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Introduction In PostgreSQL (and standard SQL in general), Aggregate Constraint is not an officially supported syntax or keyword, but rather a concept referring to constraints based on aggregated data (Aggregate Constraint / Cross-row Constraint), which is a very common problem in data processing. In practice, PostgreSQL directly prohibits using Aggregate Functions such as SUM, COUNT, AVG, MAX, MIN inside a table's CHECK constraint. The reason is that a CHECK constraint is evaluated on individual rows upon insertion or modification, whereas aggregate functions compute values across sets of multiple rows. For example, you cannot use CHECK with SUM to create a constraint ensuring the total revenue percentage of categories does not exceed 100% . Postgres will throw an error regarding the use of aggregate functions within a CHECK Constraint . Alternative Solutions To enforce an aggregate constraint rule, you can apply the following solutions: Using Triggers This is the most commo...

Introduction The IN clause is usually used in two main cases: Literal Values : When you already know the exact values to filter and the number of elements is small (from a few elements to a few dozen elements). Note that when parsing, Postgres will treat each item in Literal Values as a single node to execute the Parse Tree, so if the number of items is too large, it will consume a lot of RAM and CPU to process By the time planning is executed, the Query Planner will have to traverse this Tree to process, so you should be careful not to query with too many Literal Values as it will significantly affect performance It can be rewritten with EXISTS but it will make the query more complex, so if using Literal Values , it is best to use IN to keep the query simple and easy to understand An example of usage is filtering out orders with statuses like processing or completed . Dynamic List : When the filter list depends on the data of another table. In most cases, it can be replaced by usin...