Being the dedicated database developer and/or administrator that you are, I don't need to remind you that the rigorous application of the principles of sound database design via data modeling is one of the cornerstones of data management. To that end, the emergence of specialized software such as Navicat Data Modeler have made the process much easier to accomplish.
CASE is a Control Flow statement that acts a lot like an IF-THEN-ELSE statement to choose a value based on the data. The CASE statement goes through conditions and returns a value when the first condition is met. So, once a condition is true, it will short circuit, thereby ignoring later clauses, and return the result. As we'll see in today's blog, it can be used to test for conditions as well as discrete values.
There are some very good reasons why data validation is best performed at the database level rather than at the application level. For instance, the same data source may be accessed by multiple applications. Therefore, you can rely on the data being consistent and valid without having to depend on validation logic being applied on the application side, which might not be consistent across different implementations. Moreover, triggers are ideal for validation because they can be executed before data is inserted or updated. Triggers can also can also prevent a database transaction from being applied while providing an error message.
The SQL LIMIT clause constrains the number of rows returned by a SELECT statement. For Microsoft databases like SQL Server or MSAccess, you can use the SELECT TOP statement to limit your results, which is Microsoft's proprietary equivalent to the SELECT LIMIT statement. However, for most relational databases (DBMSes), including MySQL/MariaDB, PostgreSQL, and Oracle, the SQL LIMIT clause can solve several problems. In today's blog, we'll explore a few of these, using Navicat for PostgreSQL.
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