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Posted to jira@arrow.apache.org by "Andy Teucher (Jira)" <ji...@apache.org> on 2022/03/22 19:08:00 UTC
[jira] [Updated] (ARROW-16007) [R] binding for grepl has different behaviour with NA compared to R base grepl
[ https://issues.apache.org/jira/browse/ARROW-16007?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Andy Teucher updated ARROW-16007:
---------------------------------
Description:
The arrow binding to {{grepl}} behaves slightly differently than the base R {{{}grepl{}}}, in that it returns {{NA}} for {{NA}} inputs, whereas base {{grepl}} returns {{{}FALSE with \{{NA}}inputs. arrow's implementention is consistent with stringr::str_detect(){}}}, and both {{str_detect()}} and {{grepl()}} are bound to {{match_substring_regex}} and {{match_substring}} in arrow.
I don't know if this is something you would want to change so that the {{grepl}} behaviour aligns with base {{{}grepl{}}}, or simply document this difference?
Reprex:
{code:r}
library(arrow, warn.conflicts = FALSE, quietly = TRUE)
library(dplyr, warn.conflicts = FALSE, quietly = TRUE)
library(stringr, quietly = TRUE)
alpha_df <- data.frame(alpha = c("alpha", "bet", NA_character_))
alpha_dataset <- InMemoryDataset$create(alpha_df)
mutate(alpha_df,
grepl_is_a = grepl("a", alpha),
stringr_is_a = str_detect(alpha, "a"))
#> alpha grepl_is_a stringr_is_a
#> 1 alpha TRUE TRUE
#> 2 bet FALSE FALSE
#> 3 <NA> FALSE NA
mutate(alpha_dataset,
grepl_is_a = grepl("a", alpha),
stringr_is_a = str_detect(alpha, "a")) |>
collect()
#> alpha grepl_is_a stringr_is_a
#> 1 alpha TRUE TRUE
#> 2 bet FALSE FALSE
#> 3 <NA> NA NA
# base R grepl returns FALSE for NA
grepl("a", alpha_df$alpha) # bound to arrow_match_substring_regex
#> [1] TRUE FALSE FALSE
grepl("a", alpha_df$alpha, fixed = TRUE) # bound to arrow_match_substring
#> [1] TRUE FALSE FALSE
# stringr::str_dectect returns NA for NA
str_detect(alpha_df$alpha, "a")
#> [1] TRUE FALSE NA
alpha_array <- Array$create(alpha_df$alpha)
# arrow functions return null for null (NA)
call_function("match_substring_regex", alpha_array, options = list(pattern = "a"))
#> Array
#> <bool>
#> [
#> true,
#> false,
#> null
#> ]
call_function("match_substring", alpha_array, options = list(pattern = "a"))
#> Array
#> <bool>
#> [
#> true,
#> false,
#> null
#> ]
{code}
was:
The arrow binding to {{grepl}} behaves slightly differently than the base R {{{}grepl{}}}, in that it returns {{NA}} for {{NA}} inputs, whereas base {{grepl}} returns {{FALSE }}with{{ NA }}inputs. arrow's implementention is consistent with {{{}stringr::str_detect(){}}}, and both {{str_detect()}} and {{grepl()}} are bound to {{match_substring_regex}} and {{match_substring}} in arrow.
I don't know if this is something you would want to change so that the {{grepl}} behaviour aligns with base {{{}grepl{}}}, or simply document this difference?
Reprex:
{code:r}
library(arrow, warn.conflicts = FALSE, quietly = TRUE)
library(dplyr, warn.conflicts = FALSE, quietly = TRUE)
library(stringr, quietly = TRUE)
alpha_df <- data.frame(alpha = c("alpha", "bet", NA_character_))
alpha_dataset <- InMemoryDataset$create(alpha_df)
mutate(alpha_df,
grepl_is_a = grepl("a", alpha),
stringr_is_a = str_detect(alpha, "a"))
#> alpha grepl_is_a stringr_is_a
#> 1 alpha TRUE TRUE
#> 2 bet FALSE FALSE
#> 3 <NA> FALSE NA
mutate(alpha_dataset,
grepl_is_a = grepl("a", alpha),
stringr_is_a = str_detect(alpha, "a")) |>
collect()
#> alpha grepl_is_a stringr_is_a
#> 1 alpha TRUE TRUE
#> 2 bet FALSE FALSE
#> 3 <NA> NA NA
# base R grepl returns FALSE for NA
grepl("a", alpha_df$alpha) # bound to arrow_match_substring_regex
#> [1] TRUE FALSE FALSE
grepl("a", alpha_df$alpha, fixed = TRUE) # bound to arrow_match_substring
#> [1] TRUE FALSE FALSE
# stringr::str_dectect returns NA for NA
str_detect(alpha_df$alpha, "a")
#> [1] TRUE FALSE NA
alpha_array <- Array$create(alpha_df$alpha)
# arrow functions return null for null (NA)
call_function("match_substring_regex", alpha_array, options = list(pattern = "a"))
#> Array
#> <bool>
#> [
#> true,
#> false,
#> null
#> ]
call_function("match_substring", alpha_array, options = list(pattern = "a"))
#> Array
#> <bool>
#> [
#> true,
#> false,
#> null
#> ]
{code}
> [R] binding for grepl has different behaviour with NA compared to R base grepl
> ------------------------------------------------------------------------------
>
> Key: ARROW-16007
> URL: https://issues.apache.org/jira/browse/ARROW-16007
> Project: Apache Arrow
> Issue Type: Improvement
> Affects Versions: 7.0.0
> Reporter: Andy Teucher
> Priority: Minor
>
> The arrow binding to {{grepl}} behaves slightly differently than the base R {{{}grepl{}}}, in that it returns {{NA}} for {{NA}} inputs, whereas base {{grepl}} returns {{{}FALSE with \{{NA}}inputs. arrow's implementention is consistent with stringr::str_detect(){}}}, and both {{str_detect()}} and {{grepl()}} are bound to {{match_substring_regex}} and {{match_substring}} in arrow.
> I don't know if this is something you would want to change so that the {{grepl}} behaviour aligns with base {{{}grepl{}}}, or simply document this difference?
> Reprex:
>
> {code:r}
> library(arrow, warn.conflicts = FALSE, quietly = TRUE)
> library(dplyr, warn.conflicts = FALSE, quietly = TRUE)
> library(stringr, quietly = TRUE)
> alpha_df <- data.frame(alpha = c("alpha", "bet", NA_character_))
> alpha_dataset <- InMemoryDataset$create(alpha_df)
> mutate(alpha_df,
> grepl_is_a = grepl("a", alpha),
> stringr_is_a = str_detect(alpha, "a"))
> #> alpha grepl_is_a stringr_is_a
> #> 1 alpha TRUE TRUE
> #> 2 bet FALSE FALSE
> #> 3 <NA> FALSE NA
> mutate(alpha_dataset,
> grepl_is_a = grepl("a", alpha),
> stringr_is_a = str_detect(alpha, "a")) |>
> collect()
> #> alpha grepl_is_a stringr_is_a
> #> 1 alpha TRUE TRUE
> #> 2 bet FALSE FALSE
> #> 3 <NA> NA NA
> # base R grepl returns FALSE for NA
> grepl("a", alpha_df$alpha) # bound to arrow_match_substring_regex
> #> [1] TRUE FALSE FALSE
> grepl("a", alpha_df$alpha, fixed = TRUE) # bound to arrow_match_substring
> #> [1] TRUE FALSE FALSE
> # stringr::str_dectect returns NA for NA
> str_detect(alpha_df$alpha, "a")
> #> [1] TRUE FALSE NA
> alpha_array <- Array$create(alpha_df$alpha)
> # arrow functions return null for null (NA)
> call_function("match_substring_regex", alpha_array, options = list(pattern = "a"))
> #> Array
> #> <bool>
> #> [
> #> true,
> #> false,
> #> null
> #> ]
> call_function("match_substring", alpha_array, options = list(pattern = "a"))
> #> Array
> #> <bool>
> #> [
> #> true,
> #> false,
> #> null
> #> ]
> {code}
>
>
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