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  1. Apache Arrow
  2. ARROW-11243

[C++] Parse time32 from string and infer in CSV reader

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    Details

    • Type: Improvement
    • Status: Open
    • Priority: Minor
    • Resolution: Unresolved
    • Affects Version/s: 2.0.0
    • Fix Version/s: 5.0.0
    • Component/s: C++
    • Labels:
      None
    • Environment:
      Ubuntu 18.04, R 4.0.3

      Description

      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.
       

      samp_readr <- readr::read_csv('sampledata.csv')
      samp_readr
      
      # 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
      

      Reading with arrow::read_csv_arrow() without providing schema() results in a tibble with three columns: dttm, chr, dbl.

      samp_arrow_plain <- arrow::read_csv_arrow('sampledata.csv')
      samp_arrow_plain
      
      # 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
      

      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.

      samp_arrow_date <- arrow::read_csv_arrow('sampledata.csv', col_types=schema(date=date32()))
      samp_arrow_date
      
      # 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
      

      Reading with arrow::read_csv_arrow() and providing time=time32() via schema() to col_types generates an error.

      samp_arrow_time <- arrow::read_csv_arrow('sampledata.csv', col_types=schema(time=time32()))
      
      Error in csv___TableReader__Read(self) : 
        NotImplemented: CSV conversion to time32[ms] is not supported
      

      The same error occurs when using compact string notation.

      samp_arrow_string <- arrow::read_csv_arrow('sampledata.csv', col_types='DTc', col_names=c('date', 'time', 'reading'), skip=1)
      
      Error in csv___TableReader__Read(self) : 
        NotImplemented: CSV conversion to time32[ms] is not supported
      

      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.

        Attachments

        1. sampletimedata.csv
          0.1 kB
          Jared Lander

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              • Assignee:
                Unassigned
                Reporter:
                jaredlander Jared Lander
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                Dates

                • Created:
                  Updated: