Apollo DataSource for Firestore
This is a Firestore DataSource for Apollo GraphQL Servers. It was adapted from the CosmosDB DataSource
Usage
Use by creating a new class extending the FirestoreDataSource, with the desired document type.
Use separate DataSources for each data type, and preferably
different collections in Firestore too. Initialise the class
by passing a collection reference created by the Firestore library.
export interface UserDoc {
// a string id value is required for entities using this library.
// It will be used for the firestore document ID but not stored in the document in firestore.
readonly id: string
readonly collection: 'users'
name: string
groupId: number
}
export interface PostsDoc {
readonly id: string
readonly collection: 'posts'
title: string
}
export class UserDataSource extends FirestoreDataStore<UserDoc, ApolloContext> {}
export class PostsDataSource extends FirestoreDataStore<PostsDoc, ApolloContext> {}
const usersCollection: CollectionReference<UserDoc> = firestore.collection('users')
const postsCollection: CollectionReference<PostsDoc> = firestore.collection('posts')
const server = new ApolloServer({
typeDefs,
resolvers,
dataSources: () => ({
users: new UserDataSource(usersCollection),
posts: new PostsDataSource(postsCollection)
})
})Custom queries
FirestoreDataSource has a findByQuery method that accepts a function taking the collection as its only argument, which you can then create a query based on. Can be used in resolvers or to create wrappers.
Example of derived class with custom query methods:
export class UserDataSource extends FirestoreDataStore<UserDoc, ApolloContext> {
async findManyByGroupId (groupId: number) {
return this.findManyByQuery(c => c.where('groupId', '==', groupId).limit(2))
}
async findOneByEmail (email: string) {
return this.findManyByQuery(c => c.where('email', '==', email).limit(1))?.[0] ?? undefined
}
}Write Operations
This DataSource has some built-in mutations that can be used to create, update and delete documents.
await context.dataSources.users.createOne(userDoc)
await context.dataSources.users.updateOne(userDoc)
await context.dataSources.users.updateOnePartial(userId, { name: 'Bob' })
await context.dataSources.users.deleteOne(userId)Batching
Batching is provided on all id-based queries by DataLoader.
Caching
Caching is available on an opt-in basis by passing a ttl option on queries.