Github user NarineK commented on the pull request:
https://github.com/apache/spark/pull/12836#issuecomment-219344135
Hi @sun-rui ,
Thank you for the comments.
1. This point is easy to do. I'll do the change.
2. With `key columns` I assume that you refer to the grouping column names.
Something like `Species` in the iris dataset ?
Actually, in my implementation I do not use the keys on the R side, I use
it as a boundary, I could also write one bit, like dataOut.writeInt(1) just to
mark the boundary. But if according to your 3rd point we want to pass keys to R
function like: (Keys, ldf), then we need more than just a boundary.
3. Well it might make sense, but currently the user can still access the
grouping columns, like I did in the examples:
```
df1 <- gapply(
df, list(df$"Species")
function(x) {
data.frame(**x$Species[1]**, mean(x$Sepal_Width), stringsAsFactors =
FALSE)
},
schema)
```
`**x$Species[1]**` accesses the key .
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