# Adding a new DBI backend

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

- Ensure that you have a DBI compliant database backend. If not, you’ll need to first create it by following the instructions in `vignette("backend", package = "DBI")`.

- You’ll need a working knowledge of S3. Make sure that you’re familiar with the basics before you start.

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.

    library(dplyr)
    library(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 3.34.1 []
    #>     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
    #> # … with 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:

- If `copy_to()` fails, you probably need a method for `sql_table_analyze()` or `sql_table_index()`. If `copy_to()` fails during creation of the tbl, you may need a method for `sql_query_fields()`.

- If `collapse()` fails, your database has a non-standard way of constructing subqueries. Add a method for `sql_subquery()`.

- If `compute()` fails, your database has a non-standard way of saving queries in temporary tables. Add a method for `db_save_query()`.

## 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:

- `summarise()`, `mutate()`, `filter()` etc: powered by `sql_query_select()`
- `left_join()`, `inner_join()`: powered by `sql_query_join()`
- `semi_join()`, `anti_join()`: powered by `sql_query_semi_join()`
- `union()`, `intersect()`, `setdiff()`: powered by `sql_query_set_op()`

### 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.