R offers excellent facilities for working interactively with SQL databases on a remote server. It becomes more challenging to do so in a self-contained Quarto document, especially if you wish to be able to render it without running into errors. Fortunately, there are ways around these challenges.

The first step is establishing an SSH connection with the remote server on which your database is running, allowing you to interact with the database as though it were running on your own device. In an interactive session you could use the following code to establish an SSH connection and open a tunnel. The ssh_tunnel function will run indefinitely, leaving you unable to execute other code, but you can open a second R session and communicate with the database in that second session.

```{r}
session <- ssh::ssh_connect("[email protected]")
ssh::ssh_tunnel(session, port = 3305, 
         target = "localhost:3306")
```

In the example above we map port 3306 on the remote server (the default port for MySQL) to port 3305 on our local machine. You will often want to use the same port on the local machine, but I find it is easier to keep track of examples where different values are used.

In a Quarto document you will need to run the SSH tunnel in the background. This is made easy with the callr package. The example below will run the SSH tunnel in a separate background process.

```{r}
rbg <- callr::r_bg(\() {
  session <- ssh::ssh_connect("[email protected]")
  ssh::ssh_tunnel(session, port = 3305, 
           target = "localhost:3306")
})
```

You can now open a connection to the database as though it were running on your local machine on port 3305. Given that the SSH tunnel is opened in a separate process, I often find that if you attempt to connect to the database
directly after opening the tunnel you will encounter an error. To prevent this, I use Sys.sleep() to add a delay and allow the SSH tunnel to finish connecting before establishing the connection to the database.

It is easiest and safest to manage your database connections with a configuration file. Typically these are stored in a user directory, but I prefer to create them on a per-project basis.

.my.cnf

[groupname]
database="mydatabase"
host="localhost"
port="3305"
user="username"
password="mypassword"

You can use the a conf file setup like above to connect to the database.

```{r}
con <- DBI::dbConnect(RMySQL::MySQL(), 
                 group = "groupname", 
                 default.file = ".my.cnf")
```

You can now access the database using DBI in R.

If you are already an experienced SQL user, you can write SQL directly in Quarto using your established connection. The ability to switch between R, Python, and even Julia is marketed quite heavily by the Posit team, while this SQL functionality seems much more obscure.

```{sql}
#| connection: "con"
select * from mytable;
```

You can even output of an SQL query to an R object, in this example named df, allowing you to seamlessly integrate SQL queries and R code.

```{sql}
#| connection: "con"
#| output.var: "df"
select * from mytable;
```

You should now be set to query with confidence.