[jira] [Created] (SPARK-33113) [SparkR] gapply works with arrow disabled, fails with arrow enabled

["Jacek Pliszka (Jira)" <ji...@apache.org>]

Jacek Pliszka created SPARK-33113:
-------------------------------------

             Summary: [SparkR] gapply works with arrow disabled, fails with arrow enabled
                 Key: SPARK-33113
                 URL: https://issues.apache.org/jira/browse/SPARK-33113
             Project: Spark
          Issue Type: Bug
          Components: R
    Affects Versions: 3.0.0
            Reporter: Jacek Pliszka


Running in databricks on Azure

library("arrow")
library("SparkR")

df <- as.DataFrame(list("A", "B", "C"), schema="ColumnA")
udf <- function(key, x) data.frame(out=c("dfs"), stringAsFactors=FALSE)

 

This works:

sparkR.session(master = "local[*]", sparkConfig=list(spark.sql.execution.arrow.sparkr.enabled = "false"))
df1 <- gapply(df, c("ColumnA"), udf, "out String")
collect(df1)

This fails:

sparkR.session(master = "local[*]", sparkConfig=list(spark.sql.execution.arrow.sparkr.enabled = "true"))
df2 <- gapply(df, c("ColumnA"), udf, "out String")
collect(df2)

 

with error
{{ Error in readBin(con, raw(), as.integer(dataLen), endian = "big") :  }}Error in readBin(con, raw(), as.integer(dataLen), endian = "big") : invalid 'n' argument
Error in readBin(con, raw(), as.integer(dataLen), endian = "big") : invalid 'n' argument In addition: Warning messages: 1: Use 'read_ipc_stream' or 'read_feather' instead. 2: Use 'read_ipc_stream' or 'read_feather' instead.
 
Clicking through Failed Stages to Failure Reason:
 
Job aborted due to stage failure: Task 49 in stage 1843.0 failed 4 times, most recent failure: Lost task 49.3 in stage 1843.0 (TID 89810, 10.99.0.5, executor 0): java.lang.UnsupportedOperationException
 at org.apache.spark.sql.vectorized.ArrowColumnVector$ArrowVectorAccessor.getUTF8String(ArrowColumnVector.java:233)
 at org.apache.spark.sql.vectorized.ArrowColumnVector.getUTF8String(ArrowColumnVector.java:109)
 at org.apache.spark.sql.vectorized.ColumnarBatchRow.getUTF8String(ColumnarBatch.java:220)
 at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
 at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
 at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
 at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$1.$anonfun$next$1(ArrowConverters.scala:131)
 at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
 at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1559)
 at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$1.next(ArrowConverters.scala:140)
 at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$1.next(ArrowConverters.scala:115)
 at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
 at scala.collection.Iterator.foreach(Iterator.scala:941)
 at scala.collection.Iterator.foreach$(Iterator.scala:941)
 at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
 at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
 at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
 at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
 at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
 at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
 at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
 at scala.collection.AbstractIterator.to(Iterator.scala:1429)
 at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
 at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
 at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1429)
 at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
 at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
 at scala.collection.AbstractIterator.toArray(Iterator.scala:1429)
 at org.apache.spark.sql.Dataset.$anonfun$collectAsArrowToR$3(Dataset.scala:3589)
 at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
 at org.apache.spark.scheduler.Task.doRunTask(Task.scala:144)
 at org.apache.spark.scheduler.Task.run(Task.scala:117)
 at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$9(Executor.scala:639)
 at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1559)
 at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:642)
 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
 at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
 
 

 

 

 

 



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