Tutorials > Egghead - Prevent Scaling Issues With GraphQL Data Loaders

Egghead - Prevent Scaling Issues With GraphQL Data Loaders


Date: 18 July 2022 | Posted by: voska89
Egghead - Prevent Scaling Issues With GraphQL Data Loaders
Released 12/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 10 Lessons (12m) | Size: 73.1 MB
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.
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
Homepage
https://egghead.io/courses/use-graphql-data-loaders-to-prevent-scaling-issues-by-batching-caching-database-requests-3b5d4442



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