[ https://issues.apache.org/jira/browse/SPARK-33113?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Jacek Pliszka updated SPARK-33113: ---------------------------------- Description: 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")) 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: was: 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: > [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, 3.0.1 > Reporter: Jacek Pliszka > Priority: Major > > 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")) > > 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: > > > > > > -- 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