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https://issues.apache.org/jira/browse/ARROW-15312?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17482644#comment-17482644
]
Nicola Crane commented on ARROW-15312:
--------------------------------------
This appears to be restricted to Parquet format as there are no issues with
Feather or CSV:
{code:r}
library(arrow)
library(dplyr)
ds_path <- tempfile()
dir.create(ds_path)
df <- tibble(
y = c(0L, 0L, NA_integer_),
z = c(0L, 1L, NA_integer_)
)
df %>% arrow::write_dataset(ds_path, format = "feather")
arrow::open_dataset(ds_path, format = "feather") %>% collect() %>%
filter(is.na(y))
#> # A tibble: 1 × 2
#> y z
#> <int> <int>
#> 1 NA NA
arrow::open_dataset(ds_path, format = "feather") %>% filter(is.na(y)) %>%
collect()
#> # A tibble: 1 × 2
#> y z
#> <int> <int>
#> 1 NA NA
ds_path = tempfile()
dir.create(ds_path)
df %>% arrow::write_dataset(ds_path, format = "csv")
arrow::open_dataset(ds_path, format = "csv") %>% collect() %>% filter(is.na(y))
#> # A tibble: 1 × 2
#> y z
#> <int> <int>
#> 1 NA NA
arrow::open_dataset(ds_path, format = "csv") %>% filter(is.na(y)) %>% collect()
#> # A tibble: 1 × 2
#> y z
#> <int> <int>
#> 1 NA NA
{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: Blocker
> Fix For: 8.0.0, 7.0.1
>
>
> 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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