Solution to Under-Fetching
1. Comprehensive Data Retrieval
- Meet the requirement by making sure the need that user specifies appears in our interface.
- This could be done by refactoring CMS queries or API endpoints, to ensure that the requisite data is sent to the corresponding locations.
2. Feedback Mechanisms
- Develop feedback mechanisms by which the user can ask the developer for additional information or a feature, thus solving the problem of under-fetching, since the user input is continuously taken into consideration and the developers can deliver what the user truly needs.
3. Dynamic Loading
- Delayed loading methods can fetch additional data in case bugs show up or such issues when the user starts deeper interactions like preferences.
- Through this method, the first phase of the querying process is optimized without compromising on the subsequent fetching stages.
What Are Over-Fetching and Under-Fetching?
Fetching data in GraphQL is a fundamental concept that involves retrieving information from a server or database. Unlike traditional REST APIs, GraphQL allows clients to request only the specific data they need, minimizing over–fetching and under–fetching.
In this article, We will explore the concepts of fetching, over–fetching, and under–fetching in GraphQL, along with their challenges and solutions in detail and so on.
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