Handling Cross-Subgraph Queries and Mutations in Federated GraphQL
Federated GraphQL allows you to build a unified API from multiple independent GraphQL services (subgraphs). A key challenge and powerful feature is the ability to perform queries and mutations that span across these subgraphs. This enables complex data retrieval and manipulation without requiring clients to orchestrate multiple API calls.
Understanding Cross-Subgraph Queries
When a query requests data that resides in different subgraphs, the Apollo Federation gateway intelligently orchestrates the execution. It breaks down the single client request into multiple requests to the relevant subgraphs, collects the results, and stitches them together before returning a unified response to the client.
The gateway acts as a smart orchestrator for cross-subgraph queries.
When you query for a user's profile and their associated orders, and these pieces of data are managed by different subgraphs (e.g., 'users' subgraph and 'orders' subgraph), the gateway identifies which subgraph holds which data. It then sends separate requests to each subgraph and combines the results.
Consider a scenario where a User entity has a field orders which is resolved by a separate Order subgraph. When a client requests user(id: "123") { name orders { id total } }, the gateway first queries the User subgraph for user(id: "123") { id name }. Upon receiving the user's ID, it then queries the Order subgraph for orders(userId: "123") { id total }. Finally, it merges these results to provide the complete response.
Key Concepts in Cross-Subgraph Querying
The gateway orchestrates requests across subgraphs, collects results, and stitches them into a unified response.
Federation relies on entity resolution. When a subgraph returns an entity that is also managed by another subgraph, the gateway uses the
@key
Handling Cross-Subgraph Mutations
Mutations, like queries, can also span multiple subgraphs. The execution of cross-subgraph mutations follows a similar orchestration pattern, but with specific considerations for atomicity and error handling.
Mutations can trigger actions in multiple subgraphs.
When a mutation modifies data in one subgraph and then uses that modified data to trigger an action in another subgraph, the gateway manages this sequence. For example, creating an order might involve updating inventory in one service and then creating the order record in another.
A mutation like createOrder(input: { userId: "123", itemIds: ["A", "B"] }) might first call an Inventory subgraph to decrement stock for items "A" and "B", and then call an Order subgraph to create the order record associated with user "123". The gateway ensures that the userId returned or inferred from the first operation is correctly passed to the second operation.
For mutations that involve multiple subgraphs, consider the transactional integrity. If one part of the mutation fails, you might need strategies for rollback or compensation to maintain data consistency across your federated services.
Strategies for Complex Cross-Subgraph Operations
When dealing with complex cross-subgraph operations, especially mutations, careful design is crucial. This includes defining clear entity relationships, using appropriate directives, and implementing robust error handling.
| Feature | Cross-Subgraph Queries | Cross-Subgraph Mutations |
|---|---|---|
| Primary Goal | Unified data retrieval | Unified data modification and side effects |
| Execution Flow | Parallel or sequential fetching, then stitching | Sequential execution, often with data passing between steps |
| Error Handling | Partial results are often acceptable | Requires careful consideration for atomicity and rollback |
| Key Directives | @key, @extends | @key, @extends, custom directives for side effects |
Example: A Federated E-commerce Scenario
Imagine an e-commerce platform with separate subgraphs for 'Products', 'Users', and 'Orders'. A client might want to view a user's order history, including product details for each item in the order. This involves querying the 'Users' subgraph for user information, the 'Orders' subgraph for order IDs, and then the 'Products' subgraph for product details for each item in those orders. The gateway handles this by resolving the
User
orders
order
products
The diagram illustrates how a federated gateway orchestrates a query that spans multiple subgraphs. The client sends a single query to the gateway. The gateway, aware of the schema from each subgraph, determines which subgraph is responsible for which part of the query. It then sends targeted requests to the relevant subgraphs (e.g., User subgraph, Order subgraph). Each subgraph processes its part of the query and returns its results. The gateway then merges these results, resolving any entity references (e.g., linking an order to its products), and sends a single, unified response back to the client. This process is crucial for efficient data fetching in a microservices architecture.
Text-based content
Library pages focus on text content
Learning Resources
Official documentation on how Apollo Federation handles query execution and tracing across subgraphs.
Details on how mutations are handled in a federated GraphQL setup, including considerations for cross-subgraph operations.
A conceptual overview of GraphQL Federation, explaining the core principles behind building distributed GraphQL APIs.
A practical video tutorial demonstrating the setup and usage of Apollo Federation, including cross-subgraph interactions.
An in-depth explanation of GraphQL Federation concepts, covering schema stitching and entity resolution.
Learn about the `@key` directive and how Apollo Federation resolves entities across different subgraphs.
Discusses common patterns and best practices for designing and implementing federated GraphQL services.
Explores more complex scenarios in federation, such as custom directives and handling distributed transactions.
A foundational resource for understanding the core principles of GraphQL, essential for grasping federation.
An article discussing the benefits of GraphQL Federation as an architectural pattern for microservices.