GraphQL Tutorial #9 - How to do Server-Side Caching in GraphQL?

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Server-side caching in GraphQL can be more challenging compared to traditional REST APIs due to the nature of GraphQL queries. In REST, you can easily cache an endpoint at the HTTP level, but in GraphQL, since it typically uses a single endpoint and the queries can be highly varied, caching needs a different approach. Here are some strategies for server-side caching in GraphQL:

### 1. **Resolver-Level Caching**

- **Concept:** Cache the result of individual resolvers. Since resolvers are functions that return data for a specific field, you can cache their outputs.
- **Implementation:** Use a caching mechanism (like Redis or Memcached) to store the results of resolver executions. The cache key can be a combination of the resolver name and its arguments.

```javascript
const userResolver = async (parent, { id }, context) = {
const cacheKey = `user:${id}`;
if (cachedUser) return cachedUser;

return user;
};
```

### 2. **DataLoader for Batch and Cache per Request**

- **Purpose:** DataLoader is often used to batch requests to the database but can also cache responses per individual request.
- **Implementation:** Create a DataLoader for each request and use it in your resolvers. DataLoader will cache the results of the database calls during a single GraphQL query.

```javascript
// Setup DataLoader in context

// In Resolver
const userResolver = (parent, { id }, context) = {
};
```

### 3. **Field-Level Caching with Directives**

- **Approach:** Define custom directives to annotate fields that should be cached.
- **Implementation:** Implement the logic to handle these caching directives in your resolvers.

```graphql
type User @cacheControl(maxAge: 3600) {
id: ID!
name: String
}
```

### 4. **Schema Stitching or Federation Caching**

- If using a GraphQL gateway (like Apollo Federation), implement caching at the gateway level. This allows caching responses from different services.

### 5. **Partial Query Caching**

- Cache parts of your queries. This is complex but can be effective for repeated nested queries within different higher-level queries.

### 6. **HTTP Caching with Persisted Queries**

- **Persisted Queries:** Store the query server-side and reference it with a unique identifier. This allows HTTP-level caching mechanisms to be utilized.
- **Implementation:** Clients send a query ID instead of the full query. The server fetches the query using this ID, executes it, and can cache the response.

### 7. **Monitoring and Invalidating Cache**

- **Monitoring:** Keep track of how often data changes and how it impacts your cache.
- **Invalidation:** Implement strategies to invalidate the cache when the underlying data changes.

### Conclusion

Server-side caching in GraphQL requires a more granular approach compared to REST. You'll often need to mix and match different strategies based on your data access patterns and how your schema is structured. Remember, improper caching can lead to stale data, so it's crucial to have robust invalidation mechanisms in place.