What is Query Complexity Analysis?

Query complexity analysis is a technique used to evaluate the computational cost of a GraphQL query based on its structure and the fields requested. It assigns a complexity score to each query, allowing developers to set limits on how complex a query can be. This is particularly important in GraphQL due to its flexibility, which can lead to performance issues or denial-of-service (DoS) attacks if clients send overly complex or deeply nested queries.

Why is Query Complexity Analysis Important?

The importance of query complexity analysis can be summarized in the following points:

• Performance Management: By limiting the complexity of queries, you can prevent resource exhaustion on your server, ensuring that it remains responsive and performant.
• Security: It helps mitigate the risk of DoS attacks, where an attacker might send complex queries to overwhelm the server.
• Predictable Resource Usage: Complexity analysis allows you to predict and manage the resources consumed by different queries, making it easier to scale your application.
• Improved User Experience: By rejecting overly complex queries, you can ensure that users receive faster responses and a better overall experience.

How Query Complexity Analysis Works

Query complexity analysis works by assigning a cost to each field in the GraphQL schema. When a query is received, the server calculates the total complexity based on the fields requested and their associated costs. If the total complexity exceeds a predefined limit, the server can reject the query.

Sample Code for Query Complexity Analysis

Below is an example of how to implement query complexity analysis using the graphql-validation-complexity library in an Apollo Server setup.

Step 1: Install the Required Library

npm install graphql-validation-complexity

Step 2: Set Up Apollo Server with Complexity Analysis

const { ApolloServer, gql } = require('apollo-server');
const { createComplexityLimitRule } = require('graphql-validation-complexity');

// Define your schema
const typeDefs = gql`
    type User {
        id: ID!
        name: String!
        posts: [Post]
    }

    type Post {
        id: ID!
        title: String!
        content: String!
    }

    type Query {
        users: [User ]
    }
`;

// Define your resolvers
const resolvers = {
    Query: {
        users: () => {
            // Fetch users from the database or any data source
            return [
                { id: '1', name: 'Alice', posts: [] },
                { id: '2', name: 'Bob', posts: [] },
            ];
        },
    },
};

// Create a complexity limit rule
const complexityLimitRule = createComplexityLimitRule(10); // Set a complexity limit

// Create an instance of ApolloServer
const server = new ApolloServer({
    typeDefs,
    resolvers,
    validationRules: [complexityLimitRule],
});

// Start the server
server.listen().then(({ url }) => {
    console.log(`🚀 Server ready at ${url}`);
});

Step 3: Testing Query Complexity

In this example, if a client sends a query that exceeds the complexity limit of 10, the server will reject the query with an error message. For instance, a query that requests deeply nested fields could easily exceed this limit.

Sample Query That May Exceed Complexity:

query {
    users {
        id
        name
        posts {
            id
            title
            content
        }
    }
}

Conclusion

Query complexity analysis is a vital technique for managing the performance and security of GraphQL APIs. By implementing complexity limits, developers can prevent resource exhaustion, mitigate DoS attacks, and ensure a better user experience. Using libraries like graphql-validation-complexity makes it straightforward to integrate complexity analysis into your GraphQL server.