Jonathan Keane created ARROW-15838:
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Summary: [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
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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