jonkeane commented on code in PR #41223:
URL: https://github.com/apache/arrow/pull/41223#discussion_r1566578934
##########
r/R/dplyr-summarize.R:
##########
@@ -221,25 +257,27 @@ do_arrow_summarize <- function(.data, ..., .groups =
NULL) {
# It's more complex than other places because a single summarize() expr
# may result in multiple query nodes (Aggregate, Project),
# and we have to walk through the expressions to disentangle them.
- ctx <- env(
- mask = arrow_mask(.data, aggregation = TRUE),
- aggregations = empty_named_list(),
- post_mutate = empty_named_list()
- )
+
+ # Agg functions pull out the aggregation info and append it here
+ ..aggregations <- empty_named_list()
+ # And if there are any transformations after the aggregation, they go here
+ ..post_mutate <- empty_named_list()
+ mask <- arrow_mask(.data, aggregation = TRUE)
+
for (i in seq_along(exprs)) {
# Iterate over the indices and not the names because names may be repeated
# (which overwrites the previous name)
summarize_eval(
names(exprs)[i],
exprs[[i]],
- ctx,
+ mask,
length(.data$group_by_vars) > 0
)
}
# Apply the results to the .data object.
# First, the aggregations
- .data$aggregations <- ctx$aggregations
+ .data$aggregations <- ..aggregations
Review Comment:
Aaah yes, got it. I didn't totally put together that `..aggregations` wasn't
at the package scope, but that's really clever. And because it's transient
within the call we don't have to worry about flushing it at the end / cleaning
it up / managing state, yeah?
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