Joining the flock from R: working with data on MotherDuck

With DuckDB releasing version 1.0.0 on June 3rd, and MotherDuck following with the general availability announcement on June 11th, it is a perfect opportunity to see how both can be used from R. I work for an organization where R is the default language for doing most of the analytics, so being able to do this is more than just simple curiosity.

My setup

I am running R version 4.4.1 on Linux, with duckdb version 1.0.0.

I have python version 3.12, and I am installing duckb 1.0.0 in a virtual environment.

I installed the duckdb version 1.0.0 binary as well, and installed the motherduck extension.

And, of course, I also have created an account on MotherDuck.

Running duckdb in R

This has been probably covered many times so far. Nevertheless, for completeness, running duckdb in R is fairly straight forward:

# Connect to an in-memory DuckDB database
con <- dbConnect(duckdb::duckdb(), ":memory:")
# Write the Iris dataset to the DuckDB in-memory database
dbWriteTable(con, "iris", iris)
# Query data from the DuckDB database
data <- dbGetQuery(con, "SELECT * FROM iris")

Of course, there is the possibility of doing things with duckplyr, but we are not going to go into that.

Connecting to MotherDuck

MotherDuck documentation has details about connecting to MotherDuck using python, but not for connecting using R.

After asking a few questions on the discord, I learned that the process should be similar.

Let’s see how that looks.

Python

In a Python 3.12 virtual environment, that has duckdb-1.0.0, getting to MotherDuck is simple, in fact as the documentation says:

import duckdb
# connect to MotherDuck using 'md:' or 'motherduck:'
con = duckdb.connect('md:')

The above results in getting a notification on the terminal:

Attempting to automatically open the SSO authorization page in your default browser.
1. Please open this link to login into your account: https://auth.motherduck.com/activate
2. Enter the following code: XXXX-XXXX

Nothing else is required here. We click in the browser, establish a connection, get a token, etc.

R

However, doing the same with R doesn’t have the same outcome:

con <- DBI::dbConnect(duckdb::duckdb(), "md:")

Creates a local database called md::

ls -lh md\:
-rw-r--r-- 1 novica novica 12K jun 21 10:32 md:

My best guess here is that the duckdb package for R does not automatically figure out that it should load the motherduck extension, as is probably the case in python.

The approach in R is then similar to what is suggested in the section Connecting to MotherDuck after opening a local DuckDB database:

# Create a local database
con <- DBI::dbConnect(duckdb::duckdb(), "local.duckdb")
# Note: Installing the extension is not nececsary here since
# I already have it installed on my system. However, if you don't want
# to go to the trouble of installing the duckdb binary and then installing
# extensions, then it is possible to do the installation here before
# loading with:
# DBI::dbExecute(con, "INSTALL 'motherduck';")
# Load the Mother Duck extension
DBI::dbExecute(con, "LOAD 'motherduck';")
# Verify that the extension is loaded
DBI::dbGetQuery(
con,
"SELECT extension_name, loaded, installed FROM duckdb_extensions() WHERE
extension_name = 'motherduck'"
)
# Connect to MotherDuck
DBI::dbExecute(con, "PRAGMA MD_CONNECT")

At which point the message for authenticating in the browser shows up in the terminal.

After approving the connection, as the friendly message says, the token can be stored in an environment variable to avoid having to log in again.

Then it is a simple matter of querying things on MotherDuck:

# Query the sample data about air quality that is avaiable on MotherDuck
DBI::dbGetQuery(
con,
"SELECT country_name, city, \"year\", pm10_concentration, pm25_concentration, no2_concentration, FROM sample_data.who.ambient_air_quality WHERE city = 'Skopje' OR city = 'Oslo';"
)

Note that we have to specify the database name: sample_data, and the schema: who to query the data on MotherDuck.

The results can be assigned to an object in R, which I did. And since it is always fun to make a plot, here is how it looks for the two cities where I spend most of my time.

And, that’s a wrap. I mean, a quack. 🙂