Description
This issue seems to be related with https://issues.apache.org/jira/browse/SPARK-17811, which was resolved by https://github.com/apache/spark/pull/15421 .
If there exists a column of data type `date` which is completely NA, and another column of data type `timestamp`, then SparkR cannot collect that Spark dataframe into R dataframe.
The reproducible code snippet is below.
df <- data.frame(x = as.Date(NA), y = as.POSIXct("2022-01-01"))
SparkR::collect(SparkR::createDataFrame(df))
#> Error in handleErrors(returnStatus, conn): org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 25.0 failed 1 times, most recent failure: Lost task 0.0 in stage 25.0 (TID 25) (ip-10-172-210-194.us-west-2.compute.internal executor driver): java.lang.IllegalArgumentException: Invalid type N
#> at org.apache.spark.api.r.SerDe$.readTypedObject(SerDe.scala:94)
#> at org.apache.spark.api.r.SerDe$.readObject(SerDe.scala:68)
#> at #> org.apache.spark.sql.api.r.SQLUtils$.$anonfun$bytesToRow$1(SQLUtils.scala:129)
#> at org.apache.spark.sql.api.r.SQLUtils$.$anonfun$bytesToRow$1$adapted(SQLUtils.scala:128)
#> at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
#> at scala.collection.immutable.Range.foreach(Range.scala:158)
#> ...
This issue does not appear If the column of `date` data type is not missing. Or if there does not exist any other column with data type as `timestamp`.
df <- data.frame(x = as.Date("2022-01-01"), y = as.POSIXct("2022-01-01")) SparkR::collect(SparkR::createDataFrame(df)) #> x y #> 1 2022-01-01 2022-01-01
or
df <- data.frame(x = as.Date(NA), y = as.character("2022-01-01"))
SparkR::collect(SparkR::createDataFrame(df))
#> x y
#> 1 <NA> 2022-01-01
Attachments
Issue Links
- is related to
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SPARK-17811 SparkR cannot parallelize data.frame with NA or NULL in Date columns
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- Resolved
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- Resolved
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