ianmcook commented on a change in pull request #10269:
URL: https://github.com/apache/arrow/pull/10269#discussion_r629647107
##########
File path: r/R/record-batch.R
##########
@@ -161,6 +161,17 @@ RecordBatch$create <- function(..., schema = NULL) {
out <- RecordBatch__from_arrays(schema, arrays)
return(dplyr::group_by(out, !!!dplyr::groups(arrays[[1]])))
}
+
+ # If any arrays are length 1, recycle them
+ arr_lens <- map_int(arrays, length)
+ if (length(arrays) > 1 && any(arr_lens == 1) && !all(arr_lens==1)){
+ max_array_len <- max(arr_lens)
+ arrays <- modify2(
+ arrays,
+ arr_lens == 1,
+ ~if(.y) MakeArrayFromScalar(Scalar$create(as.vector(.x)), max_array_len)
else .x
Review comment:
Looking at this a bit more, I think it might require some challenging
C++ coding to implement `combine_chunks()` like I described. Perhaps it should
be dealt with in a separate Jira & separate PR.
In the meantime, you could avoid calling `as.vector()` by handling
`ChunkedArray` explicitly here, taking the first chunk before passing it to
`Scalar$create()`:
```r
if (inherits(.x, "ChunkedArray")) {
.x <- .x$chunk(0)
}
```
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