Virtual attributes in Rails can be useful for eliminating N+1 queries, which often lead to slower requests and increase the need for premature scaling.

What Are N+1 Queries?

N+1 queries can occur whenever we have records with has_many associations that we lazy load in our application. When loading a set of records and then loading each of those records’ associated records, queries are issued for both the parent record and for every child record, thus generating N+1 queries. Doing this can potentially flood our database with queries, which is something we should avoid.

Recently, we ran into the N+1 query problem while working on a Rails API for a client project where we wanted to take in a geographic point and serve up a collection of resources, ordered by distance from that point, and also provide the distance for each resource in the collection. I’d like to share how we solved that problem using the #attribute method in Rails.

For the sake of illustration, let’s say we have a polling_location model, and we want to find our nearest polling_locations and calculate how far away each polling_location is from us. Using the PostGIS extension for PostgreSQL, we can query for all polling_locations ordered by distance by defining a method like this one:

This method takes longitude and latitude arguments and an optional distance_in_meters argument that defaults to an arbitrarily large number (large enough to span the United States in this example). The lonlat reference in the SQL string is a geography column on the polling_locations table. With this geographic data, we can use PostGIS’ ST_DWithin and ST_Distance functions to query for all of the polling_locations whose lonlat is within a given distance to the provided coordinates and return these ordered by distance.

Now we can call PollingLocation.near(lat, lon) to find our nearest polling_locations. Great! But we also want to know how far each one is from us. How do we do that? We might start by writing a method to calculate distance for each polling_location:

This distance method takes our coordinates and makes a SQL query using functions from PostGIS to calculate the distance in meters. Now we can call distance on a polling_location and see how far away it is. 😎

The above method works fine for a single polling_location instance, but we want our API to serve up all of our polling_locations near a given point and provide the calculated distance for every one. How can we do that? Well, we could call the distance method for every polling_location that is returned in our collection, but that would make a new SQL query for every object. Depending on how many records we have in our database, that could potentially mean thousands or hundreds of thousands of SQL queries for each API request. 😢 How can we do this without generating N+1 queries?

If we look closely at our code, we might notice that we are already doing the work of calculating distance in the ordering of the .near method. What would be great is if we could take that distance we’ve already calculated and return that along with each polling_location. Here’s where virtual attributes can help us.

Virtual Attributes To The Rescue

Using the #attribute method provided to us by Rails, we can add a virtual attribute to our model, which means an attribute with no database column backing it. Let’s call ours distance_in_meters and give it a type of float:

With this in place, we can chain a .select method to the query in our .near method, taking the distance we’ve calculated and setting it dynamically as distance_in_meters on our model:

Now, when we call PollingLocation.near(lat, lon), we get all of the polling_locations ordered by distance, and each has a distance_in_meters attribute that shows how many meters away each polling_location is — all in a single SQL query!

We could leave this is as, but if we wanted to go one step further and serve up the distance in another unit of length, such as miles, we could define a distance conversion method on our PollingLocationSerializer:

Now, let’s take a look at our new PollingLocation model:

With the help of Rails virtual attributes, we were able to arrive at a solution that avoids N+1 queries and helps us find our nearest polling locations more quickly. 🎉

Special thanks to Dave Kroondyk, who helped me work out this solution and provided feedback on this blog post.