Windows vs Self-Joins

One of the most impactful things you can do with window functions is eliminate self-joins. A self-join is when a table is joined to itself, typically to compare each row with a related row in the same table. Self-joins are expensive: the engine must scan the table twice, build a join hash map, and match rows. Window functions accomplish the same comparison in a single pass over the data. Self-joins are extremely common in legacy codebases. Before window functions were widely supported, they were the only way to compare a row with its neighbors. You will encounter them frequently when working with older data warehouses or reading code written by analysts who learned SQL before window functions became standard. Recognizing these patterns and knowing how to rewrite them is a high-value skill.

About This Interactive Section

This section is part of the Window Functions: Advanced 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.

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