GraphQL Interview Questions

GraphQL is a query language for your API, and it's the next big thing in web development. If you're interviewing for a GraphQL-related role, you might be wondering what kind of questions you can expect. This article will help you prepare by covering common GraphQL interview questions and providing tips on how to answer them.

Here we go:

1. What is GraphQL and how does it differ from REST?

GraphQL is a query language for APIs developed by Facebook. It provides a more efficient, powerful, and flexible alternative to REST. Unlike REST, which exposes a fixed set of endpoints, GraphQL allows clients to request only the data they need in a single query. This reduces the amount of data transferred over the network and makes it easier to evolve your API over time.

Want to learn more at Latest edition of REST vs GraphQL

2. What are the benefits of using GraphQL?

Some of the key benefits of using GraphQL include:

• Reduced Overfetching and Underfetching: Clients can request only the data they need, reducing the amount of data transferred over the network.
• Strongly Typed Schema: GraphQL schemas are strongly typed, which provides better validation and auto-completion in IDEs.
• Flexible Queries: Clients can specify their data requirements in a single query, making it easier to evolve the API over time.
• Real-time Updates: GraphQL supports real-time updates through subscriptions, allowing clients to receive updates as soon as they happen.

3. How do you define a GraphQL schema?

A GraphQL schema is defined using the GraphQL Schema Definition Language (SDL). It consists of types, fields, and directives. Here's an example of a simple schema:

type Query {
  hello: String
}

This schema defines a single query field called hello that returns a String. You can also define more complex types and relationships between them.

4. What are resolvers in GraphQL?

Resolvers are functions that resolve the value of a field in a GraphQL query. They are responsible for fetching the data from the underlying data source and returning it to the client. Each field in a GraphQL query can have its own resolver, allowing you to customize the data fetching logic for each field.

5. How do you handle authentication and authorization in GraphQL?

There are several ways to handle authentication and authorization in GraphQL:

• HTTP Headers: You can pass authentication tokens or cookies in the Authorization header of the HTTP request.
• Context: You can use the context argument in resolvers to pass authentication information to the resolver functions.
• Directives: You can use custom directives to apply authorization rules to specific fields or types in your schema.

Learn more about authentication and authorization

6. What is the difference between a query and a mutation in GraphQL?

A query is used to read data from the server, while a mutation is used to write or modify data on the server. Queries are executed in parallel, while mutations are executed sequentially.

7. How do you handle errors in GraphQL?

GraphQL has built-in support for error handling. You can use the errors field in the response to return a list of errors that occurred during the execution of the query or mutation. Each error has a message field that describes the error, and an optional locations field that specifies the location in the query where the error occurred.

8. What are subscriptions in GraphQL?

Subscriptions are a way to subscribe to real-time updates from the server. They are similar to queries and mutations, but instead of executing once and returning a result, they execute repeatedly and return a stream of results as they become available. This makes it easy to build real-time features like chat apps or live feeds.

9. What are some best practices for designing a GraphQL schema?

Some best practices for designing a GraphQL schema include:

• Keep it simple: Start with a simple schema and add complexity as needed.
• Use descriptive names: Use descriptive names for types, fields, and arguments to make your schema easier to understand.
• Avoid deep nesting: Keep your schema shallow to avoid overly complex queries.
• Use interfaces and unions: Use interfaces and unions to model complex data relationships.