Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/prisma-labs/http-link-dataloader
📚📡 HTTP Apollo Link with batching & caching provided by dataloader.
https://github.com/prisma-labs/http-link-dataloader
apollo-link batch-request dataloader graphql
Last synced: about 2 months ago
JSON representation
📚📡 HTTP Apollo Link with batching & caching provided by dataloader.
- Host: GitHub
- URL: https://github.com/prisma-labs/http-link-dataloader
- Owner: prisma-labs
- License: mit
- Created: 2017-11-14T10:39:28.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2022-12-06T19:51:49.000Z (almost 2 years ago)
- Last Synced: 2024-07-12T18:33:40.206Z (2 months ago)
- Topics: apollo-link, batch-request, dataloader, graphql
- Language: TypeScript
- Homepage:
- Size: 327 KB
- Stars: 78
- Watchers: 6
- Forks: 14
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-list - http-link-dataloader - labs | 79 | (TypeScript)
README
# http-link-dataloader
[](https://circleci.com/gh/prisma/http-link-dataloader) [](https://badge.fury.io/js/http-link-dataloader)
📚📡 HTTP Apollo Link with batching & caching provided by dataloader.
## Idea
A Apollo Link that batches requests both in Node and the Browser.
You may ask what's the difference to [apollo-link-batch-http](https://github.com/apollographql/apollo-link/tree/master/packages/apollo-link-batch-http).
Instead of having a time-frame/fixed cache size based batching approach like in `apollo-link-batch-http`, this library uses [dataloader](https://github.com/facebook/dataloader) for batching requests. It is a more generic approach just depending on the Node.JS event loop that batches all consecutive queries directly.
The main use-case for this library is the usage from a [`graphql-yoga`](https://github.com/graphcool/graphql-yoga) server using [`prisma-binding`](https://github.com/graphcool/prisma-binding), but it can be used in any environment, even the browser as the latest `dataloader` version also runs in browser environments.
## Usage
```ts
import { HTTPLinkDataloader } from 'http-link-dataloader'
const link = new HTTPLinkDataloader()
const token = 'Auth Token'
const httpLink = new HTTPLinkDataloader({
uri: `api endpoint`,
headers: { Authorization: `Bearer ${token}` },
})
```
## Caching behavior
Note that the dataloader cache aggressively caches everything! That means if you don't want to cache anymore, just create a new instance of `BatchedHTTPLink`.
A good fit for this is every incoming HTTP request in a server environment - on each new HTTP request a new `BatchedHTTPLink` instance is created.
## Batching
This library uses array-based batching. Querying 2 queries like this creates the following payload:
```graphql
query {
Item(id: "1") {
id
name
text
}
}
```
```graphql
query {
Item(id: "2") {
id
name
text
}
}
```
Instead of sending 2 separate http requests, it gets combined into one:
```js
;[
{
query: `query {
Item(id: "1") {
id
name
text
}
}`,
},
{
query: `query {
Item(id: "2") {
id
name
text
}
}`,
},
]
```
**Note that the GraphQL Server needs to support the array-based batching!**
(Prisma supports this out of the box)
## Even better batching
A batching that would even be faster is alias-based batching. Instead of creating the array described above, it would generate something like this:
```js
{
query: `
query {
item_1: Item(id: "1") {
id
name
text
}
item_2: Item(id: "2") {
id
name
text
}
}`
}
```
This requires a lot more logic and resolution magic for aliases, but would be a lot faster than the array based batching as our tests have shown!
Anyone intersted in working on this is more than welcome to do so!
You can either create an issue or just reach out to us in slack and join our #contributors channel.
## Help & Community [](https://slack.prisma.io)
Join our [Slack community](http://slack.prisma.io) if you run into issues or have questions. We love talking to you!
