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https://issues.apache.org/jira/browse/ARROW-17886?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17625280#comment-17625280
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Nicola Crane commented on ARROW-17886:
--------------------------------------
Closing this as I believe that this is covered by the changes made in
ARROW-12105, but if not, please let me know.
> [R] Convert schema to the corresponding ptype (zero-row data frame)?
> --------------------------------------------------------------------
>
> Key: ARROW-17886
> URL: https://issues.apache.org/jira/browse/ARROW-17886
> Project: Apache Arrow
> Issue Type: Improvement
> Components: R
> Reporter: Kirill Müller
> Priority: Minor
>
> When fetching data e.g. from a RecordBatchReader, I would like to know, ahead
> of time, what the data will look like after it's converted to a data frame. I
> have found a way using utils::head(0), but I'm not sure if it's efficient in
> all scenarios.
> My use case is the Arrow extension to DBI, in particular the default
> implementation for drivers that don't speak Arrow yet. I'd like to know which
> types the columns should have on the database. I can already infer this from
> the corresponding R types, but those existing drivers don't know about Arrow
> types.
> Should we support as.data.frame() for schema objects? The semantics would be
> to return a zero-row data frame with correct column names and types.
> library(arrow)
> #> Some features are not enabled in this build of Arrow. Run `arrow_info()`
> for more information.
> #>
> #> Attaching package: 'arrow'
> #> The following object is masked from 'package:utils':
> #>
> #> timestamp
> data <- data.frame(
> a = 1:3,
> b = 2.5,
> c = "three",
> stringsAsFactors = FALSE
> )
> data$d <- blob::blob(as.raw(1:10))
> tbl <- arrow::as_arrow_table(data)
> rbr <- arrow::as_record_batch_reader(tbl)
> tibble::as_tibble(head(rbr, 0))
> #> # A tibble: 0 × 4
> #> # … with 4 variables: a <int>, b <dbl>, c <chr>, d <blob>
> rbr$read_table()
> #> Table
> #> 3 rows x 4 columns
> #> $a <int32>
> #> $b <double>
> #> $c <string>
> #> $d <<blob[0]>>
> #>
> #> See $metadata for additional Schema metadata
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