SQL doesn't have explicit looping constructs like `for` or `while` found in programming languages. Instead, it achieves iterative processing through techniques like cursors and procedural languages (like PL/SQL). These methods allow you to process data row by row, but they are less common than set-based operations.
SQL, at its core, is a set-based language. It excels at manipulating entire datasets at once. Unlike procedural languages, it doesn't have built-in looping mechanisms. While you can't directly loop through rows in a standard SQL query, you can achieve similar results using cursors or procedural extensions like PL/SQL. Cursors are essentially pointers to rows in a result set, allowing you to fetch and process them one at a time. Procedural languages provide more control and flexibility, enabling complex logic and data manipulation within the database environment. This approach is often used when you need to perform actions that aren't easily expressed in a set-based query, such as updating multiple rows based on conditions or performing complex calculations on each row.
While SQL's set-based approach is generally preferred, understanding cursors and procedural languages is crucial for handling complex data manipulation tasks that require row-by-row processing. This knowledge is valuable for tasks like complex data transformations, custom reporting, and integration with other applications.
SQL was designed around set theory, meaning a single statement is expected to act on an entire result set at once. This design lets the database optimizer choose the fastest execution plan without the overhead of row-by-row control flow. By thinking in sets—using joins, window functions, and aggregations—you let the engine scan, filter, and transform millions of rows in a single, highly tuned pass instead of performing procedural loops in application code.
Reserve cursors or procedural blocks for situations that can’t be cleanly expressed in a declarative query—for example, applying sequential business rules where the outcome for one row influences the next, or performing complex calculations that require branching logic. In those edge cases, a cursor lets you fetch each row, manipulate variables, and issue targeted DML statements. Keep in mind that this row-by-row processing is typically slower than set-based SQL, so use it sparingly and only after profiling alternatives.
Absolutely. Galaxy’s context-aware AI copilot can inspect a cursor or PL/SQL loop, identify the intent, and suggest an equivalent set-based rewrite. It highlights anti-patterns, proposes window-function or CTE solutions, and even benchmarks the new query so you can confirm performance gains—all without leaving the editor.