


How to perform multi-table joint query and conditional filtering in the database?
Database multi-table joint query and conditional filtering skills
In database queries, it is often necessary to extract data from multiple tables and filter by specific conditions. This article will explore how to achieve this goal efficiently and illustrate it in combination with actual cases.
Application scenarios
Suppose we need:
- Step 1: Based on the user table and user profile table, query user data that meets specific conditions (paging index, paging size, province, city, gender, age).
- Step 2: Remove the blacklisted user from the result of the first step.
- Optional step 3: Further exclude users from other tables (such as blocked tables).
Solution
There are two main strategies:
Strategy 1: Single SQL statement implements joint query of multiple tables
Use a single SQL statement to join multiple tables through JOIN
operation and add all filter conditions in the WHERE
clause. This method has few query times and is efficient. The example SQL statement is as follows:
SELECT u.*, ud.* FROM User Table u JOIN User Profile Table ud ON u.user_id = ud.user_id LEFT JOIN Blacklist table b ON u.user_id = b.user_id LEFT JOIN Mask table s ON u.user_id = s.user_id WHERE b.user_id IS NULL -- Exclude blacklist users AND s.user_id IS NULL -- Exclude masked table users AND ud.province = 'Special province' AND ud.city = 'Special City' AND ud.gender = 'Specific Gender' AND ud.age BETWEEN Specific age range LIMIT paging index, paging size;
This statement uses LEFT JOIN
to connect blacklist tables and mask tables and filters out users in these tables through the IS NULL
condition in the WHERE
clause. All operations are done in one SQL statement, with the best efficiency.
Strategy 2: Step-by-step query and filtering
First execute the query to obtain the preliminary results, and then perform subsequent filtering. This method is easy to manage and debug, but it has many queries that may affect performance. The steps are as follows:
- Step 1: Obtain preliminary user data
SELECT u.*, ud.* FROM User Table u JOIN User Profile Table ud ON u.user_id = ud.user_id WHERE ud.province = 'Special Province' AND ud.city = 'Special City' AND ud.gender = 'Specific Gender' AND ud.age BETWEEN Specific age range LIMIT paging index, paging size;
- Step 2: Filter blacklist users
SELECT t.* FROM (first step result) t LEFT JOIN Blacklist table b ON t.user_id = b.user_id WHERE b.user_id IS NULL;
- Step 3: Filter the block table user (if required)
SELECT t.* FROM (Second step 2) t LEFT JOIN mask table s ON t.user_id = s.user_id WHERE s.user_id IS NULL;
This method facilitates step-by-step processing and verification of data, but multiple queries can affect performance.
Summarize
Which strategy to choose depends on actual demand and data volume. In the case of large data volume, it is recommended to use a single SQL statement, which is more efficient. The data volume is small or for easy debugging, you can choose to query step by step.
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