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This will do the necessary configuration to create a (virtual) table in DuckDB that is backed by the Arrow object given. No data is copied or modified until collect() or compute() are called or a query is run against the table.

Usage

to_duckdb(
  .data,
  con = arrow_duck_connection(),
  table_name = unique_arrow_tablename(),
  auto_disconnect = TRUE
)

Arguments

.data

the Arrow object (e.g. Dataset, Table) to use for the DuckDB table

con

a DuckDB connection to use (default will create one and store it in options("arrow_duck_con"))

table_name

a name to use in DuckDB for this object. The default is a unique string "arrow_" followed by numbers.

auto_disconnect

should the table be automatically cleaned up when the resulting object is removed (and garbage collected)? Default: TRUE

Value

A tbl of the new table in DuckDB

Details

The result is a dbplyr-compatible object that can be used in d(b)plyr pipelines.

If auto_disconnect = TRUE, the DuckDB table that is created will be configured to be unregistered when the tbl object is garbage collected. This is helpful if you don't want to have extra table objects in DuckDB after you've finished using them.

Examples

library(dplyr)

ds <- InMemoryDataset$create(mtcars)

ds %>%
  filter(mpg < 30) %>%
  group_by(cyl) %>%
  to_duckdb() %>%
  slice_min(disp)
#> # Source:   SQL [5 x 11]
#> # Database: DuckDB 0.8.1 [unknown@Linux 5.15.0-1042-azure:R 4.3.1/:memory:]
#> # Groups:   cyl
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  27.3     4   79     66  4.08  1.94  18.9     1     1     4     1
#> 2  19.7     6  145    175  3.62  2.77  15.5     0     1     5     6
#> 3  16.4     8  276.   180  3.07  4.07  17.4     0     0     3     3
#> 4  17.3     8  276.   180  3.07  3.73  17.6     0     0     3     3
#> 5  15.2     8  276.   180  3.07  3.78  18       0     0     3     3