Github user olarayej commented on the pull request:
https://github.com/apache/spark/pull/11336#issuecomment-191399711
Also, the fact that the size of a column depends on the join seems
counter-intuitive for an R user:
```
> dim(irisDF2)
[1] 150 5
> dim(irisDF)
[1] 150 5
> x <- irisDF$Sepal_Length + irisDF2$Sepal_Length
```
In R, x will always have 150 elements. However:
```
# Cartesian product
> df3 <- join(irisDF, irisDF2)
> dim(select(df3, x))
[1] 22500 1
# Inner join by Species
> df4 <- merge(irisDF, irisDF2, by="Species")
> dim(select(df4, x))
[1] 7500 1
```
I still think SparkR shouldn't allow operations between columns coming from
different DataFrames. And, in the case of a join, operations can be performed
on the joined DataFrame (e.g., df3) as opposed to the original ones (e.g.,
irisDF and irisDF2).
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