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https://issues.apache.org/jira/browse/ARROW-15312?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17482600#comment-17482600
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Nicola Crane commented on ARROW-15312:
--------------------------------------
After further investigation, it looks a lot like this is to do with the number
of unique values in a column; if there is only 1 unique value other than NA,
nothing is returned; see the smaller reprex below.
{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
ds_path = tempfile()
dir.create(ds_path)
df = tibble(y=c("hi", "hi", NA_character_))
df %>% arrow::write_dataset(ds_path)
arrow::open_dataset(ds_path) %>% collect() %>% filter(is.na(y))
#> # A tibble: 1 × 1
#> y
#> <chr>
#> 1 <NA>
arrow::open_dataset(ds_path) %>% filter(is.na(y)) %>% collect()
#> # A tibble: 0 × 1
#> # … with 1 variable: y <chr>
{code}
> [R][C++] filtering a dataset with is.na() misses some rows
> ----------------------------------------------------------
>
> Key: ARROW-15312
> URL: https://issues.apache.org/jira/browse/ARROW-15312
> Project: Apache Arrow
> Issue Type: Bug
> Components: R
> Affects Versions: 6.0.1
> Environment: R 4.1.2 on Windows
> arrow 6.0.1
> dplyr 1.0.7
> Reporter: Pierre Gramme
> Priority: Major
>
> Hi !
> I just found an issue when querying an Arrow dataset with dplyr, filtering on
> is.na(...)
> It seems linked to columns containing only one distinct value and some NA's.
> Can you also reproduce the following?
>
> {code:java}
> library(arrow)
> library(dplyr)
>
> ds_path = "test-arrow-na"
> df = tibble(x=1:3, y=c(0L, 0L, NA_integer_), z=c(0L, 1L, NA_integer_))
>
> df %>% arrow::write_dataset(ds_path)
>
> # OK: Collect then filter: returns row 3, as expected
> arrow::open_dataset(ds_path) %>% collect() %>% filter(is.na(y))
> # ERROR: Filter then collect (on y) returns a tibble with no row
> arrow::open_dataset(ds_path) %>% filter(is.na(y)) %>% collect()
>
> # OK: Filter then collect (on z) returns row 3, as expected
> arrow::open_dataset(ds_path) %>% filter(is.na(z)) %>% collect() {code}
>
> Thanks
> Pierre
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