westonpace commented on a change in pull request #10191:
URL: https://github.com/apache/arrow/pull/10191#discussion_r625372419
##########
File path: r/tests/testthat/test-dplyr-mutate.R
##########
@@ -344,20 +344,21 @@ test_that("print a mutated table", {
select(int) %>%
mutate(twice = int * 2) %>%
print(),
-'Table (query)
+'InMemoryDataset (query)
int: int32
twice: expr
See $.data for the source Arrow object',
fixed = TRUE)
# Handling non-expressions/edge cases
+ skip("InMemoryDataset$Project() doesn't accept array (or could it?)")
expect_output(
Table$create(tbl) %>%
select(int) %>%
mutate(again = 1:10) %>%
Review comment:
None of the examples on
https://dplyr.tidyverse.org/reference/mutate.html actually use this form and I
have a hard time understanding why someone might want to do this?
Furthermore, this question
https://stackoverflow.com/questions/60582562/another-length-error-using-dplyr-mutate-and-if-else
shows some of the confusion you run into with something like this.
From an SQL perspective the proper way to add in a new column would be to
join. This is sort of a "join without a common key" which raises a few
eyebrows in this question:
https://stackoverflow.com/questions/1198124/combine-two-tables-that-have-no-common-fields
Also, would the vector be the same length as a single batch? Or the entire
table? If it's the entire table then it's going to force the table to be
processed in order which is undesirable as well.
I think I'd want to see a valid use case before investing effort.
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