The Young DBA

Think of the QUALIFY clause as the secret shortcut of the SQL world. While most of us grew up nesting subqueries just to filter the results of a window function, QUALIFY lets you do it in a single step. It acts on window functions exactly how HAVING acts on GROUP BY aggregations. Why It’s a Game Changer Cleaner Code : It eliminates the "Subquery Pyramid of Doom." No more wrapping a SELECT inside a SELECT just to get the ROW_NUMBER() = 1. Logical Flow: It filters results after window functions are calculated but before the final ORDER BY and LIMIT. Performance : Engines like Snowflake, BigQuery, and Teradata can optimize the execution plan better when the filter is explicit. The Syntax in Action Instead of writing 15 lines of CTEs to find the most recent login for every user, you can simply write: SELECT user_id, login_time, device_type FROM user_logs QUALIFY ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY login_time DESC) = 1;

AWS documentation also says horizontal physical partitioning of large table data is best practices instead keeping all in one physical file. There are advantages and disadvantages to using InnoDB file-per-table tablespaces, depending on your application. To determine the best approach for your application, go to InnoDB File-Per-Table Mode in the MySQL documentation. We don't recommend allowing tables to grow to the maximum file size. In general, a better practice is to partition data into smaller tables, which can improve performance and recovery times. One option that you can use for breaking a large table up into smaller tables is partitioning. Partitioning distributes portions of your large table into separate files based on rules that you specify. For example, if you store transactions by date, you can create partitioning rules that distribute older transactions into separate files using partitioning. Then periodically, you can archive the historical transaction data th...