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https://issues.apache.org/jira/browse/ARROW-15838?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17566909#comment-17566909
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Ian Cook edited comment on ARROW-15838 at 7/14/22 4:17 PM:
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IIUC, I think it should be possible to resolve this with a change only to the R
bindings, by using the {{coalesce}} function. I don't think we need changes in
Acero to resolve this, so it does not really depend on ARROW-15957.
was (Author: icook):
IIUC, I think it should be possible to resolve this with a change only to the R
bindings, by using the `coalesce` function. I don't think we need changes in
Acero to resolve this, so it does not really depend on ARROW-15957.
> [C++] Key column behavior in joins
> ----------------------------------
>
> Key: ARROW-15838
> URL: https://issues.apache.org/jira/browse/ARROW-15838
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++
> Reporter: Jonathan Keane
> Priority: Major
> Fix For: 10.0.0
>
>
> By default in dplyr (and possibly in pandas too?) coalesces the key column
> for full joins to be the (non-null) values from both key columns:
> {code}
> > left <- tibble::tibble(
> key = c(1, 2),
> A = c(0, 1),
> )
> left_tab <- Table$create(left)
> > right <- tibble::tibble(
> key = c(2, 3),
> B = c(0, 1),
> )
> right_tab <- Table$create(right)
> > left %>% full_join(right)
> Joining, by = "key"
> # A tibble: 3 × 3
> key A B
> <dbl> <dbl> <dbl>
> 1 1 0 NA
> 2 2 1 0
> 3 3 NA 1
> > left_tab %>% full_join(right_tab) %>% collect()
> # A tibble: 3 × 3
> key A B
> <dbl> <dbl> <dbl>
> 1 2 1 0
> 2 1 0 NA
> 3 NA NA 1
> {code}
> And right join, we would expect the key from the right table to be in the
> result, but we get the key from the left instead:
> {code}
> > left <- tibble::tibble(
> key = c(1, 2),
> A = c(0, 1),
> )
> left_tab <- Table$create(left)
> > right <- tibble::tibble(
> key = c(2, 3),
> B = c(0, 1),
> )
> right_tab <- Table$create(right)
> > left %>% right_join(right)
> Joining, by = "key"
> # A tibble: 2 × 3
> key A B
> <dbl> <dbl> <dbl>
> 1 2 1 0
> 2 3 NA 1
> > left_tab %>% right_join(right_tab) %>% collect()
> # A tibble: 2 × 3
> key A B
> <dbl> <dbl> <dbl>
> 1 2 1 0
> 2 NA NA 1
> {code}
> Additionally, we should be able to keep both key columns with an option (cf
> https://github.com/apache/arrow/blob/9719eae66dcf38c966ae769215d27020a6dd5550/r/R/dplyr-join.R#L32)
>
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