Unified GraphQL Schema for Multi-Source Data Aggregation
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Solution Overview
Problem
Current systems for using GraphQL to enhance external APIs and SDKs are underdeveloped, lacking efficient methods for defining and generating schemas, which limits their effectiveness in managing data queries and reducing network bandwidth and server trips.
Innovation Solution
The implementation of a method that automatically generates combined schemas based on multiple data sources using graph-processing techniques, allowing clients to unify interaction between API producers and consumers, and retrieve dependent resources with a single client request, thereby reducing network bandwidth and CPU cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate API calls are made to retrieve data from different endpoints, then complete data can be obtained, but network bandwidth usage increases and server trips multiply
Solution Approach 1:
The patent combines multiple separate API endpoints into a single unified GraphQL endpoint. Clients can retrieve data from what would traditionally require multiple separate calls (e.g., user profile, posts, comments) through one consolidated query, eliminating redundant network requests and reducing bandwidth consumption while maintaining complete data retrieval
Solution Approach 2:
The GraphQL endpoint serves as a universal interface that can handle multiple different data retrieval requests through a single endpoint. The schema design allows the same endpoint to efficiently serve various data combinations (user data, post data, comment data) without requiring separate specialized API calls for each resource type
2Ease of operation
If traditional REST APIs are used with fixed endpoints, then data retrieval is straightforward, but clients cannot precisely specify the data structure needed
Solution Approach 1:
The patent implements a dynamic schema system where the data structure is not fixed but can be precisely configured by clients through GraphQL queries. The schema language allows clients to dynamically specify exactly what fields and data structures they need, enabling precise control over data structure while maintaining ease of operation through a standardized query interface
Solution Approach 2:
The GraphQL schema allows clients to change parameters of their data requests by modifying query structure, field selections, and type specifications. This enables precise control over data structure without complicating the operation, as clients can adapt their queries to exact data needs while the unified endpoint handles all variations
3Manufacturing precision
If GraphQL schema generation is manually defined, then schema accuracy is high, but the process is time-consuming and complex
Solution Approach 1:
The patent implements automatic schema generation that performs preliminary actions by analyzing existing API endpoints and data models to pre-configure the GraphQL schema. This automated approach maintains high schema accuracy by deriving schemas from actual data structures while dramatically reducing the time and manual effort required compared to traditional manual schema definition processes
Data Source
AI summary
In an embodiment, a method comprises: generating, at a client computer, a first schema in a graph query language processing system, the schema indicating which querying operations and mutating operations that a graph endpoint of the graph query language processing system supports, wherein generating the first schema comprises: automatically mapping a first resource of a first plurality of resources from a first endpoint of a first data source to a first field in the first schema; automatically mapping a second resource of a second plurality of resources from a second endpoint of a second data source to a second field in the first schema; generating and submitting a query to the graph endpoint based on the first schema that causes retrieving the first resource from the first endpoint and the second resource from the second endpoint; generating and causing displaying, at the client computer, a digital data display that shows the first resource and the second resource in a unified format. The method is adapted to automatically generate a combined schema from multiple schemas and/or data sources and use the combined schema to query and aggregate data from multiple data sources.