)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2446)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2388)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2377)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:873)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2208)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2303)
at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToPython$5(Dataset.scala:3648)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1437)
at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToPython$2(Dataset.scala:3652)
at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToPython$2$adapted(Dataset.scala:3629)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:774)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704)
at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToPython$1(Dataset.scala:3629)
at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToPython$1$adapted(Dataset.scala:3628)
at org.apache.spark.security.SocketAuthServer$.$anonfun$serveToStream$2(SocketAuthServer.scala:139)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1437)
at org.apache.spark.security.SocketAuthServer$.$anonfun$serveToStream$1(SocketAuthServer.scala:141)
at org.apache.spark.security.SocketAuthServer$.$anonfun$serveToStream$1$adapted(SocketAuthServer.scala:136)
at org.apache.spark.security.SocketFuncServer.handleConnection(SocketAuthServer.scala:113)
at org.apache.spark.security.SocketFuncServer.handleConnection(SocketAuthServer.scala:107)
at org.apache.spark.security.SocketAuthServer$$anon$1.$anonfun$run$4(SocketAuthServer.scala:68)
at scala.util.Try$.apply(Try.scala:213)
at org.apache.spark.security.SocketAuthServer$$anon$1.run(SocketAuthServer.scala:68)
Caused by: java.lang.NullPointerException
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at scala.collection.Iterator$SliceIterator.hasNext(Iterator.scala:266)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:131)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:60)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:498)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1437)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:501)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
{code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org