Use GraphQL Data Loaders to Prevent Scaling Issues by Batching & Caching Database Requests
Learn the basics of Use GraphQL Data Loaders to Prevent Scaling Issues by Batching & Caching Database Requests ▼
ADVERTISEMENT
Course Feature
Cost:
Free
Provider:
egghead.io
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from egghead.io platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
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.
Follow Along
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!
Check out the Gitpod here!
Skills you'll Gain
Implement a cache layer to optimize your requests
Batch requests so your Database isn't overloaded
Build a performant GraphQL API
(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
GraphQL Data Loaders is a powerful tool for developers to optimize their applications and prevent scaling issues. This course will teach learners how to use the GraphQL Data Loader pattern to improve the performance of their application and solve scaling issues before they become a problem. Learners will gain the skills to implement a cache layer to optimize their requests, batch requests so their Database isn't overloaded, and build a performant GraphQL API. They will also learn how to use the official DataLoader package to explore the benefits further. With just a couple of clicks, learners will be able to set up a Gitpod to follow along and optimize a GraphQL API as they work through the course.
Course Provider
Provider egghead.io's Stats at AZClass
Discussion and Reviews
0.0 (Based on 0 reviews)
Explore Similar Online Courses
Stashbusting Secrets for Sweater Knitting & More
Pivot Tables Excel: Detailed Beginners Pivot Table Tutorial
Python for Informatics: Exploring Information
Social Network Analysis
Introduction to Systematic Review and Meta-Analysis
The Analytics Edge
DCO042 - Python For Informatics
Causal Diagrams: Draw Your Assumptions Before Your Conclusions
Whole genome sequencing of bacterial genomes - tools and applications
A Practical Guide to GraphQL: From the Client Perspective
Building Better APIs with GraphQL
GraphQL Essential Training
Related Categories
Popular Providers
Quiz
Submitted Sucessfully
1. What is the main purpose of the GraphQL Data Loader pattern?
2. What is the first step to using the GraphQL Data Loader pattern?
3. What is the benefit of using the GraphQL Data Loader pattern?
4. What is the best way to get started with the GraphQL Data Loader pattern?
Start your review of Use GraphQL Data Loaders to Prevent Scaling Issues by Batching & Caching Database Requests