Скачать или смотреть Organizing Related Tables in MySQL: The Best Approach to Optimize Database Operations

Learn the most effective method to organize related tables in MySQL, improve performance, and avoid data redundancy by implementing JOIN and SUM functions.
---
This video is based on the question https://stackoverflow.com/q/68456002/ asked by the user 'orel-22' ( https://stackoverflow.com/u/11071119/ ) and on the answer https://stackoverflow.com/a/68456217/ provided by the user 'sticky bit' ( https://stackoverflow.com/u/9661424/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How to properly organize related tables in MySQL database?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Organizing Related Tables in MySQL: The Best Approach to Optimize Database Operations

When it comes to managing data in a MySQL database, structure is key to ensuring efficiency and accuracy. If you find yourself needing to organize related tables effectively, you're not alone. Many developers grapple with how to link tables and ensure the necessary data is easily obtainable, particularly when it involves user orders in an e-commerce setting.

In this post, we will delve into a common scenario involving two tables: users and orders. We’ll explore how to properly combine these tables to display the sum of all orders for each user, weighing the pros and cons of different approaches.

Understanding the Challenge

For our example, we will consider the following two tables:

Users Table

idfirst_nameorders_amount_total1Jone56342002Mike3982830Orders Table

iduser_idorder_amount11200211503270413205220621072858125In this case, the two tables are linked by the user_id, which allows us to associate orders with specific users.

Exploring the Options

The task is to show the total sums of all orders for each user in the most efficient way possible. There are two main options to consider:

Keep the orders_amount_total field updated:

Each time an order is added to the orders table, increment the orders_amount_total for the corresponding user directly.

Remove the orders_amount_total field and calculate:

Use SQL JOIN statements and the SUM operator to dynamically calculate the total amount of orders for each user when needed.

Which Option is Better?

Option 1: Updating orders_amount_total

While this option seems straightforward and might yield instant results when querying, it introduces several significant drawbacks:

Data Redundancy: Maintaining a separate orders_amount_total can lead to inconsistencies if the data is not properly maintained.

Complicated Writes: With every new order, the system needs to perform two operations: one for the orders table and another for the users table.

Increased Error Risk: If the counters do not sync properly (e.g., due to a failure), you may get inaccurate totals.

Option 2: Using JOIN and SUM

This option is typically the better choice for most cases, and here’s why:

Data Integrity: By calculating totals as needed, you ensure that you're always pulling the latest information from the orders table, reducing the risk of errors or inconsistencies.

Reduced Complexity: You have less worry about updating totals after every order, which simplifies database operations and minimizes potential for bugs.

Scalability: Modern relational database management systems (RDBMS) are designed to handle large datasets efficiently. Tens of thousands of rows are manageable without resorting to denormalization.

Performance Considerations

While it’s true that calculating totals on-the-fly can put additional load on your server, modern optimized databases are capable of handling these operations efficiently, especially with proper indexing:

Indexing: Indexing the user_id in the orders table can dramatically improve query performance, ensuring that your database operates smoothly even under heavy load.

Optimization Techniques: Employing caching strategies, such as storing frequently accessed results temporarily, can further enhance performance.

Conclusion

In summary, while both options have their merits, using JOIN and SUM is the superior method for most applications. It helps maintain data integrity and reduce redundancy, even if it might seem daunting at first. With the right database optimization techniques, you'll find that your MySQL database can handle the demands of an expanding user base seamlessly.

By embraci