Resolvers: The Backbone Of Graphql Queries

As GraphQL becomes increasingly popular as an API query language of choice, one of its core components - the resolver - plays a vital role in fulfilling GraphQL queries. Resolvers act as the bridge between a GraphQL query and retrieving the necessary data from various data sources like databases, REST APIs or elsewhere. Without effective resolvers, GraphQL queries cannot be executed and fetch the desired data. This article delves deeper into what resolvers are, their functioning and best practices for building resolver logic.

What Are Resolvers?

Resolvers in GraphQL are functions that are responsible for fulfilling specific fields (or types) in a GraphQL schema. Whenever a GraphQL query is executed and it asks for a field, the resolver tied to that particular field is invoked to fetch and return the value for that field.

For example, consider a schema with a `User` type that has fields like `name`, `age` and `posts`. The resolver for the `name` field would likely fetch the user's name from a database and return it. The `age` field resolver may calculate age based on birthdate. And the `posts` field resolver would retrieve all posts associated with that user from the posts table.

So in summary, resolvers act as handlers or functions that are attached to fields/types in a GraphQL schema to fetch and return data when a query is executed for those fields. Without resolvers, queries would not know where and how to fetch the required data.

Resolver Types

There are generally three types of resolvers developers build:

- Root Value Resolvers: These are Resolver attached to the root fields of a GraphQL query. For example a `user` query may have a resolver to fetch a user by ID.

- Nested Resolvers: These handle nested fields within objects. For example fetching posts for a user or comments for each post.

- Interface/Union Resolvers: Resolve interfaces/unions back to their actual object types.

It's important to understand the different resolver types and how they work together to fetch nested and related data in a GraphQL query.

Building Resolver Logic

With a basic understanding of resolver types, let's look at the typical steps to build resolver logic:

Data Access
- Resolvers typically make API calls, query databases or access in-memory caches to fetch the required data. Common libraries used include MongoDB, PostgreSQL, REST clients etc.

Parameters Parsing
- Resolvers often accept parameters passed from the query. For example, a user resolver may accept a user ID parameter. Parameters need to be parsed from the resolver context.

Data Massaging
- Fetched data sometimes needs formatting or adding additional fields before returning. For example, calculating age from birthdate.

Error Handling
- Anticipate and gracefully handle errors from data sources or during data processing within resolvers.

Caching
- For performance, cache resolver results based on parameters. Libraries like Redis are commonly used.

Batching Requests
- Fetch nested/related data in a single round-trip using batching where possible to optimize performance.

Permission Checks
- Only return authorized data based on permissions. Useful for security.

Tracing/Logging
- Add tracing/logging to monitor and debug resolver performance and errors.

With proper data access logic, parameter handling, error catching and optimizations like caching - developers can build robust and high performing resolver functions.

Best Practices With Resolvers

Some best practices to keep in mind regarding GraphQL resolvers include:

- Keep resolvers focused, thin and Single Responsibility focused
- Leverage existing data access libraries instead of logic duplication
- Return Promise from async resolvers
- Implement caching at resolver level
- Avoid expensive operations like DB queries in non-leaf fields
- Structure resolvers based on domain/type not technical layers
- Verify authorization and permissions in resolvers
- Trace and log resolver performance
- Batch resolve related operations for efficiency
- Validate and sanitize resolver parameters
- Add error handling and validation
- Modularize resolvers based on domain for readability
- Abstract data access from resolvers for decoupling
- Leverage resolvers for filtering, pagination etc
- Write unit tests for resolver functions.

Following these practices helps build scalable, optimized and maintainable GraphQL resolvers for any project or schema.

Resolvers act as critical functions attached to GraphQL schema types and fields that are responsible for fetching the required data and fields to fulfill GraphQL queries and mutations. Understanding resolver types, building reusable resolver logic with best practices like caching, validation and optimization techniques ensure a smooth and top performing GraphQL implementation. Resolvers are truly the backbone that help execute GraphQL queries efficiently.