Examples of Over-Fetching
1. API Requests
Think of a social network mobile app that shows user accounts with actual pictures of the users. The API endpoint created for obtaining the user data returns all information about the user including his address, phone number, and preferred selections, but app that require only user name and profile picture performs the over-fetching.
2. Database Queries
An example may be to run a query which does not require all the columns from the table, but only a few of them, whereas in reality, the unnecessary columns are also fetched along with others. Likewise, a case where a refreshing page only gets the email address and name data fields from the user table is typical since all the columns are retrieved, thus data being moved and processed in a sub-optimal way.
3. File Downloads
Downloading files may involve requesting huge files which are full of information that we don’t need, hence wasting bandwidth and storages space. One example is that when downloading a document – for a particular area – but ended up with the whole document which includes different topics that irrelevant.
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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