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This document describes how to add a new SQL backend to dbplyr. To begin:

This document is still a work in progress, but it will hopefully get you started. I’d also strongly recommend reading the bundled source code for SQLite, MySQL, and PostgreSQL.

First steps

For interactive exploitation, attach dplyr and DBI. If you’re creating a package, you’ll need to import dplyr and DBI.

Check that you can create a tbl from a connection, like:

con <- DBI::dbConnect(RSQLite::SQLite(), path = ":memory:")
DBI::dbWriteTable(con, "mtcars", mtcars)

tbl(con, "mtcars")
#> # Source:   table<`mtcars`> [?? x 11]
#> # Database: sqlite 3.47.1 []
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 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
#> # ℹ more rows

If you can’t, this likely indicates some problem with the DBI methods. Use DBItest to narrow down the problem.

Write your first method

The first method of your dbplyr backend should always be for the dbplyr_edition() generic:

#' @importFrom dbplyr dbplyr_edition
#' @export
dbplyr_edition.myConnectionClass <- function(con) 2L

This declares that your package uses version 2 of the API, which is the version that this vignette documents.

Copying, computing, collecting and collapsing

Next, check that copy_to(), collapse(), compute(), and collect() work:

SQL translation

Make sure you’ve read vignette("translation-verb") so you have the lay of the land.

Verbs

Check that SQL translation for the key verbs work:

Vectors

Finally, you may have to provide custom R -> SQL translation at the vector level by providing a method for sql_translate_env(). This function should return an object created by sql_variant(). See existing methods for examples.