paleolimbot commented on a change in pull request #11612:
URL: https://github.com/apache/arrow/pull/11612#discussion_r744631444
##########
File path: r/tests/testthat/test-dplyr-summarize.R
##########
@@ -879,3 +879,20 @@ test_that("summarize() handles group_by .drop", {
)
)
})
+
+test_that("summarise() passes through type information for temporary columns",
{
+ # applies to ifelse and case_when(), in which argument types are checked
+ # within a translated function (previously this failed because the
appropriate
+ # schema was not available for n() > 1, mean(y), and mean(z))
+ compare_dplyr_binding(
+ .input %>%
+ group_by(x) %>%
+ summarise(r = ifelse(n() > 1, mean(y), mean(z))) %>%
+ collect(),
+ tibble(
+ x = c(0, 1, 1),
+ y = c(2, 3, 5),
+ z = c(8, 13, 21)
+ )
+ )
Review comment:
It doesn't, and I wonder if all the elements of inner expressions have
to be aggregate expressions? FWIW I get:
``` r
library(arrow, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)
RecordBatch$create(x = c(0, 1, 1), y = c(2, 3, 5), z = c(8, 13, 21)) %>%
mutate(new_col = x + 0.1) %>%
group_by(x) %>%
summarise(r = ifelse(new_col > 1, mean(y), mean(z))) %>%
collect()
#> Warning: Error : Expression ifelse(new_col > 1, mean(y), mean(z)) not
supported
#> in Arrow; pulling data into R
#> `summarise()` has grouped output by 'x'. You can override using the
`.groups` argument.
#> # A tibble: 3 × 2
#> # Groups: x [2]
#> x r
#> <dbl> <dbl>
#> 1 0 8
#> 2 1 4
#> 3 1 4
```
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