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Posted to jira@arrow.apache.org by "Ben Kietzman (Jira)" <ji...@apache.org> on 2021/01/07 20:54:00 UTC
[jira] [Commented] (ARROW-10485) open_dataset(): specifying
partition when hive_style =TRUE fails silently
[ https://issues.apache.org/jira/browse/ARROW-10485?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17260817#comment-17260817 ]
Ben Kietzman commented on ARROW-10485:
--------------------------------------
To be clear: the issue here stems from the dataset-on-disk being hive-partitioned, so directories look like /{{cyl=4/part-0.parquet}}. When reading with a *directory* partitioning (which what results when a character vector is specified), this results in string values like "cyl=4" for field "cyl"; obviously suspect to a human but technically valid. If you construct a {{HivePartitioning}} explicitly this issue should not arise
> open_dataset(): specifying partition when hive_style =TRUE fails silently
> -------------------------------------------------------------------------
>
> Key: ARROW-10485
> URL: https://issues.apache.org/jira/browse/ARROW-10485
> Project: Apache Arrow
> Issue Type: Bug
> Components: R
> Affects Versions: 2.0.0
> Environment: MacOS Catalina 10.15.7 (19H2), R 4.01, arrow R package v2.0.0
> Reporter: John Sheffield
> Assignee: Ben Kietzman
> Priority: Minor
>
> When writing a dataset with hive_style = TRUE, now the default, that dataset has to be opened without an explicit definition of the partitions to work as expected. Even if the correct partition is specified, any query to the dataset on the partition field returns 0 rows.
>
> From my eyes as a user, I'd want this to error out specifically (not just warn), probably when first calling open_dataset().
> {code:r}
> data("mtcars")
> arrow::write_dataset(
> dataset = mtcars, path = "mtcarstest", partitioning = "cyl",
> format = "parquet", hive_style = TRUE)
> mtc1 <- arrow::open_dataset("mtcarstest", partitioning = "cyl")
> mtc2 <- arrow::open_dataset("mtcarstest")
> mtc1 %>%
> dplyr::filter(cyl == 4) %>%
> collect()
> mtc2 %>%
> dplyr::filter(cyl == 4) %>%
> collect()
> {code}
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