ARROW-13766: [R] Add slice_*() methods #14361
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| arrow_not_supported("Slicing Arrow data with groups") | ||
| } | ||
| if (with_ties) { | ||
| arrow_not_supported("with_ties = TRUE") |
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As @paleolimbot noted on ARROW-13766, it is possible to do with_ties but it requires doing the top-k calculation and then using that as a filtering join. I'm inclined either not to support it (as done here, before I saw that comment) or to flip the default value of with_ties and perhaps raise a warning the first time the function is called to note the difference. Thoughts?
| } | ||
| slice_head.Dataset <- slice_head.ArrowTabular <- slice_head.RecordBatchReader <- slice_head.arrow_dplyr_query | ||
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| slice_tail.arrow_dplyr_query <- function(.data, ..., n, prop) { |
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There's an error message for extraneous slice_*()-related arguments which dplyr has but we don't have that here:
library(dplyr)
library(arrow)
mtcars %>%
slice_tail(n = 3, with_ties = FALSE) %>%
collect()
#> Error in `slice_tail()`:
#> ! `...` must be empty.
#> ✖ Problematic argument:
#> • with_ties = FALSE
mtcars %>%
arrow_table() %>%
slice_tail(n = 3, with_ties = FALSE) %>%
collect()
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
#> 2 15.0 8 301 335 3.54 3.57 14.6 0 1 5 8
#> 3 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2There was a problem hiding this comment.
Good catch, added the rlang::check_dots_empty call. I left it as rlang:: instead of adding it to the importFrom we use because I thought you had some PRs open that were touching that, can move there before merging. (Also need to re-run the docgen.R anyway.)
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I had a check, and none of my open PRs are touching that, so good to move whenever.
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@thisisnic thanks for your excellent review. I've addressed your feedback and pushed a little more to unlock |
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Co-authored-by: Nic Crane <thisisnic@gmail.com>
…without projecting it first)
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@thisisnic want to give this one more look? |
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Benchmark runs are scheduled for baseline = b5b41cc and contender = 80e3986. 80e3986 is a master commit associated with this PR. Results will be available as each benchmark for each run completes. |
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['Python', 'R'] benchmarks have high level of regressions. |
This PR implements
slice_head,()slice_tail(),slice_min(),slice_max()andslice_sample().slice_sample()requires a clever hack using a UDF because therandom()C++ function apparently does not work; see ARROW-17974.