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
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 v0.9.2 [unknown@Linux 6.2.0-1018-azure:R 4.3.2/: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