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Table of Contents
What is CROSS JOIN? When will it be used?
What pitfalls should be paid attention to when using it?
How to use CROSS JOIN reasonably?
Home Database Mysql Tutorial mysql cross join

mysql cross join

Jul 11, 2025 am 02:37 AM

CROSS JOIN is a Cartesian product operation in MySQL, which is often used to generate a combination of all rows in two tables. Its syntax can be written as SELECT FROM table1 CROSS JOIN table2 or SELECT FROM table1, table2, but it is recommended to use CROSS JOIN to improve semantic clarity. Common uses include report generation and enumeration combination scenarios, such as the full combination of colors and sizes. Note when using: 1. Explosion of data volume may cause performance problems; 2. The WHERE condition should not be mistakenly equated with INNER JOIN due to different execution logic; 3. High concurrency may affect system performance. Methods of reasonable use include: 1. To clarify whether the business needs a full combination; 2. To limit the data scope before connection; 3. To consider using other methods to avoid unnecessary Cartesian products.

mysql cross join

CROSS JOIN in MySQL seems simple, but it is easy to cause problems if you don’t use it well. It is actually a "Cartesian product" operation, combining each row in the two tables, and the result is the product of the number of rows of the two tables. If you have no idea about the amount of data, you may find tens of thousands or even hundreds of thousands of results by accident, which will get stuck in the database.

mysql cross join

Let’s take a look at a few key points from the perspective of actual use.


What is CROSS JOIN? When will it be used?

CROSS JOIN is a join without any conditions, and all rows of the two tables are combined in pairs. For example, you have a color table (red, blue, green) and a size table (S, M, L). After using CROSS JOIN , it will become 3×3=9 records: red-S, red-M...green-L.

mysql cross join

This operation is particularly useful when generating and enumeration combinations of reports. For example, if you want to list all products and all regions for subsequent filling of sales data, using CROSS JOIN is a good choice.

Syntax can be written as:

mysql cross join
 SELECT *
FROM colors
CROSS JOIN sizes;

You can also write it directly without using the CROSS JOIN keyword:

 SELECT *
FROM colors, sizes;

The two writing methods have the same effect, but it is recommended to use CROSS JOIN first, which has clearer semantics.


What pitfalls should be paid attention to when using it?

  1. Explosion of data volume
    If the two tables are 1000 rows and 500 rows, the result is 500,000 rows. If you connect the third table, it is easy to exceed expectations, resulting in slow querying, insufficient memory or even locking the table.

  2. Don't mistake it for INNER JOIN
    Many novices think that writing CROSS JOIN and adding WHERE condition is equivalent to INNER JOIN . Although the result may be the same, in terms of execution logic, CROSS JOIN first does Cartesian product and then filters, which is less efficient.

  3. Performance issues are easily overlooked
    Even if both tables are not large, if such unconditional connections are often called, it will affect the overall performance, especially when concurrency is high.


How to use CROSS JOIN reasonably?

  • Clarify whether business needs really need combinations
    For example, if you want to generate a product SKU, the color sizes do need to be fully combined, then there is no problem; but if you just want to check all the sizes corresponding to a certain color, you should use JOIN with conditions.

  • Try to limit the data range
    You can filter the data on both sides before CROSS JOIN , such as taking only the currently valid color or size to reduce the number of combinations.

  • Consider whether it can be replaced by other methods
    For example, in some cases, UNION ALL or temporary tables can be used instead to avoid unnecessary Cartesian products.


Basically that's it. CROSS JOIN is not complicated, but it is like a double-edged sword. If used well, it can quickly generate combined data, and if used poorly, it will easily drag down the system. As long as you pay attention to the data scale and usage scenarios, there will generally be no major problems.

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