15/100 SQL Interview Tips | Walmart #shorts
Why It Matters
Identifying the longest order gaps helps businesses spot churn risk and optimize retention, while demonstrating the candidate’s proficiency with complex SQL constructs.
Key Takeaways
- •Use LAG window function to compute previous order date.
- •Calculate gap days by subtracting lag date from current order date.
- •Apply ROW_NUMBER ranking per customer to identify maximum gap.
- •Chain CTEs to organize intermediate calculations cleanly effectively.
- •Filter rank = 1 to return each customer's longest order interval.
Summary
The video walks through a Walmart interview question that asks candidates to determine each customer's longest interval between consecutive orders.
The solution hinges on the LAG window function, which brings the previous order date alongside the current one. By subtracting the lagged date from the current order date, the query derives a "gap days" column. A second window function, ROW_NUMBER, ranks these gaps per customer, allowing the maximum gap to be isolated.
The presenter demonstrates the logic with sample data, showing gaps of 7, 67, and 14 days. He builds the logic inside a common table expression (CTE) and then layers another CTE to apply the ranking. The final SELECT filters for row_number = 1, returning the start date, end date, and gap length for each customer.
Mastering this pattern showcases advanced SQL capabilities—particularly window functions and CTE chaining—that are prized in data‑engineering roles and can give candidates a competitive edge in interviews like Walmart’s.
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