ianmcook commented on a change in pull request #9586:
URL: https://github.com/apache/arrow/pull/9586#discussion_r588621424
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File path: r/R/dplyr.R
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@@ -539,6 +537,13 @@ mutate.arrow_dplyr_query <- function(.data,
if (inherits(results[[new_var]], "try-error")) {
msg <- paste('Expression', as_label(exprs[[i]]), 'not supported in
Arrow')
return(abandon_ship(call, .data, msg))
+ } else if (is_dataset && !inherits(results[[new_var]], "Expression")) {
+ # We need some wrapping to handle literal values
+ if (length(results[[new_var]]) != 1) {
+ msg <- paste0('In ', new_var, " = ", as_label(exprs[[i]]), ", only
values of size one are recycled")
Review comment:
> Why would one ever call `transmute()` or `mutate()` like this (on
purpose)?
An increasing amount of dplyr code is programmatically generated, not
hand-written. It's quite common to have empty lists and `NULL` values getting
passed to verbs in such cases.
Also, this could happen by accident if a variable has a `NULL` value and
then it's used in the `mutate()` expression.
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