Prevent Scaling Issues With GraphQL Data Loaders
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Learn how to optimize your GraphQL API performance and solve scaling issues with the GraphQL Data Loader pattern. Improve efficiency and get started now!
Most developers would raise an eyebrow if they saw database queries being done in a for-loop, but GraphQL provides just enough abstraction that it isn’t always intuitive exactly how many times each resolver fires at scale, nor is it obvious how to batch operations efficiently and still return the correct results to the correct consumer
You’ll learn how to use the GraphQL Data Loader pattern to improve the performance of your application, and solve scaling issues before they become a problem.
To do this, we’ll first implement our own naive version of the pattern to understand why the API is shaped how it is. Then we will switch over to the official DataLoader package and explore the benefits further.
With just a couple of clicks, you’ll be able to set up a Gitpod to follow along and optimize a GraphQL API as you work through the course. Navigate to the GitHub Repository and get started!
Course Content
Detect Scaling Issues When Loading Data In a GraphQL API
Cache Database Requests Across GraphQL Resolvers
Batch Database Requests with a GraphQL API
Refactor the Data Loader into a Reusable Class
Create a New Cache on Every GraphQL Request Using Apollo Context
Install the DataLoader Package
Fetching an Item by ID with a GraphQL DataLoader
Fetching Many Items by Key with GraphQL DataLoaders
Count the Items in a Collection By Reusing a Data Loader
Count the Items in a Collection with a Custom Data Loader
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