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https://issues.apache.org/jira/browse/ARROW-11243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17264465#comment-17264465
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Neal Richardson commented on ARROW-11243:
-----------------------------------------
Thanks. The error message comes from
https://github.com/apache/arrow/blob/master/cpp/src/arrow/csv/converter.cc#L621,
and it's true, there is no case defined for Type::TIME32. There also is no
cast method to convert/parse the string to time32 after the fact.
I'll split to a separate issue the date vs. datetime type inference.
> Cannot use time32() in col_types=schema() when reading CSV with
> read_csv_arrow()
> --------------------------------------------------------------------------------
>
> Key: ARROW-11243
> URL: https://issues.apache.org/jira/browse/ARROW-11243
> Project: Apache Arrow
> Issue Type: Bug
> Components: R
> Affects Versions: 2.0.0
> Environment: Ubuntu 18.04, R 4.0.3
> Reporter: Jared Lander
> Priority: Minor
> Attachments: sampletimedata.csv
>
>
> When reading a CSV with read_csv_arrow() with date types and time types, the
> dates are read as datetimes rather than dates and times are read as
> characters rather than time.
> The first problem can be fixed by supplying date32() to schema(), though
> better inference would be nice. However, supplying time32() to schema()
> causes an error.
> Here is a sample dataset, also attached.
> date,time,reading
> 2021-01-01,00:00:00,67.8
> 2021-01-01,00:00:00,72.4
> 2021-01-01,00:00:00,63.1
> 2021-01-01,00:05:00,67.8
> Reading with readr::read_csv() results in a tibble with three columns: date,
> time, dbl, as expected.
>
> {code:r}
> samp_readr <- readr::read_csv('sampledata.csv')
> samp_readr
> {code}
> {code:r}
> # A tibble: 4 x 3
> date time reading
> <date> <time> <dbl>
> 1 2021-01-01 00'00" 67.8
> 2 2021-01-01 00'00" 72.4
> 3 2021-01-01 00'00" 63.1
> 4 2021-01-01 05'00" 67.8
> {code}
> Reading with arrow::read_csv_arrow() without providing schema() results in a
> tibble with three columns: dttm, chr, dbl.
> {code:r}
> samp_arrow_plain <- arrow::read_csv_arrow('sampledata.csv')
> samp_arrow_plain
> {code}
> {code:r}
> # A tibble: 4 x 3
> date time reading
> <dttm> <chr> <dbl>
> 1 2020-12-31 19:00:00 00:00:00 67.8
> 2 2020-12-31 19:00:00 00:00:00 72.4
> 3 2020-12-31 19:00:00 00:00:00 63.1
> 4 2020-12-31 19:00:00 00:05:00 67.8
> {code}
> Reading with arrow::read_csv_arrow() and providing date=date32() via schema()
> to col_types results in a tibble with three columns: date, chr, dbl.
> {code:r}
> samp_arrow_date <- arrow::read_csv_arrow('sampledata.csv',
> col_types=schema(date=date32()))
> samp_arrow_date
> {code}
> {code:r}
> # A tibble: 4 x 3
> date time reading
> <date> <chr> <dbl>
> 1 2021-01-01 00:00:00 67.8
> 2 2021-01-01 00:00:00 72.4
> 3 2021-01-01 00:00:00 63.1
> 4 2021-01-01 00:05:00 67.8
> {code}
> Reading with arrow::read_csv_arrow() and providing time=time32() via schema()
> to col_types generates an error.
> {code:r}
> samp_arrow_time <- arrow::read_csv_arrow('sampledata.csv',
> col_types=schema(time=time32()))
> {code}
> {code:r}
> Error in csv___TableReader__Read(self) :
> NotImplemented: CSV conversion to time32[ms] is not supported
> {code}
> The same error occurs when using compact string notation.
> {code:r}
> samp_arrow_string <- arrow::read_csv_arrow('sampledata.csv', col_types='DTc',
> col_names=c('date', 'time', 'reading'), skip=1)
> {code}
> {code:r}
> Error in csv___TableReader__Read(self) :
> NotImplemented: CSV conversion to time32[ms] is not supported
> {code}
> This is something in the internals, so far beyond me to figure out a fix, but
> I saw it in action and wanted to report it.
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