The docs (https://www.apollographql.com/docs/apollo-server/features/data-sources.html#Using-Memcached-Redis-as-a-cache-storage-backend) show code like this:
const { RedisCache } = require('apollo-server-cache-redis');
const server = new ApolloServer({
typeDefs,
resolvers,
cache: new RedisCache({
host: 'redis-server',
// Options are passed through to the Redis client
}),
dataSources: () => ({
moviesAPI: new MoviesAPI(),
}),
});
I was wondering how that cache
key is used, considering it seems like the caching is actually custom implemented in something like MoviesAPI()
and then used via context.dataSources.moviesAPI.someFunc()
. For example, say I wanted to implement my own cache for a SQL database. It'd look like
cache: new RedisCache({
host: 'redis-server',
}),
dataSources: () => ({
SQL: new SQLCache(),
}),
});
where SQLCache
has my own function that connects to the RedisCache
like:
getCached(id, query, ttl) {
const cacheKey = `sqlcache:${id}`;
return redisCache.get(cacheKey).then(entry => {
if (entry) {
console.log('CACHE HIT!');
return Promise.resolve(JSON.parse(entry));
}
console.log('CACHE MISS!');
return query.then(rows => {
if (rows) redisCache.set(cacheKey, JSON.stringify(rows), ttl);
return Promise.resolve(rows);
});
});
}
So that means I have RedisCache
in both the ApolloServer
cache
key and dataSource
implementation. Clearly, the RedisCache
is used in the dataSource
implementation, but then what does that ApolloServer
cache
key do exactly?
Also on the client, examples mostly show use of InMemoryCache
instead of Redis cache. Should the client Apollo cache be a different cache from the server cache or should the same cache like RedisCache
be in both places?
Apollo Server uses an in-memory cache by default, but you can configure it to use a different backend, such as Redis or Memcached. You can specify a cache backend by passing a cache option to the ApolloServer constructor. Your specified cache backend must implement the KeyValueCache interface from the @apollo/utils.
Basic Usage By default, the contents of your Apollo cache will be immediately restored (asynchronously, see how to persist data before rendering), and will be persisted upon every write to the cache (with a short debounce interval).
When we have access to the cache object we can call cache. data. delete(key) where key is the key that Apollo is using to store the data for a specific item. And the record will be entirely deleted from the cache.
This solution exists only because GraphQL cannot handle caching in the server, for which we normally use the URL as the identifier and cache the data for all entities in the response all together. Caching in the client has a few disadvantages: The application got more JavaScript to run on the client side.
The cache
passed to the ApolloServer
is, to my knowledge, strictly used in the context of a RESTDataSource
. When fetching resources from the REST endpoint, the server will examine the Cache-Control
header on the response, and if one exists, will cache the resource appropriately. That means if the header is max-age=86400
, the response will be cached with a TTL of 24 hours, and until the cache entry expires, it will be used instead of calling the same REST url.
This is different than the caching mechanism you've implemented, since your code caches the response from the database. Their intent is the same, but they work with different resources. The only way your code would effectively duplicate what ApolloServer's cache
already does is if you had written a similar DataSource
for a REST endpoint instead.
While both of these caches reduce the time it takes to process your GraphQL response (fetching from cache is noticeably faster than from the database), client-side caching reduces the number of requests that have to be made to your server. Most notably, the InMemoryCache
lets you reuse one query across different places in your site (like different components in React) while only fetching the query once.
Because the client-side cache is normalized, it also means if a resource is already cached when fetched through one query, you can potentially avoid refetching it when it's requested with another query. For example, if you fetch a list of Users with one query and then fetch a user with another query, your client can be configured to look for the user in the cache instead of making the second query.
It's important to note that while resources cached server-side typically have a TTL, the InMemoryCache
does not. Instead, it uses "fetch policies" to determine the behavior of individual queries. This lets you, for example, have a query that always fetches from the server, regardless of what's in the cache.
Hopefully that helps to illustrate that both server-side and client-side caching are useful but in very different ways.
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