I've recently started to research the possibility of using GraphQL for requesting dynamic data configurations. The very first thing that jumps out at me is the strongly-typed concept of GraphQL.
Is there a way for GraphQL schemas to handle arrays of mixed type objects? I would greatly appreciate either an explanation or possibly a reference I can read over.
I am currently working with GraphQL with Node.js but a later implementation will be out of a Java Container. All data will be JSON pulled from MongoDB.
The GraphQL schema language supports the scalar types of String , Int , Float , Boolean , and ID , so you can use these directly in the schema you pass to buildSchema . By default, every type is nullable - it's legitimate to return null as any of the scalar types.
Schema stitching is the idea that you can take two or more GraphQL schemas, and merge them into one endpoint that can pull data from all of them.
GraphQL scalar types Here are the primitive data types that GraphQL supports: Int – A signed 32-bit integer. Float – A signed double precision floating point value.
The __typename field returns the object type's name as a String (e.g., Book or Author ). GraphQL clients use an object's __typename for many purposes, such as to determine which type was returned by a field that can return multiple types (i.e., a union or interface).
You either have to make these disparate types implement the same interface, make your resolvers return unions, or create a custom scalar to hold the dynamic data.
The cleanest approach is the first one: if your resulting objects can be of a limited number of types, define the types so that they implement the same interface, and type your resolvers by the interface. This allows the client to conditionally select sub-fields based on the actual type, and you maintain type safety.
The second approach has similar limitations: you need to know the possible types ahead of time, but they do not have to implement the same interface. It is preferable when the possible values are unrelated to each other and have either/or semantics, like success/failure.
The custom scalar approach is the only one in which you do not need to know the possible types of the result, i.e. the structure of the result can be completely dynamic. Here's an implementation of that approach, known as JSON scalar (i.e. cram any JSON-serializable structure into a scalar value). The big downside of this approach is that it makes sub-selection impossible, as the entire value becomes one big scalar (even though it's a complex object).
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