Window Functions: Beginner

Every row and the big picture at once

Every row and the big picture at once

Category

SQL

Difficulty

beginner

Duration

39 minutes

Challenges

5 hands-on challenges

Topics covered: What is a Window Function?, PARTITION BY Deep Dive, ROW_NUMBER, RANK and DENSE_RANK, SUM/COUNT/AVG OVER

Lesson Sections

1. What is a Window Function? (concepts: sqlPartitionBy)

   What Window Functions Solve Consider a common analytical question: "Show me each employee's salary alongside the average salary for their department." This requires two things at once: individual row detail (each employee's name and salary) and aggregate context (the department average). Before window functions existed, you had to write a subquery or a self-join to combine these. Window functions let you do it in a single, clean pass. Comparing Approaches Here is our employee data: GROUP BY Resu

2. PARTITION BY Deep Dive

   Single Column Partition Every Electronics row sees 1,200 as the category max price (the Laptop). Every Clothing row sees 150 (the Jacket). The partitions are completely independent. You can immediately see how each product compares to the most expensive item in its category. Advanced Partitioning Once you understand basic partitioning, you can apply more sophisticated techniques to handle complex real-world scenarios like multi-dimensional groupings and edge cases. Multiple Partition Columns NUL

3. ROW_NUMBER (concepts: sqlRowNumber)

   Basic ROW_NUMBER Every employee gets a unique number from 1 to 6, ordered by salary from highest to lowest. Carol earns the most so she gets position 1. Dave earns the least so he gets position 6. No two rows ever share the same number. ROW_NUMBER + PARTITION BY Multiple ORDER BY Columns Handling NULLs in ORDER BY ROW_NUMBER Applications Dedup with ROW_NUMBER Which approach would you use to find the most recent signup per user?

4. RANK and DENSE_RANK (concepts: sqlRankDenseRank)

   How Ties Work Consider five students with test scores where two students scored 92. Here is how the three ranking functions differ on the exact same data: When Ties Matter: Rankings RANK Example DENSE_RANK Example Choosing Between Functions The choice between these three functions comes down to how you want ties handled and whether gaps in the numbering matter. Compare them side by side on the same query:

5. SUM/COUNT/AVG OVER (concepts: sqlAggregateOver)

   Regular SUM vs SUM OVER Running Totals: SUM OVER Here is how each row's running total is calculated: Row 1 (Jan 1): just 500, nothing before it. Row 2 (Jan 2): 500 + 300 = 800. Row 3 (Jan 3): 500 + 300 + 700 = 1,500. Row 4 (Jan 4): 500 + 300 + 700 + 200 = 1,700. Row 5 (Jan 5): 500 + 300 + 700 + 200 + 400 = 2,100. Each row accumulates all previous amounts plus its own. Running totals are perfect for cumulative revenue, inventory levels, progress toward a goal, or account balances. Any "how much s