SQL Interview Question| Running Total or Cumulative Sum: Self Join vs Window Functions
Struggling with SQL Window Functions or preparing for a Data Analyst/Data Engineer interview? In this video, we break down how to calculate a Running Total (Cumulative Sum) in SQL using different methods!
We’ll move from traditional legacy techniques to modern industry standards, exploring the exact logic behind each approach and why one method could completely crash your database server.
What you will learn:
1. The business logic behind Running Totals (Goal vs. Achievement charts).
2. Method 1: The legacy Self-Join (Inequality Join) and its performance flaws ($O(N^2)$ complexity).
3. Method 2: Modern Window Functions using SUM() OVER (ORDER BY).
4. Method 3: Advanced Partitioned Running Totals using PARTITION BY.
Whether you're writing queries for dashboards or optimization, this guide covers everything you need to know.
Agenda:
Introduction to Cumulative Sum
Business Use Cases (Goal vs. Achievement)
The Foundation Dataset
Method 1: The Self-Join (Legacy Way)
Method 2: Window Functions (Industry Standard)
Deep Dive: OVER, ORDER BY, & Framing Logic
Method 3: Partitioned Running Totals (By Region)
Summary: When to use which method?
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