Why are loaders created within the context per request?

Creating loaders inside the context ensures that data is only cached for the duration of a single request, which is essential for preventing stale data across different users and avoiding memory leaks.

Can I use this with any GraphQL server?

While the code examples are tailored for Node.js environments like Apollo Server, the core architectural patterns and batching logic apply to most GraphQL server implementations.

Does this skill handle GraphQL subscriptions?

Yes, it includes patterns for implementing real-time subscriptions using PubSub systems and provides examples for using filters to control which clients receive specific updates.

How does this skill prevent N+1 queries?

It guides you through implementing the DataLoader pattern, which batches multiple individual requests for related resources into a single database query using a short-lived cache.

GraphQL Resolver Optimization

Name: GraphQL Resolver Optimization
Author: pluginagentmarketplace

bypluginagentmarketplace

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API開発

Implements high-performance GraphQL resolvers using DataLoader patterns and batching to eliminate N+1 query problems.

概要

This skill provides comprehensive guidance for building production-grade GraphQL backends by focusing on resolver efficiency and optimized data-fetching patterns. It covers the implementation of the DataLoader pattern for batching and caching, request-scoped context management, field-level resolvers, and standardized error handling. Developers can use this skill to transform slow, unoptimized GraphQL APIs into performant services that handle complex relationship queries with minimal database overhead while maintaining clean, maintainable code architectures.

主な機能

Implementation of field-level and computed resolvers
Standardized error handling with GraphQLError extensions
DataLoader integration for N+1 query prevention and batching
1 GitHub stars
Subscription patterns with PubSub and filtering logic
Request-scoped context design for authentication and data sources

ユースケース

Standardizing error responses and authentication checks across a GraphQL server
Implementing complex data relationships and nested queries efficiently
Optimizing slow GraphQL APIs that suffer from high database query volume

概要

主な機能

Implementation of field-level and computed resolvers
Standardized error handling with GraphQLError extensions
DataLoader integration for N+1 query prevention and batching
1 GitHub stars
Subscription patterns with PubSub and filtering logic
Request-scoped context design for authentication and data sources

ユースケース

Standardizing error responses and authentication checks across a GraphQL server
Implementing complex data relationships and nested queries efficiently
Optimizing slow GraphQL APIs that suffer from high database query volume