Overview
It's time to introduce data loaders to our application.
In this lesson, we will:
- Implement the
DataLoader
class with a batching function - Update our
getAmenities
method to pass each listing ID to the data loader - Test out our new data loading capability
Adding the data loader
Let's bring the dataloader
package into our application. Open up a new terminal in the root of your project, and run the following command.
npm install --save dataloader
Next, we'll jump to our ListingAPI
class. Here, we'll introduce a new method that does the following:
- Creates a new
DataLoader
- Provides a batching function that gathers
listingIds
and makes a single request to the REST API
At the top of the file, bring in DataLoader
from the dataloader
package.
import DataLoader from "dataloader";
Inside of our ListingAPI
class, let's set up a new private
field for our data loader instantiation. This will make it accessible only from within this same class.
private batchAmenities = new DataLoader()
The DataLoader
constructor accepts a batch loading function, which we'll define in-line. This batch function accepts an array of keys, and returns a Promise that resolves to an array of values. For the array of keys, we'll set a parameter called listingIds
, and we can add our return type annotation as well: Promise<Amenity[][]>
.
private batchAmenities = new DataLoader((listingIds): Promise<Amenity[][]> => {// TODO})
Next, we'll make this function async
, and await
the results of calling our REST endpoint, GET /amenities/listings
.
private batchAmenities = new DataLoader(async (listingIds): Promise<Amenity[][]> => {await this.get<Amenity[][]>("amenities/listings");});
This endpoint expects a query parameter called ids
, a comma-separated string of listing IDs. We'll add this as a second argument to the this.get
function, an object with a params
property, passing in another object with the query parameter ids
. Because our data loader receives its listingIds
as an array, we'll use the join
method, specifying a comma as the separator for each value.
private batchAmenities = new DataLoader(async (listingIds): Promise<Amenity[][]> => {await this.get<Amenity[][]>("amenities/listings", {params: {ids: listingIds.join(","),},});});
Finally, let's capture the results of calling our endpoint in a new constant called amenitiesLists
, then return the results.
private batchAmenities = new DataLoader(async (listingIds): Promise<Amenity[][]> => {const amenitiesLists = await this.get<Amenity[][]>("amenities/listings", {params: {ids: listingIds.join(","),},});return amenitiesLists;});
Before we move on, let's add a couple of log statements so that we can keep an eye on how our method is working. We'll log out the list of listingIds
passed into our data loader, and the amenitiesLists
results.
private batchAmenities = new DataLoader(async (listingIds): Promise<Amenity[][]> => {console.log("Making one batched call with ", listingIds);const amenitiesLists = await this.get<Amenity[][]>("amenities/listings", {params: {ids: listingIds.join(","),},});console.log(amenitiesLists);return amenitiesLists;});
That's our data loader method taken care of; now we need to call it from inside this class.
Updating getAmenities
Scrolling down in our class, we'll find the getAmenities
method that our Listing.amenities
resolver has historically called.
Rather than calling the GET /listings/:id/amenities
endpoint for each listing, we'll update our method to instead pass each listing ID it receives to the data loader. We can do this by calling load
on our private field, batchAmenities
.
getAmenities(listingId: string): Promise<Amenity[]> {console.log("Making a follow-up call for amenities with ", listingId);- return this.get<Amenity[]>(`listings/${listingId}/amenities`);+ return this.batchAmenities.load(listingId);}
Let's also update the log statement here: rather than reporting that we're making a follow-up request, let's change the wording so it's clear that we're passing a particular listing ID to the data loader.
getAmenities(listingId: string): Promise<Amenity[]> {- console.log("Making a follow-up call for amenities with ", listingId);+ console.log("Passing listing ID to the data loader: ", listingId);return this.batchAmenities.load(listingId);}
That's it for our data source class! And we have no changes to make to our resolver: it will continue to call the getAmenities
method, which will delegate the responsibility for batching together and loading data for all the listing IDs requested in a single query. Let's test it out!
Testing the data loader
Make sure that your server is still running, and let's jump back to Sandbox.
We'll run the same query again for featured listings and their amenities.
query GetFeaturedListingsAmenities {featuredListings {idtitleamenities {idnamecategory}}}
When we execute the query, we get data just like before! But let's check on what happened under the hood, back in our terminal.
First, we'll see three lines: one for each listing ID involved in our featured listings request.
Passing listing ID to the data loader: listing-1Passing listing ID to the data loader: listing-2Passing listing ID to the data loader: listing-3
These lines are followed by output from our single batched call:
Making one batched call with [ 'listing-1', 'listing-2', 'listing-3' ]
After that we should see one big array printed out: it contains multiple smaller arrays, each of which contains multiple amenities! These are the amenity lists for each of our requested listing IDs. Our listing IDs have successfully been batched together in a single request! 👏👏👏
Practice
Key takeaways
- We create a new
DataLoader
per request, passing into its constructor a batching function that receives an array of keys and returns an array of values. - To actually use a data loader, we call its
load
method and pass in each key. - The GraphQL
dataloader
package comes with caching benefits, and will deduplicate the keys it makes requests for.
Congratulations!
And with that, you've done it! You've tackled the n+1 problem—with data loaders in your toolbelt, you have the resources to boost your app's efficiency. We've taken a basic data fetching strategy in our application, and made it into something that can scale with our queries and features. By employing data loaders, we've seen how we can make fewer, more efficient requests across the network, delivering up data much faster than we ever could have before.
Next up: learn how to grow your GraphQL API with an entirely new domain in Federation with Apollo Server & TypeScript. We'll cover the best practices of building a federated graph, along with the GraphOS tools you'll use to make the path toward robust enterprise APIs smooth, observable, and performant!
Thanks for joining us in this course, and we can't wait to see you in the next.
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