SWIGGY SQL Interview Question | Group by clause | timestamdiff function | Udit Soni
🔥 Welcome to the Sixth Video of the SQL Interview Series! 🔥
Script:
CREATE TABLE order_details (
orderid INT PRIMARY KEY,
custid INT,
city VARCHAR(50),
order_date DATE,
del_partner VARCHAR(50),
order_time TIME,
deliver_time TIME,
predicted_time INT,
aov DECIMAL(10, 2)
);
INSERT INTO order_details (orderid, custid, city, order_date, del_partner, order_time, deliver_time, predicted_time, aov)
VALUES
(1, 101, 'Bangalore', '2024-01-01', 'PartnerA', '10:00:00', '11:30:00', 60, 100.00),
(2, 102, 'Chennai', '2024-01-02', 'PartnerB', '12:00:00', '13:15:00', 45, 200.00),
(3, 103, 'Bangalore', '2024-01-03', 'PartnerA', '14:00:00', '15:45:00', 60, 300.00),
(4, 104, 'Chennai', '2024-01-04', 'PartnerB', '16:00:00', '17:30:00', 90, 400.00);
SQL interview questions Swiggy / Calculate delayed orders SQL / DATEDIFF function in SQL / Delivery partner performance SQL / Time comparison
SQL query / Swiggy data analyst interview / COUNT with condition SQL / Logistics SQL interview questions / Actual vs predicted time SQL / Real-time SQL problems
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Struggling with SQL interview questions from top companies? In this 6th video of the SQL for Interviews series, we break down Swiggy’s REAL interview question:
✅ What You’ll Learn:
How to use DATEDIFF() or TIMESTAMPDIFF() for time comparisons
Efficiently COUNT delayed orders with conditional aggregation
Avoid NULL traps in delivery time datasets
Structure queries for real-world logistics problems
💡 Perfect For:
SQL beginners & data analysts
Developers targeting food-tech roles (Swiggy, Zomato, Uber Eats)
Anyone mastering date-time functions in SQL
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