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Posted to jira@arrow.apache.org by "Antoine Pitrou (Jira)" <ji...@apache.org> on 2021/05/10 16:49:00 UTC

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

     [ https://issues.apache.org/jira/browse/ARROW-12083?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Antoine Pitrou resolved ARROW-12083.
------------------------------------
    Fix Version/s: 5.0.0
       Resolution: Fixed

Issue resolved by pull request 10284
[https://github.com/apache/arrow/pull/10284]

> [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
>            Assignee: David Li
>            Priority: Minor
>              Labels: pull-request-available
>             Fix For: 5.0.0
>
>          Time Spent: 40m
>  Remaining Estimate: 0h
>
> 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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