Efficient Daily Data Statistics and Performance Optimization with PHP and MySQL

Introduction

In the era of big data, data statistics and analysis have become increasingly important. In web development, it is often necessary to perform statistical and optimization operations on daily data over a certain period. This article shares how to efficiently implement daily data statistics and performance optimization using PHP combined with MySQL.

Database Design

First, it is essential to design an appropriate database structure to store the statistical data. Suppose we want to track daily website visits, we can create a table named visits with the following structure:

CREATE TABLE visits (
   id INT AUTO_INCREMENT PRIMARY KEY,
   visit_date DATE,
   visits INT
);

Here, id is an auto-increment primary key, visit_date stores the visit date, and visits represents the number of visits on that day.

Daily Data Statistics Implementation

We can use a PHP script to fetch daily visit counts from the database, as shown below:

    $conn = mysqli_connect("localhost", "username", "password", "database");
    if (!$conn) {
        die("Connection failed: " . mysqli_connect_error());
    }
    $sql = "SELECT visit_date, visits FROM visits";
    $result = mysqli_query($conn, $sql);
    if (mysqli_num_rows($result) > 0) {
        while ($row = mysqli_fetch_assoc($result)) {
            $visit_date = $row["visit_date"];
            $visits = $row["visits"];
            // Example statistical operation
            $average_visits = $visits / $total_days;
            echo "Date: " . $visit_date . " Average visits: " . $average_visits . "<br>";
        }
    } else {
        echo "No results found";
    }
    mysqli_close($conn);

The above code uses mysqli_fetch_assoc to retrieve each row of data and perform statistical operations, then outputs the results.

Performance Optimization Suggestions

When dealing with large datasets, proper indexing can significantly improve query performance. Creating an index on the visit_date field, for example:

CREATE INDEX visit_date_index ON visits (visit_date);

This index helps the database quickly locate rows for specific dates, accelerating retrieval.

Conclusion

This article introduced how to use PHP and MySQL to perform daily data statistics over a period and improve performance through database table design and indexing. This approach is practical for statistical analysis of website visit data and helps developers efficiently process and analyze data.