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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:02:10 UTC
[jira] [Updated] (SPARK-18011) SparkR serialize "NA" throws
exception
[ https://issues.apache.org/jira/browse/SPARK-18011?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-18011:
---------------------------------
Labels: bulk-closed (was: )
> SparkR serialize "NA" throws exception
> --------------------------------------
>
> Key: SPARK-18011
> URL: https://issues.apache.org/jira/browse/SPARK-18011
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Reporter: Miao Wang
> Priority: Major
> Labels: bulk-closed
>
> For some versions of R, if Date has "NA" field, backend will throw negative index exception.
> To reproduce the problem:
> {code}
> > a <- as.Date(c("2016-11-11", "NA"))
> > b <- as.data.frame(a)
> > c <- createDataFrame(b)
> > dim(c)
> 16/10/19 10:31:24 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1)
> java.lang.NegativeArraySizeException
> at org.apache.spark.api.r.SerDe$.readStringBytes(SerDe.scala:110)
> at org.apache.spark.api.r.SerDe$.readString(SerDe.scala:119)
> at org.apache.spark.api.r.SerDe$.readDate(SerDe.scala:128)
> at org.apache.spark.api.r.SerDe$.readTypedObject(SerDe.scala:77)
> at org.apache.spark.api.r.SerDe$.readObject(SerDe.scala:61)
> at org.apache.spark.sql.api.r.SQLUtils$$anonfun$bytesToRow$1.apply(SQLUtils.scala:161)
> at org.apache.spark.sql.api.r.SQLUtils$$anonfun$bytesToRow$1.apply(SQLUtils.scala:160)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.Range.foreach(Range.scala:160)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.api.r.SQLUtils$.bytesToRow(SQLUtils.scala:160)
> at org.apache.spark.sql.api.r.SQLUtils$$anonfun$5.apply(SQLUtils.scala:138)
> at org.apache.spark.sql.api.r.SQLUtils$$anonfun$5.apply(SQLUtils.scala:138)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:372)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {code}
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