eitsupi commented on issue #34589:
URL: https://github.com/apache/arrow/issues/34589#issuecomment-1472233438

   Is this perhaps related to the need to skip the header row when specifying 
schema in `read_csv_arrow`?
   https://arrow.apache.org/docs/r/reference/read_delim_arrow.html#ref-examples
   
   For CSV files, `col_types` should be used to change the type of a particular 
column.
   
   ``` r
   readr::readr_example("mtcars.csv") |>
     arrow::read_csv_arrow(schema = arrow::schema(cyl = arrow::utf8()))
   #> Error:
   #> ! Invalid: CSV parse error: Expected 1 columns, got 11: 
"mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb"
   
   #> Backtrace:
   #>     ▆
   #>  1. └─arrow (local) `<fn>`(...)
   #>  2.   └─base::tryCatch(...)
   #>  3.     └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   #>  4.       └─base (local) tryCatchOne(expr, names, parentenv, 
handlers[[1L]])
   #>  5.         └─value[[3L]](cond)
   #>  6.           └─arrow:::augment_io_error_msg(e, call, schema = schema)
   #>  7.             └─rlang::abort(msg, call = call)
   
   readr::readr_example("mtcars.csv") |>
     arrow::open_dataset(schema = arrow::schema(cyl = arrow::utf8()), format = 
"csv") |>
     dplyr::collect()
   #> Error in `compute.Dataset()`:
   #> ! Invalid: Could not open CSV input source 
'/usr/local/lib/R/site-library/readr/extdata/mtcars.csv': Invalid: CSV parse 
error: Row #1: Expected 1 columns, got 11: 
"mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb"
   
   #> Backtrace:
   #>      ▆
   #>   1. ├─dplyr::collect(...)
   #>   2. └─arrow:::collect.Dataset(...)
   #>   3.   ├─arrow:::collect.ArrowTabular(compute.Dataset(x), as_data_frame)
   #>   4.   │ └─base::as.data.frame(x, ...)
   #>   5.   └─arrow:::compute.Dataset(x)
   #>   6.     └─base::tryCatch(...)
   #>   7.       └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   #>   8.         └─base (local) tryCatchOne(expr, names, parentenv, 
handlers[[1L]])
   #>   9.           └─value[[3L]](cond)
   #>  10.             └─arrow:::augment_io_error_msg(e, call, schema = 
schema())
   #>  11.               └─rlang::abort(msg, call = call)
   
   readr::readr_example("mtcars.csv") |>
     arrow::read_csv_arrow(col_types = arrow::schema(cyl = arrow::utf8()))
   #> # A tibble: 32 × 11
   #>      mpg cyl    disp    hp  drat    wt  qsec    vs    am  gear  carb
   #>    <dbl> <chr> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
   #>  1  21   6      160    110  3.9   2.62  16.5     0     1     4     4
   #>  2  21   6      160    110  3.9   2.88  17.0     0     1     4     4
   #>  3  22.8 4      108     93  3.85  2.32  18.6     1     1     4     1
   #>  4  21.4 6      258    110  3.08  3.22  19.4     1     0     3     1
   #>  5  18.7 8      360    175  3.15  3.44  17.0     0     0     3     2
   #>  6  18.1 6      225    105  2.76  3.46  20.2     1     0     3     1
   #>  7  14.3 8      360    245  3.21  3.57  15.8     0     0     3     4
   #>  8  24.4 4      147.    62  3.69  3.19  20       1     0     4     2
   #>  9  22.8 4      141.    95  3.92  3.15  22.9     1     0     4     2
   #> 10  19.2 6      168.   123  3.92  3.44  18.3     1     0     4     4
   #> # … with 22 more rows
   
   readr::readr_example("mtcars.csv") |>
     arrow::open_dataset(col_types = arrow::schema(cyl = arrow::utf8()), format 
= "csv") |>
     dplyr::collect()
   #> # A tibble: 32 × 11
   #>      mpg cyl    disp    hp  drat    wt  qsec    vs    am  gear  carb
   #>    <dbl> <chr> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
   #>  1  21   6      160    110  3.9   2.62  16.5     0     1     4     4
   #>  2  21   6      160    110  3.9   2.88  17.0     0     1     4     4
   #>  3  22.8 4      108     93  3.85  2.32  18.6     1     1     4     1
   #>  4  21.4 6      258    110  3.08  3.22  19.4     1     0     3     1
   #>  5  18.7 8      360    175  3.15  3.44  17.0     0     0     3     2
   #>  6  18.1 6      225    105  2.76  3.46  20.2     1     0     3     1
   #>  7  14.3 8      360    245  3.21  3.57  15.8     0     0     3     4
   #>  8  24.4 4      147.    62  3.69  3.19  20       1     0     4     2
   #>  9  22.8 4      141.    95  3.92  3.15  22.9     1     0     4     2
   #> 10  19.2 6      168.   123  3.92  3.44  18.3     1     0     4     4
   #> # … with 22 more rows
   ```
   
   <sup>Created on 2023-03-16 with [reprex 
v2.0.2](https://reprex.tidyverse.org)</sup>
   
   If the schema option is used for Parquet files, only that columns will be 
read.
   
   ``` r
   readr::readr_example("mtcars.csv") |>
     readr::read_csv(show_col_types = FALSE) |>
     arrow::write_parquet("test.parquet")
   
   arrow::open_dataset("test.parquet", schema = arrow::schema(cyl = 
arrow::utf8())) |>
     dplyr::collect()
   #> # A tibble: 32 × 1
   #>    cyl
   #>    <chr>
   #>  1 6
   #>  2 6
   #>  3 4
   #>  4 6
   #>  5 8
   #>  6 6
   #>  7 8
   #>  8 4
   #>  9 4
   #> 10 6
   #> # … with 22 more rows
   ```
   
   <sup>Created on 2023-03-16 with [reprex 
v2.0.2](https://reprex.tidyverse.org)</sup>


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