Data cache merging using React Query and database
Sep 27, 2023 am 08:01 AMUse React Query and database for data cache merging
Introduction:
In modern front-end development, data management is a very important part. In order to improve performance and user experience, we usually need to cache the data returned by the server and merge it with local database data. React Query is a very popular data caching library that provides a powerful API to handle querying, caching, and updating data. This article will introduce how to use React Query and a database for data cache merging, and provide specific code examples.
Step 1: Install and configure React Query
First, we need to install React Query. Open a terminal and execute the following command:
npm install react-query
or
yarn add react-query
Next, create a React Query configuration file in our project. Create a file named react-query-config.js in the src directory and add the following content:
import { QueryClient, QueryClientProvider } from 'react-query';
const queryClient = new QueryClient();
export const QueryClientProviderWrapper = ({ children }) => (
{children}
);
Here we create an instance named queryClient and pass it to the QueryClientProvider component. This way we can use React Query throughout the project.
Step 2: Create data API
Now we need to create a data API to get the data on the server and cache it into React Query. Suppose our API provides a getItems() method that gets a list of items and returns an array containing all the items. Create a file named api.js in the src directory and add the following content:
import { queryClient } from './react-query-config';
export const getItems = async () => {
// Get item data from the server
const response = await fetch('/api/items');
const data = await response.json();
// Cache data into React Query
queryClient.setQueryData('items', data);
return data;
};
Here we use the fetch() method Get the data from the server and cache the data into React Query using the queryClient.setQueryData() method.
Step 3: Create a database API
Next, we need to create a database API to obtain data from the local database. Suppose our database provides a getItemsFromDatabase() method to get a list of items in the database and return an array containing all the items. Create a file named database.js in the src directory and add the following content:
export const getItemsFromDatabase = () => {
// Get item data from the database
const items = ...
return items;
};
In actual applications, you need to implement the getItemsFromDatabase() method according to the database type and corresponding library you use.
Step 4: Merge Data
Now, we can use React Query and the database API to merge the data. In our component, we use the useQuery() hook to get the data and the useMutation() hook to handle updates to the data. Here is a basic example component:
import { useQuery, useMutation } from 'react-query';
import { getItems, getItemsFromDatabase } from './api';
const ItemList = () => {
// Use useQuery hook to get data
const { data: serverData } = useQuery('items', getItems);
const { data: databaseData } = useQuery( 'itemsFromDatabase', getItemsFromDatabase);
//Use useMutation hook to handle data updates
const { mutate } = useMutation(() => {
// 在這里使用數(shù)據(jù)庫API更新數(shù)據(jù)
});
// Merge cache data and database data
const mergedData = [...serverData, ...databaseData];
return (
<div> {mergedData.map((item) => ( <div key={item.id}>{item.name}</div> ))} </div>
);
};
Here, we use two useQuery hooks to get data from the server and the database respectively (by passing 'items' and 'itemsFromDatabase' as query keys). We then use the useMutation hook to handle updates to the data. Finally, we merge the cache data with the database data and display it in the component.
Summary:
Using React Query and database for data cache merging can greatly improve application performance and user experience. In this article, we learned how to install and configure React Query, and use React Query and the database API to get and update data. I hope this article was helpful and if you have any questions, please feel free to ask!
The above is the detailed content of Data cache merging using React Query and database. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Apple's latest releases of iOS18, iPadOS18 and macOS Sequoia systems have added an important feature to the Photos application, designed to help users easily recover photos and videos lost or damaged due to various reasons. The new feature introduces an album called "Recovered" in the Tools section of the Photos app that will automatically appear when a user has pictures or videos on their device that are not part of their photo library. The emergence of the "Recovered" album provides a solution for photos and videos lost due to database corruption, the camera application not saving to the photo library correctly, or a third-party application managing the photo library. Users only need a few simple steps

JSON data can be saved into a MySQL database by using the gjson library or the json.Unmarshal function. The gjson library provides convenience methods to parse JSON fields, and the json.Unmarshal function requires a target type pointer to unmarshal JSON data. Both methods require preparing SQL statements and performing insert operations to persist the data into the database.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

How to use MySQLi to establish a database connection in PHP: Include MySQLi extension (require_once) Create connection function (functionconnect_to_db) Call connection function ($conn=connect_to_db()) Execute query ($result=$conn->query()) Close connection ( $conn->close())

To handle database connection errors in PHP, you can use the following steps: Use mysqli_connect_errno() to obtain the error code. Use mysqli_connect_error() to get the error message. By capturing and logging these error messages, database connection issues can be easily identified and resolved, ensuring the smooth running of your application.

Oracle is not only a database company, but also a leader in cloud computing and ERP systems. 1. Oracle provides comprehensive solutions from database to cloud services and ERP systems. 2. OracleCloud challenges AWS and Azure, providing IaaS, PaaS and SaaS services. 3. Oracle's ERP systems such as E-BusinessSuite and FusionApplications help enterprises optimize operations.

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.
