[jira] [Commented] (ARROW-12083) [R] schema use in open_dataset

["Neal Richardson (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-12083?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17309006#comment-17309006 ] 

Neal Richardson commented on ARROW-12083:
-----------------------------------------

cc [~bkietz] [~lidavidm] 

It's true that this works differently from how single file reading works. 

This is also the motivating use case behind ARROW-11589 ([~jonkeane]): open_dataset once to detect schema, then modify the Schema object and use it to open_dataset with declared schema.

> [R] schema use in open_dataset
> ------------------------------
>
>                 Key: ARROW-12083
>                 URL: https://issues.apache.org/jira/browse/ARROW-12083
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: R
>    Affects Versions: 3.0.0
>         Environment: Windows
>            Reporter: Shaun Nielsen
>            Priority: Minor
>
> I have a directory of split .csvs that I'm importing with open_dataset(). Between files, a column is imported as either int64 (e.g. -2) and the other string (1986CD), and this throws an error when {{unify_schemas = T}}
> {{ arrow::open_dataset('./split-csvs/nswcr/', format = 'csv', unify_schemas = T)}}
> {{Error: Invalid: Unable to merge: Field SEIFACalcMethod has incompatible types: int64 vs string}}
> If I use the schema parameter, and only want to specify this column, I only am able to import this column
> {{arrow::open_dataset('./split-csvs/nswcr/', }}{{format = 'csv', }}{{schema = schema(SEIFACalcMethod = string()))}}
> {{ }}
> {{FileSystemDataset with 45 csv files}}
> {{SEIFACalcMethod: string}}
> I was expecting that could set the class of a select few columns, while the rest would be imported as-is. Similar to readr::read_csv(col_types = cols()) approach.
> Not sure if this is expected behaviour, a bug, or a possible avenue for improvement. I've tagged this as the latter. (y)
>  



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