Examples of Under-Fetching in Different Contexts
1. E-commerce Product Listings:
- Take for example the case of an e-commerce site that has product displays with basic information which lacks the details such as price, description or the availability of the item.
- Visitors to the site will understand under-fetching, as they can not arrive at the decision making without the full details of the product.
2. Weather Forecasting:
- If a weather application replaces the basic temperature information with high-tech wind speed, humidity levels, and precipitation forecasts, users can face even a situation of under-fetching when they need more comprehensive look at how the weather will develop throughout the day.
3. Educational Resources:
- In a learning platform online, if the course overview is skimpy on information that shall include curriculum, instructors details and course duration among others, learners might find it hard to gauge the viability of the courses with the result of reluctance to enroll.
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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