[jira] [Updated] (ARROW-15879) [R] passing a schema calls open_dataset to fail on hive-partitioned csv files

["Nicola Crane (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-15879?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nicola Crane updated ARROW-15879:
---------------------------------
    Summary: [R] passing a schema calls open_dataset to fail on hive-partitioned csv files  (was: passing a schema calls open_dataset to fail on hive-partitioned csv files)

> [R] passing a schema calls open_dataset to fail on hive-partitioned csv files
> -----------------------------------------------------------------------------
>
>                 Key: ARROW-15879
>                 URL: https://issues.apache.org/jira/browse/ARROW-15879
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: R
>    Affects Versions: 7.0.0, 7.0.1
>            Reporter: Carl Boettiger
>            Priority: Major
>
> Consider this reprex:
>  
> Create a dataset with hive partitions in csv format with write_dataset() (so cool!):
>  
> {code:java}
> library(arrow)
> library(dplyr)
> path <- fs::dir_create("tmp")
> mtcars %>% group_by(gear) %>% write_dataset(path, format="csv")## works fine, even with 'collect()'
> ds <- open_dataset(path, format="csv")## but pass a schema, and things fail
> df <- open_dataset(path, format="csv", schema = ds$schema, skip_rows=1)
> df %>% collect()
>  {code}
> In the first call to open_dataset, we don't pass a schema and things work as expected. 
> However, csv files often need a schema to be read in correctly, particularly with partitioned data where it is easy to 'guess' the wrong type.  Passing the schema though confuses open_dataset, because the grouping column (partition column) isn't found on the individual files even though it is mentioned in the schema!
> Nor can we just omit the grouping column from the schema, since then it is effectively lost from the data. 



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