Frame Specifications

Concepts covered: sqlWindowFrame

Frame specifications define exactly which rows participate in a window calculation. Every window function operates on a frame, and understanding frames is the key to unlocking the full power of window functions. Up to this point, you have been relying on the default frame, which extends from the beginning of the partition to the current row. That default works for running totals but fails for many other patterns. To build moving averages, trailing windows, and centered calculations, you need to take explicit control of the frame boundaries. Frame Syntax and Types Frame clauses follow a consistent syntax pattern that gives you fine-grained control over exactly which rows are included in each calculation. ROWS BETWEEN Syntax ROWS vs RANGE Common Frame Patterns Real-World Frame Patterns Movin

About This Interactive Section

This section is part of the Window Functions: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.