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As an API grows, a single schema.graphqls file becomes thousands of lines, hard to navigate and prone to merge conflicts.

Modularization splits the schema by feature so each team owns a focused slice.

This is different from schema stitching. Stitching merges schemas from separate services. Modularization splits one service's schema into many files that load into the same runtime.

Spring for GraphQL automatically loads every .graphqls file under src/main/resources/graphql/ and merges them into one schema.

GraphQL allows only one Query type. If two files both declare type Query, the schema fails to build with a duplicate-type error.

Declare type Query once, then use extend type Query in other files to add fields. The pieces merge into one root.

extend works on any object type, not just roots. A reviews module can add a field to Book without editing the book file.

Each module gets its own controller. The extended field on Book is resolved by a @SchemaMapping in the review module's controller.

Cross-cutting types like PageInfo or shared enums live in a common.graphqls file. Every module references them without redefining.

Group SDL files and controllers by feature, not by GraphQL kind. Keep book.graphqls next to BookController mentally, so a feature change touches one cohesive area.

Spring assembles and validates the merged schema at startup. If an extend references a type that does not exist, the application fails fast with a clear error, catching mistakes early.

Keep modular schemas healthy:

• Declare each root type once, extend elsewhere
• One SDL file and controller per feature
• Centralize shared types in a common file
• Let startup validation guard your merges

You modularized a large schema:

• Split SDL into multiple feature files Spring auto-merges
• Declare root types once, add fields with extend
• Extend any object type from another module
• Centralize shared types and keep resolvers modular

Modular schemas scale cleanly across teams and features.