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Message storage and history processing of PHP real-time chat function
With the popularity of the Internet and the development of technology, the real-time chat function has become an indispensable part of websites and applications. A missing part. Implementing the real-time chat function requires consideration of message storage and history processing. This article will introduce how to use PHP to implement these two key issues.
In real-time chat, messages need to be saved for subsequent display and query. A common practice is to store messages in a database. The following is a sample code that shows how to use PHP to store chat messages into a MySQL database:
<?php // 连接到MySQL数据库 $servername = "localhost"; $username = "username"; $password = "password"; $dbname = "chat"; $conn = new mysqli($servername, $username, $password, $dbname); // 检查连接是否成功 if ($conn->connect_error) { die("连接失败: " . $conn->connect_error); } // 获取聊天消息的内容和发送者 $message = $_POST['message']; $sender = $_POST['sender']; // 插入消息到数据库 $sql = "INSERT INTO messages (message, sender) VALUES ('$message', '$sender')"; if ($conn->query($sql) === TRUE) { echo "消息已存储"; } else { echo "存储消息失败: " . $conn->error; } // 关闭数据库连接 $conn->close(); ?>
In the above code, we first connect to the MySQL database, and then obtain the message content passed through the POST request and Sender information. We then use SQL statements to insert this data into a data table named "messages". Finally, we close the database connection.
Real-time chat functions usually need to provide history records so that users can view previous chat messages. Below is a sample code that shows how to use PHP to get history records from a MySQL database and display them on a web page: Get the last 10 chat messages from the data table. We then use a loop to output these messages to the web page one after another. If there is no history, we will output "No history yet".
To sum up, by using PHP and database, we can realize message storage and history processing of real-time chat function. In actual applications, we can further optimize the code and database structure according to needs to meet higher performance and scalability requirements.
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