How to Efficiently Select Records Matching Multiple Conditions on the Same Column in SQL?

Tip of SQL multi-condition query for records in the same column

In SQL queries, filtering records based on multiple conditions, especially when these conditions apply to the same column, requires some skills. This article will explore how to handle this situation efficiently.

For example, one table associates users and tag types, and the goal is to get the contact ID that matches the checkmark in all search forms. At first glance, the following query seems intuitive:

SELECT contactid 
WHERE flag = 'Volunteer' 
AND flag = 'Uploaded'...

However, it returns no results. Because the AND operator requires the same row to meet two conditions at the same time, and such a row does not exist in this table.

To solve this problem, one way is to use GROUP BY and HAVING COUNT(*) = n, where n is the number of selected markers:

SELECT contact_id
FROM your_table
WHERE flag IN ('Volunteer', 'Uploaded', ...)
GROUP BY contact_id
HAVING COUNT(*) = 2 -- // 必须与WHERE flag IN (...) 列表中的数量匹配

This method checks whether the contact_id occurs n times with each of the n tags contained in the WHERE clause. Another way is to use join:

SELECT T1.contact_id
FROM your_table T1
JOIN your_table T2 ON T1.contact_id = T2.contact_id AND T2.flag = 'Uploaded'
-- // 如有必要，可以添加更多连接
WHERE T1.flag = 'Volunteer'

Here, multiple joins are used to associate rows representing the same contact_id with the required tags.

Which method to choose depends on the number of tags to be checked and the number of matching records. GROUP BY may be faster when dealing with a large number of tags and a small number of matches, while the join may perform better when the number of tags is small and there are many matches. It is recommended to test both methods on real data to get the best performance.

The above is the detailed content of How to Efficiently Select Records Matching Multiple Conditions on the Same Column in SQL?. For more information, please follow other related articles on the PHP Chinese website!