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https://issues.apache.org/jira/browse/ARROW-18102?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17621425#comment-17621425
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Weston Pace commented on ARROW-18102:
-------------------------------------
Supposedly both behaviors are useful (returning null is SQL standards
compliant. See
https://database.guide/sqlite-sum-vs-total-whats-the-difference/). I think we
could add an option to the sum function. See also:
https://github.com/substrait-io/substrait/issues/259 so I expect we will
eventually need both behaviors.
> [R] dplyr::count and dplyr::tally implementation return NA instead of 0
> -----------------------------------------------------------------------
>
> Key: ARROW-18102
> URL: https://issues.apache.org/jira/browse/ARROW-18102
> Project: Apache Arrow
> Issue Type: Bug
> Components: R
> Environment: Arrow R package 9.0.0 on Mac OS 12.6 with R 4.2.0
> Reporter: Adam Black
> Priority: Major
>
> I'm using dplyr with FileSystemDataset objects. The expected behavior is
> similar (or the same as) dataframe behavior. When the FileSystemDataset has
> zero rows dplyr::count and dplyr::tally return NA instead of 0. I would
> expect the result to be 0.
>
> {code:r}
> library(arrow)
> #>
> #> Attaching package: 'arrow'
> #> The following object is masked from 'package:utils':
> #>
> #> timestamp
> library(dplyr)
> #>
> #> Attaching package: 'dplyr'
> #> The following objects are masked from 'package:stats':
> #>
> #> filter, lag
> #> The following objects are masked from 'package:base':
> #>
> #> intersect, setdiff, setequal, union
> path <- tempfile(fileext = ".feather")
> zero_row_dataset <- cars %>% filter(dist < 0)
> # expected behavior
> zero_row_dataset %>%
> count()
> #> n
> #> 1 0
> zero_row_dataset %>%
> tally()
> #> n
> #> 1 0
> nrow(zero_row_dataset)
> #> [1] 0
> # now test behavior with a FileSystemDataset
> write_feather(zero_row_dataset, path)
> ds <- open_dataset(path, format = "feather")
> ds
> #> FileSystemDataset with 1 Feather file
> #> speed: double
> #> dist: double
> #>
> #> See $metadata for additional Schema metadata
> # actual behavior
> ds %>%
> count() %>%
> collect() # incorrect result
> #> # A tibble: 1 × 1
> #> n
> #> <int>
> #> 1 NA
> ds %>%
> tally() %>%
> collect() # incorrect result
> #> # A tibble: 1 × 1
> #> n
> #> <int>
> #> 1 NA
> nrow(ds) # works as expected
> #> [1] 0
> {code}
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