[ 
https://issues.apache.org/jira/browse/SPARK-32478?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-32478:
---------------------------------
    Description: 
Currently, the error message is confusing when the output schema type is not 
matched with the actual R DataFrame in gapply:

{code}
./bin/sparkR --conf spark.sql.execution.arrow.sparkr.enabled=true
{code}

{code}
df <- createDataFrame(list(list(a=1L, b="2")))
count(gapply(df, "a", function(key, group) { group }, structType("a int, b 
int")))
{code}

{code}
  org.apache.spark.SparkException: Job aborted due to stage failure: Task 43 in 
stage 2.0 failed 1 times, most recent failure: Lost task 43.0 in stage 2.0 (TID 
2, 192.168.35.193, executor driver): java.lang.UnsupportedOperationException
        at 
org.apache.spark.sql.vectorized.ArrowColumnVector$ArrowVectorAccessor.getInt(ArrowColumnVector.java:212)
        ...
{code}

We should probably also document that the type should be matched always.

  was:
Currently, the error message is confusing when the output schema type is not 
matched with the actual R DataFrame in gapply:

{code}
df <- createDataFrame(list(list(a=1L, b="2")))
count(gapply(df, "a", function(key, group) { group }, structType("a int, b 
int")))
{code}

{code}
  org.apache.spark.SparkException: Job aborted due to stage failure: Task 43 in 
stage 2.0 failed 1 times, most recent failure: Lost task 43.0 in stage 2.0 (TID 
2, 192.168.35.193, executor driver): java.lang.UnsupportedOperationException
        at 
org.apache.spark.sql.vectorized.ArrowColumnVector$ArrowVectorAccessor.getInt(ArrowColumnVector.java:212)
        ...
{code}

We should probably also document that the type should be matched always.


> Error message to show the schema mismatch in gapply with Arrow vectorization
> ----------------------------------------------------------------------------
>
>                 Key: SPARK-32478
>                 URL: https://issues.apache.org/jira/browse/SPARK-32478
>             Project: Spark
>          Issue Type: Improvement
>          Components: SparkR
>    Affects Versions: 3.0.0
>            Reporter: Hyukjin Kwon
>            Priority: Major
>
> Currently, the error message is confusing when the output schema type is not 
> matched with the actual R DataFrame in gapply:
> {code}
> ./bin/sparkR --conf spark.sql.execution.arrow.sparkr.enabled=true
> {code}
> {code}
> df <- createDataFrame(list(list(a=1L, b="2")))
> count(gapply(df, "a", function(key, group) { group }, structType("a int, b 
> int")))
> {code}
> {code}
>   org.apache.spark.SparkException: Job aborted due to stage failure: Task 43 
> in stage 2.0 failed 1 times, most recent failure: Lost task 43.0 in stage 2.0 
> (TID 2, 192.168.35.193, executor driver): 
> java.lang.UnsupportedOperationException
>       at 
> org.apache.spark.sql.vectorized.ArrowColumnVector$ArrowVectorAccessor.getInt(ArrowColumnVector.java:212)
>       ...
> {code}
> We should probably also document that the type should be matched always.



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