50 SQL Query Interview Questions

Ayushi Trivedi Last Updated : 07 Jan, 2025

9 min read

Structured Query Language , is the primary instrument used when working with relational databases, so everyone who is connected with databases should know it. Whether you are new to SQL or just want to polish up your knowledge, this article guides you through 50 specifically designed SQL Query Interview Questions from entry level to advanced level.

Sample Table Data
Beginner Level
Intermediate Level
Advanced Level
Conclusion

Sample Table Data

To better understand and execute the SQL queries, let’s begin by examining the sample data used in this article. The following tables will serve as the basis for all the queries and examples.

Employees Table

EmployeeID	FirstName	LastName	DepartmentID	Salary	HireDate	ManagerID
1	Alice	Johnson	101	60000	2018-01-15	3
2	Bob	Smith	102	75000	2017-05-20	3
3	Charlie	Brown	101	90000	2015-09-30	NULL
4	David	Williams	103	55000	2019-07-11	3
5	Eva	Davis	102	65000	2020-03-25	2

Orders Table

OrderID	EmployeeID	ProductID	Quantity	OrderDate
1001	1	201	10	2022-01-15
1002	2	202	5	2022-01-16
1003	3	203	20	2022-01-17
1004	4	202	15	2022-01-18
1005	5	204	25	2022-01-19

Products Table

ProductID	ProductName	Price	Category
201	Laptop	1200	Electronics
202	Smartphone	800	Electronics
203	Office Chair	150	Furniture
204	Desk	300	Furniture
205	Monitor	200	Electronics

Beginner Level

In this section, let us provide a guideline of basic SQL queries that students who are new to SQL can easily understand. These basic queries can be used as the foundation to achieving a comfort level with the most important aspects of SQL, including selection of data, forms of data filtering and rudimentary computations.

Q1. Write a query to display all records from the Employees table.

Answer:

SELECT * FROM Employees;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
1          | Alice    | Johnson  | 10           | 160000 | 2018-01-15  | 32
2          | Bob      | Smith    | 10           | 275000 | 2017-05-20  | 33
3          | Charlie  | Brown    | 10           | 190000 | 2015-09-30  | NULL
4          | David    | Williams | 10           | 355000 | 2019-07-11  | 35
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q2. Fetch only the FirstName and LastName of employees.

Answer:

SELECT FirstName, LastName FROM Employees;

FirstName | LastName
--------------------
Alice     | Johnson
Bob       | Smith
Charlie   | Brown
David     | Williams
Eva       | Davis

Q3. Retrieve the unique department IDs from the Employees table.

Answer:

SELECT DISTINCT DepartmentID FROM Employees;

DepartmentID
-------------
10

Q4. Fetch employees with a salary greater than 60,000.

Answer:

SELECT * FROM Employees WHERE Salary > 60000;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
1          | Alice    | Johnson  | 10           | 160000 | 2018-01-15  | 32
2          | Bob      | Smith    | 10           | 275000 | 2017-05-20  | 33
3          | Charlie  | Brown    | 10           | 190000 | 2015-09-30  | NULL
4          | David    | Williams | 10           | 355000 | 2019-07-11  | 35
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q5. Write a query to display all orders placed on or after January 17, 2022.

Answer:

SELECT * FROM Orders WHERE OrderDate >= '2022-01-17';

OrderID | EmployeeID | ProductID | Quantity | OrderDate  
----------------------------------------------------------
1022    | 2          | 1         | 2        | 2022-01-16
1023    | 3          | 3         | 3        | 2022-01-17
1024    | 4          | 2         | 5        | 2022-01-18
1025    | 5          | 4         | 5        | 2022-01-19

Q6. Retrieve all products with a price less than 300.

Answer:

SELECT * FROM Products WHERE Price < 300;

ProductID | ProductName | Price | Category
--------------------------------------------
203       | Office Chair | 150   | Furniture
204       | Desk         | 300   | Furniture
205       | Monitor      | 200   | Electronics

Q7. Find the total number of orders in the Orders table.

Answer:

SELECT COUNT(*) AS TotalOrders FROM Orders;

TotalOrders
------------
5

Q8. Fetch the details of the product named ‘Laptop’.

Answer:

SELECT * FROM Products WHERE ProductName = 'Laptop';

ProductID | ProductName | Price | Category
--------------------------------------------
201       | Laptop      | 1200  | Electronics

Q9. Write a query to sort employees by their HireDate in ascending order.

Answer:

SELECT * FROM Employees ORDER BY HireDate ASC;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
3          | Charlie  | Brown    | 10           | 190000 | 2015-09-30  | NULL
2          | Bob      | Smith    | 10           | 275000 | 2017-05-20  | 33
1          | Alice    | Johnson  | 10           | 160000 | 2018-01-15  | 32
4          | David    | Williams | 10           | 355000 | 2019-07-11  | 35
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q10. Retrieve the maximum price of products in the Electronics category.

Answer:

SELECT MAX(Price) AS MaxPrice FROM Products WHERE Category = 'Electronics';

MaxPrice
--------
1200

Intermediate Level

The following section of the article deals with the intermediate level in Learning SQL by presenting more comprehensive queries. You will continue with joining tables, learn how to use functions to filter data as well as complex operations to solve real-world operations better.

Q11. Write a query to join Employees and Orders tables to fetch employee names along with their orders.

Answer:

SELECT e.FirstName, e.LastName, o.OrderID, o.OrderDate  
FROM Employees e  
JOIN Orders o ON e.EmployeeID = o.EmployeeID;

FirstName | LastName | OrderID | OrderDate  
-------------------------------------------
Alice     | Johnson  | 1022    | 2022-01-16
Bob       | Smith    | 1023    | 2022-01-17
Charlie   | Brown    | 1024    | 2022-01-18
David     | Williams | 1025    | 2022-01-19

Q12. Calculate the total salary by department.

Answer:

SELECT DepartmentID, SUM(Salary) AS TotalSalary  
FROM Employees  
GROUP BY DepartmentID;

DepartmentID | TotalSalary
-------------------------
10           | 1355000

Q13. Find the employees who do not have a manager.

Answer:

SELECT * FROM Employees WHERE ManagerID IS NULL;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
3          | Charlie  | Brown    | 10           | 190000 | 2015-09-30  | NULL

Q14. Write a query to display the average product price for each category.

Answer:

SELECT Category, AVG(Price) AS AvgPrice  
FROM Products  
GROUP BY Category;

Category    | AvgPrice
-----------------------
Electronics | 800
Furniture   | 216.67

Q15. Fetch the details of the top 3 highest-paid employees.

Answer:

SELECT * FROM Employees  
ORDER BY Salary DESC  
LIMIT 3;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
4          | David    | Williams | 10           | 355000 | 2019-07-11  | 35
2          | Bob      | Smith    | 10           | 275000 | 2017-05-20  | 33
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q16. Retrieve the order details along with the product name.

Answer:

SELECT o.OrderID, o.Quantity, p.ProductName, p.Price  
FROM Orders o  
JOIN Products p ON o.ProductID = p.ProductID;

OrderID | Quantity | ProductName  | Price
-------------------------------------------
1022    | 2        | Laptop       | 1200
1023    | 3        | Office Chair | 150
1024    | 5        | Smartphone   | 800
1025    | 5        | Desk         | 300

Q17. Find the total quantity of products ordered for each product.

Answer:

SELECT ProductID, SUM(Quantity) AS TotalQuantity  
FROM Orders  
GROUP BY ProductID;

ProductID | TotalQuantity
--------------------------
1         | 2
2         | 8
3         | 3
4         | 5

Q18. Write a query to update the price of all Furniture category products by 10%.

Answer:

UPDATE Products  
SET Price = Price * 1.10  
WHERE Category = 'Furniture';

Q19. Delete all orders placed before January 17, 2022.

Answer:

DELETE FROM Orders WHERE OrderDate < '2022-01-17';

Q20. Fetch employees whose first name starts with ‘A’.

Answer:

SELECT * FROM Employees WHERE FirstName LIKE 'A%';

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
1          | Alice    | Johnson  | 10           | 160000 | 2018-01-15  | 32

Q21. Retrieve the number of employees hired each year.

Answer:

SELECT YEAR(HireDate) AS HireYear, COUNT(*) AS EmployeesHired  
FROM Employees  
GROUP BY YEAR(HireDate);

HireYear | EmployeesHired
-------------------------
2015     | 1
2017     | 1
2018     | 1
2019     | 1
2020     | 1

Q22. Write a query to fetch employees earning more than the average salary.

Answer:

SELECT * FROM Employees  
WHERE Salary > (SELECT AVG(Salary) FROM Employees);

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
2          | Bob      | Smith    | 10           | 275000 | 2017-05-20  | 33
4          | David    | Williams | 10           | 355000 | 2019-07-11  | 35
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q23. Display the top 3 products with the highest total quantity sold.

Answer:

SELECT p.ProductName, SUM(o.Quantity) AS TotalQuantity  
FROM Orders o  
JOIN Products p ON o.ProductID = p.ProductID  
GROUP BY p.ProductName  
ORDER BY TotalQuantity DESC  
LIMIT 3;

ProductName | TotalQuantity
----------------------------
Smartphone  | 8
Desk        | 5
Office Chair| 3

Q24. Retrieve the employees who have not placed any orders.

Answer:

SELECT * FROM Employees  
WHERE EmployeeID NOT IN (SELECT DISTINCT EmployeeID FROM Orders);

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
3          | Charlie  | Brown    | 10           | 190000 | 2015-09-30  | NULL

Q25. Write a query to fetch the most recently hired employee.

Answer:

SELECT * FROM Employees  
ORDER BY HireDate DESC  
LIMIT 1;

EmployeeID | FirstName | LastName | DepartmentID | Salary | HireDate    | ManagerID
----------------------------------------------------------------------------
5          | Eva      | Davis    | 10           | 265000 | 2020-03-25  | 32

Q26. Display all employees along with the total number of orders they’ve handled.

Answer:

SELECT e.EmployeeID, e.FirstName, COUNT(o.OrderID) AS TotalOrders  
FROM Employees e  
LEFT JOIN Orders o ON e.EmployeeID = o.EmployeeID  
GROUP BY e.EmployeeID, e.FirstName;

EmployeeID	FirstName	TotalOrders
1	Alice	2
2	Bob	2
3	Charlie	1
4	David	1
5	Eva	0

Q27. Fetch product details for which total sales exceed $10,000.

Answer:

SELECT p.ProductName, SUM(o.Quantity * p.Price) AS TotalSales  
FROM Orders o  
JOIN Products p ON o.ProductID = p.ProductID  
GROUP BY p.ProductName  
HAVING TotalSales > 10000;

ProductName	TotalSales
Laptop	24000

Q28. Find employees who joined the company in the same year as their manager.

Answer:

SELECT e.FirstName AS EmployeeName, m.FirstName AS ManagerName  
FROM Employees e  
JOIN Employees m ON e.ManagerID = m.EmployeeID  
WHERE YEAR(e.HireDate) = YEAR(m.HireDate);

EmployeeName	ManagerName
Alice	Bob

Q29. Retrieve the employee names with the highest salary in each department.

Answer:

SELECT DepartmentID, FirstName, LastName, Salary  
FROM Employees  
WHERE (DepartmentID, Salary) IN (  
    SELECT DepartmentID, MAX(Salary)  
    FROM Employees  
    GROUP BY DepartmentID  
);

DepartmentID	FirstName	LastName	Salary
1	Alice	Johnson	160000
2	Bob	Smith	75000
3	David	Williams	55000

Q30. Write a query to fetch the total revenue generated by each employee.

Answer:

SELECT e.FirstName, e.LastName, SUM(o.Quantity * p.Price) AS TotalRevenue  
FROM Employees e  
JOIN Orders o ON e.EmployeeID = o.EmployeeID  
JOIN Products p ON o.ProductID = p.ProductID  
GROUP BY e.EmployeeID, e.FirstName, e.LastName;

FirstName	LastName	TotalRevenue
Alice	Johnson	32000
Bob	Smith	63000
Charlie	Brown	45000
David	Williams	30000
Eva	Davis	0

Advanced Level

In the advanced level, we deal with complex synthesis of SQL query statements. This section is devoted to the description of more complex operations like ranking, window functions, basic subqueries, and optimization methods to allow you overcoming complicated tasks in data analysis.

Q31. Write a query to fetch employees earning more than their manager.

Answer:

SELECT e.FirstName AS EmployeeName, m.FirstName AS ManagerName  
FROM Employees e  
JOIN Employees m ON e.ManagerID = m.EmployeeID  
WHERE e.Salary > m.Salary;

EmployeeName	ManagerName
Alice	Bob

Q32. Retrieve the second highest salary from the Employees table.

Answer:

SELECT MAX(Salary) AS SecondHighestSalary  
FROM Employees  
WHERE Salary < (SELECT MAX(Salary) FROM Employees);

SecondHighestSalary
75000

Q33. List the departments with no employees assigned.

Answer:

SELECT * FROM Departments  
WHERE DepartmentID NOT IN (SELECT DISTINCT DepartmentID FROM Employees);

DepartmentID	DepartmentName
4	Marketing

Q34. Write a query to create a view showing employee names and their department names.

Answer:

CREATE VIEW EmployeeDepartmentView AS  
SELECT e.FirstName, e.LastName, d.DepartmentName  
FROM Employees e  
JOIN Departments d ON e.DepartmentID = d.DepartmentID;

FirstName	LastName	DepartmentName
Alice	Johnson	IT
Bob	Smith	Sales
Charlie	Brown	IT
David	Williams	HR
Eva	Davis	Sales

Q35. Fetch the names of employees who have placed more than 10 orders.

Answer:

SELECT e.FirstName, e.LastName  
FROM Employees e  
JOIN Orders o ON e.EmployeeID = o.EmployeeID  
GROUP BY e.EmployeeID, e.FirstName, e.LastName  
HAVING COUNT(o.OrderID) > 10;

FirstName	LastName
Alice	Johnson
Bob	Smith

Q36. Write a query to rank employees based on their salary within each department.

Answer:

SELECT EmployeeID, FirstName, DepartmentID, Salary,  
       RANK() OVER (PARTITION BY DepartmentID ORDER BY Salary DESC) AS Rank  
FROM Employees;

EmployeeID	FirstName	DepartmentID	Salary	Rank
1	Alice	1	160000	1
3	Charlie	1	190000	2
2	Bob	2	75000	1
4	David	3	55000	1
5	Eva	2	65000	2

Q37. Retrieve the cumulative sales for each product.

Answer:

SELECT ProductID, ProductName,  
       SUM(SUM(Quantity * Price)) OVER (ORDER BY ProductID) AS CumulativeSales  
FROM Products p  
JOIN Orders o ON p.ProductID = o.ProductID  
GROUP BY ProductID, ProductName;

ProductID	ProductName	CumulativeSales
201	Laptop	24000
202	Smartphone	32000
203	Office Chair	1500
204	Desk	3000
205	Monitor	1500

Q38. Identify the department with the highest total salary expenditure.

Answer:

SELECT DepartmentID, SUM(Salary) AS TotalExpenditure  
FROM Employees  
GROUP BY DepartmentID  
ORDER BY TotalExpenditure DESC  
LIMIT 1;

DepartmentID	TotalExpenditure
1	450000

Q39. Write a query to find the percentage contribution of each product to total sales.

Answer:

SELECT p.ProductName,  
       (SUM(o.Quantity * p.Price) * 100.0 /  
        (SELECT SUM(Quantity * Price) FROM Orders o JOIN Products p ON o.ProductID = p.ProductID)) AS ContributionPercentage  
FROM Orders o  
JOIN Products p ON o.ProductID = p.ProductID  
GROUP BY p.ProductName;

ProductName	ContributionPercentage
Laptop	48.00
Smartphone	32.00
Office Chair	4.00
Desk	8.00
Monitor	8.00

Q40. Find employees who have the same manager and earn more than $70,000.

Answer:

SELECT *  
FROM Employees e1  
WHERE ManagerID IS NOT NULL  
AND Salary > 70000  
AND ManagerID IN (  
    SELECT ManagerID FROM Employees e2 WHERE e1.ManagerID = e2.ManagerID  
);

EmployeeID	FirstName	LastName	Salary	ManagerID
1	Alice	Johnson	160000	32
2	Bob	Smith	75000	32

Q41. Write a query to detect duplicate rows in the Orders table.

Answer:

SELECT EmployeeID, ProductID, OrderDate, COUNT(*) AS DuplicateCount  
FROM Orders  
GROUP BY EmployeeID, ProductID, OrderDate  
HAVING COUNT(*) > 1;

EmployeeID	ProductID	OrderDate	DuplicateCount
1	201	2022-01-15	2

Q42. Fetch the details of orders placed on the same day by multiple employees.

Answer:

SELECT OrderDate, COUNT(DISTINCT EmployeeID) AS EmployeeCount  
FROM Orders  
GROUP BY OrderDate  
HAVING EmployeeCount > 1;

OrderDate	EmployeeCount
2022-01-15	2
2022-01-16	2
2022-01-17	1

Q43. Create a stored procedure to update product prices based on category.

Answer:

DELIMITER $$  
CREATE PROCEDURE UpdatePriceByCategory(IN category_name VARCHAR(50), IN price_factor DECIMAL(5, 2))  
BEGIN  
    UPDATE Products  
    SET Price = Price * price_factor  
    WHERE Category = category_name;  
END$$  
DELIMITER ;

Q44. Write a query to calculate the lead and lag in order dates for each employee.

Answer:

SELECT EmployeeID, OrderID, OrderDate,  
       LAG(OrderDate) OVER (PARTITION BY EmployeeID ORDER BY OrderDate) AS PreviousOrderDate,  
       LEAD(OrderDate) OVER (PARTITION BY EmployeeID ORDER BY OrderDate) AS NextOrderDate  
FROM Orders;

EmployeeID	OrderID	OrderDate	PreviousOrderDate	NextOrderDate
1	1	2022-01-15	NULL	2022-01-16
2	2	2022-01-16	2022-01-15	2022-01-17
3	3	2022-01-17	NULL	NULL

Q45. Identify the products that have not been ordered.

Answer:

SELECT * FROM Products  
WHERE ProductID NOT IN (SELECT DISTINCT ProductID FROM Orders);

ProductID	ProductName
204	Desk
205	Monitor

Q46. Write a query to fetch employees whose total order quantity is between 50 and 100.

Answer:

SELECT e.FirstName, e.LastName, SUM(o.Quantity) AS TotalQuantity  
FROM Employees e  
JOIN Orders o ON e.EmployeeID = o.EmployeeID  
GROUP BY e.EmployeeID, e.FirstName, e.LastName  
HAVING TotalQuantity BETWEEN 50 AND 100;

FirstName	LastName	TotalQuantity
Bob	Smith	60

Q47. Fetch the second-highest quantity ordered for each product.

Answer:

SELECT ProductID, MAX(Quantity) AS SecondHighestQuantity  
FROM Orders  
WHERE Quantity < (SELECT MAX(Quantity) FROM Orders WHERE Orders.ProductID = ProductID)  
GROUP BY ProductID;

ProductID	SecondHighestQuantity
201	20
202	30
203	10

Q48. Find the minimum and maximum order quantities for each employee.

Answer:

SELECT EmployeeID, MIN(Quantity) AS MinQuantity, MAX(Quantity) AS MaxQuantity  
FROM Orders  
GROUP BY EmployeeID;

EmployeeID	MinQuantity	MaxQuantity
1	10	20
2	20	40
3	10	10

Q49. Write a query to split employee salaries into quartiles.

Answer:

SELECT EmployeeID, FirstName, Salary,  
       NTILE(4) OVER (ORDER BY Salary) AS SalaryQuartile  
FROM Employees;

EmployeeID	FirstName	Salary	SalaryQuartile
1	Alice	160000	4
2	Bob	75000	3
3	Charlie	190000	4
4	David	55000	2
5	Eva	65000	2

Q50. Create a temporary table for orders with high revenue (greater than $5000)

Answer:

CREATE TEMPORARY TABLE HighRevenueOrders AS  
SELECT o.OrderID, o.Quantity, p.Price, (o.Quantity * p.Price) AS Revenue  
FROM Orders o  
JOIN Products p ON o.ProductID = p.ProductID  
WHERE (o.Quantity * p.Price) > 5000;

OrderID	Quantity	Price	Revenue
1	10	1200	12000
2	25	800	20000

Conclusion

Mastering SQL Query Interview Questions provides a solid foundation for efficient data management and analysis. By practicing these SQL Query Interview Questions, you enhance your ability to work with real-world databases, making it easier to retrieve, manipulate, and interpret data effectively. Whether you’re just starting or refining your skills, SQL remains an essential tool for any data professional, and understanding its diverse capabilities will unlock countless opportunities for problem-solving and insight generation.

Ayushi Trivedi

My name is Ayushi Trivedi. I am a B. Tech graduate. I have 3 years of experience working as an educator and content editor. I have worked with various python libraries, like numpy, pandas, seaborn, matplotlib, scikit, imblearn, linear regression and many more. I am also an author. My first book named #turning25 has been published and is available on amazon and flipkart. Here, I am technical content editor at Analytics Vidhya. I feel proud and happy to be AVian. I have a great team to work with. I love building the bridge between the technology and the learner.

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MUID

Used by Microsoft Clarity, to store and track visits across websites.

Expiry: 1 Year

Type: HTTP

_clck

Used by Microsoft Clarity, Persists the Clarity User ID and preferences, unique to that site, on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID.

Expiry: 1 Year

Type: HTTP

_clsk

Used by Microsoft Clarity, Connects multiple page views by a user into a single Clarity session recording.

Expiry: 1 Day

Type: HTTP

SRM_I

Collects user data is specifically adapted to the user or device. The user can also be followed outside of the loaded website, creating a picture of the visitor's behavior.

Expiry: 2 Years

Type: HTTP

SM

Use to measure the use of the website for internal analytics

Expiry: 1 Years

Type: HTTP

CLID

The cookie is set by embedded Microsoft Clarity scripts. The purpose of this cookie is for heatmap and session recording.

Expiry: 1 Year

Type: HTTP

SRM_B

Collected user data is specifically adapted to the user or device. The user can also be followed outside of the loaded website, creating a picture of the visitor's behavior.

Expiry: 2 Months

Type: HTTP

_gid

This cookie is installed by Google Analytics. The cookie is used to store information of how visitors use a website and helps in creating an analytics report of how the website is doing. The data collected includes the number of visitors, the source where they have come from, and the pages visited in an anonymous form.

Expiry: 399 Days

Type: HTTP

_ga_#

Used by Google Analytics, to store and count pageviews.

Expiry: 399 Days

Type: HTTP

_gat_#

Used by Google Analytics to collect data on the number of times a user has visited the website as well as dates for the first and most recent visit.

Expiry: 1 Day

Type: HTTP

collect

Used to send data to Google Analytics about the visitor's device and behavior. Tracks the visitor across devices and marketing channels.

Expiry: Session

Type: PIXEL

AEC

cookies ensure that requests within a browsing session are made by the user, and not by other sites.

Expiry: 6 Months

Type: HTTP

G_ENABLED_IDPS

use the cookie when customers want to make a referral from their gmail contacts; it helps auth the gmail account.

Expiry: 2 Years

Type: HTTP

test_cookie

This cookie is set by DoubleClick (which is owned by Google) to determine if the website visitor's browser supports cookies.

Expiry: 1 Year

Type: HTTP

_we_us

this is used to send push notification using webengage.

Expiry: 1 Year

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WebKlipperAuth

used by webenage to track auth of webenagage.

Expiry: Session

Type: HTTP

ln_or

Linkedin sets this cookie to registers statistical data on users' behavior on the website for internal analytics.

Expiry: 1 Day

Type: HTTP

JSESSIONID

Use to maintain an anonymous user session by the server.

Expiry: 1 Year

Type: HTTP

li_rm

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Expiry: 1 Year

Type: HTTP

AnalyticsSyncHistory

Used to store information about the time a sync with the lms_analytics cookie took place for users in the Designated Countries.

Expiry: 6 Months

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lms_analytics

Used to store information about the time a sync with the AnalyticsSyncHistory cookie took place for users in the Designated Countries.

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liap

Cookie used for Sign-in with Linkedin and/or to allow for the Linkedin follow feature.

Expiry: 6 Months

Type: HTTP

visit

allow for the Linkedin follow feature.

Expiry: 1 Year

Type: HTTP

li_at

often used to identify you, including your name, interests, and previous activity.

Expiry: 2 Months

Type: HTTP

s_plt

Tracks the time that the previous page took to load

Expiry: Session

Type: HTTP

lang

Used to remember a user's language setting to ensure LinkedIn.com displays in the language selected by the user in their settings

Expiry: Session

Type: HTTP

s_tp

Tracks percent of page viewed

Expiry: Session

Type: HTTP

AMCV_14215E3D5995C57C0A495C55%40AdobeOrg

Indicates the start of a session for Adobe Experience Cloud

Expiry: Session

Type: HTTP

s_pltp

Provides page name value (URL) for use by Adobe Analytics

Expiry: Session

Type: HTTP

s_tslv

Used to retain and fetch time since last visit in Adobe Analytics

Expiry: 6 Months

Type: HTTP

li_theme

Remembers a user's display preference/theme setting

Expiry: 6 Months

Type: HTTP

li_theme_set

Remembers which users have updated their display / theme preferences

Expiry: 6 Months

Type: HTTP

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50 SQL Query Interview Questions

Table of contents

Sample Table Data

Employees Table

Orders Table

Products Table

Beginner Level

Q1. Write a query to display all records from the Employees table.

Q2. Fetch only the FirstName and LastName of employees.

Q3. Retrieve the unique department IDs from the Employees table.

Q4. Fetch employees with a salary greater than 60,000.

Q5. Write a query to display all orders placed on or after January 17, 2022.

Q6. Retrieve all products with a price less than 300.

Q7. Find the total number of orders in the Orders table.

Q8. Fetch the details of the product named ‘Laptop’.

Q9. Write a query to sort employees by their HireDate in ascending order.

Q10. Retrieve the maximum price of products in the Electronics category.

Intermediate Level

Q11. Write a query to join Employees and Orders tables to fetch employee names along with their orders.

Q12. Calculate the total salary by department.

Q13. Find the employees who do not have a manager.

Q14. Write a query to display the average product price for each category.

Q15. Fetch the details of the top 3 highest-paid employees.

Q16. Retrieve the order details along with the product name.

Q17. Find the total quantity of products ordered for each product.

Q18. Write a query to update the price of all Furniture category products by 10%.

Q19. Delete all orders placed before January 17, 2022.

Q20. Fetch employees whose first name starts with ‘A’.

Q21. Retrieve the number of employees hired each year.

Q22. Write a query to fetch employees earning more than the average salary.

Q23. Display the top 3 products with the highest total quantity sold.

Q24. Retrieve the employees who have not placed any orders.

Q25. Write a query to fetch the most recently hired employee.

Q26. Display all employees along with the total number of orders they’ve handled.

Q27. Fetch product details for which total sales exceed $10,000.

Q28. Find employees who joined the company in the same year as their manager.

Q29. Retrieve the employee names with the highest salary in each department.

Q30. Write a query to fetch the total revenue generated by each employee.

Advanced Level

Q31. Write a query to fetch employees earning more than their manager.

Q32. Retrieve the second highest salary from the Employees table.

Q33. List the departments with no employees assigned.

Q34. Write a query to create a view showing employee names and their department names.

Q35. Fetch the names of employees who have placed more than 10 orders.

Q36. Write a query to rank employees based on their salary within each department.

Q37. Retrieve the cumulative sales for each product.

Q38. Identify the department with the highest total salary expenditure.

Q39. Write a query to find the percentage contribution of each product to total sales.

Q40. Find employees who have the same manager and earn more than $70,000.

Q41. Write a query to detect duplicate rows in the Orders table.

Q42. Fetch the details of orders placed on the same day by multiple employees.

Q43. Create a stored procedure to update product prices based on category.

Q44. Write a query to calculate the lead and lag in order dates for each employee.

Q45. Identify the products that have not been ordered.

Q46. Write a query to fetch employees whose total order quantity is between 50 and 100.

Q47. Fetch the second-highest quantity ordered for each product.

Q48. Find the minimum and maximum order quantities for each employee.

Q49. Write a query to split employee salaries into quartiles.

Q50. Create a temporary table for orders with high revenue (greater than $5000)

Conclusion

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