Advanced SQL Interview Questions

If you are a Developer or a Database Administrator or else a Data Scientist who's eagerly seeking the answers for these Advanced SQL Interview Questions you'd encountered in your last technical interview, let me equip you the technical answers for these frequently asked Advanced SQL Interview Questions to confidently ace your next SQL interview.

To be honest, Preparing for an SQL interview can be challenging, especially if your role demands advanced SQL knowledge. Let me insight you the most commonly asked Advanced SQL Interview Questions, complete with detailed answers and resources for further reading through this month's Newsletter.

Advanced SQL Interview Questions:

1. What is your understanding of SQL indexes?
2. What is SQL server advanced index analysis?
3. How do you handle data overload in your relational database?
4. What is your understanding of auto-increment in SQL?
5. What command is employed to retrieve a unique entry from a table?
6. What are the primary types of variables in SQL?
7. What is your understanding of Recursive Stored Procedure?
8. What is the primary purpose of the NVL() function in SQL?
9. What is the Unique Constraint in SQL?
10. What is your understanding of SQL Sandbox?
11. What Is a JOIN in SQL?
12. What Is the Difference Between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN?
13. What Is a CROSS JOIN?
14. What’s the Difference Between WHERE and HAVING?
15. What’s the Difference Between UNION and UNION ALL?
16. What Is a Subquery in SQL?
17. What Are Window Functions in SQL?
18. What’s the Difference Between Window Functions and GROUP BY?
19. What’s the Difference Between RANK() and DENSE_RANK()?
20. What’s the Difference Between ROWS and RANGE?
21. Event Friends Recommendation [Facebook SQL Interview Questions]
22. Uniquely Staffed Consultants [Accenture SQL Interview Questions]
23. What are ACID properties in SQL?
24. Server Utilization Time [Amazon SQL Interview Question]

Advanced SQL Interview Questions and Answers:

1) What is your understanding of SQL indexes?

Indexes in SQL enhance data retrieval efficiency. The three main types of indexes are Unique, Clustered, and Non-Clustered. A table can have multiple non-clustered indexes but only one clustered index.

2) What is SQL server advanced index analysis?

Advanced index analysis in SQL Server involves a deep examination of the indexes used in a database to optimize performance. Indexes play a crucial role in database performance by speeding up data retrieval operations, but they can also have downsides if not utilized properly.

3) How do you handle data overload in your relational database?

In case of data overload, it's recommended to utilize a symbolic link. A symbolic link enables storage of .idb and .frm files, accessible whenever needed.

4) What is your understanding of auto-increment in SQL?

This frequently asked question in technical interviews explores a fundamental concept. Auto-increment is a feature that automatically generates a unique number each time a new record is inserted into a table.

5) What command is employed to retrieve a unique entry from a table?

The command utilized for this purpose is "DISTINCT."

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6) What are the primary types of variables in SQL?

SQL primarily categorizes variables into two types: Local and Global. Local variables are confined to a single function, while Global variables can span across multiple functions, remaining accessible throughout the program.

7) What is your understanding of Recursive Stored Procedure?

A Recursive Stored Procedure is a frequently used technique in programming where developers can reuse the same code snippet multiple times within a program. In this procedure, code snippets call themselves iteratively until a predefined termination condition is met.

8) What is the primary purpose of the NVL() function in SQL?

The NVL() function serves to substitute null values with predefined defaults. If the first parameter contains a null value, the function returns the subsequent parameter. It's important to note that this function is specific to Oracle databases.

9) What is the Unique Constraint in SQL?

The Unique Constraint in SQL guarantees the uniqueness of values within a specific record. It prohibits identical or similar values in a column from being present in separate records.

10) What is your understanding of SQL Sandbox?

SQL Sandbox refers to a controlled environment within SQL databases where unverified programs can undergo testing and execution.

There are primarily three types of SQL Sandboxes:

• Sandbox for External Access
• Safe Access Sandbox
• Unsafe Access Sandbox

11) What Is a JOIN in SQL?

JOIN is an SQL command facilitating the merging of two or more tables based on a common column, enabling simultaneous use of data from multiple tables. This merging is fundamental in relational databases where data is distributed across tables.

Let me illustrate this process using two tables, starting with the first one, named football_players.

The second is?national_team.

Here’s a query that joins two tables:

Code: ?

SELECT
??fp.id,
??first_name,
??last_name,
??national_team_id,
??country,
??games_played
FROM?football_players fp
JOIN?national_team nt
ON?fp.national_team_id = nt.id
ORDER?BY?fp.id;        

To select columns from both tables, we reference one table in the FROM clause and then use JOIN to bring in the second table.

The ON clause specifies the condition for joining:

the national_team_id in the football_players table must match the id column in the national_team table.

The output of the query is:

INNER JOIN is one of the different types of joins available in SQL. It exclusively retrieves data from the joined tables where the joining condition is met. Here are further explanations on how the SQL INNER JOIN operates.

12) What Is the Difference Between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN?

In SQL, there are various types of joins, with the most common being INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN. LEFT JOIN, RIGHT JOIN, and FULL JOIN are known as outer joins. INNER JOIN, often referred to simply as JOIN, is an inner join.

In this context, "inner" signifies that it retrieves only the rows from both tables that meet the joining condition, while outer joins return all the rows from one table along with matching rows from the other table(s). The exception is FULL JOIN, which returns all rows from both tables.

Let's revisit the result of the INNER JOIN from the previous example to better understand the distinctions between different types of joins.

LEFT JOIN retrieves all the data from the left table (the first table listed before or to the left of the JOIN keyword) along with only the matching rows from the right table (the second table listed after or to the right of the JOIN keyword).

If there are no matching values in the right table, those fields appear as NULLs. Here's the same query, but with LEFT JOIN replacing INNER JOIN:

Code: ?

SELECT
??fp.id,
??first_name,
??last_name,
??national_team_id,
??country,
??games_played
FROM?football_players fp
LEFT?JOIN?national_team nt
ON?fp.national_team_id = nt.id
ORDER?BY?fp.id;        

In this scenario, the left table is football_players, and the right table is national_team. Consequently, the output differs:

All football players from the left table are included. However, Kylian Mbappe and Erling Haaland lack a corresponding country in the right table, resulting in NULL values in the country column for those players. These rows were absent in the INNER JOIN outcome but were added by the LEFT JOIN.

Conversely, the RIGHT JOIN behaves oppositely: it returns all data from the right table and only the matching data from the left table. When there's no matching data in the left table, those fields appear as NULLs.

Here's the Code:

SELECT
??fp.id,
??first_name,
??last_name,
??national_team_id,
??country,
??games_played
FROM?football_players fp
RIGHT?JOIN?national_team nt
ON?fp.national_team_id = nt.id
ORDER?BY?fp.id;        

Everything remains consistent, except now we're employing RIGHT JOIN instead of LEFT JOIN.

Here's the resulting output:

We now possess all the national teams and their players. However, there's one country (Croatia) without any players in the left table. Consequently, the player columns for Croatia are populated with NULLs.

FULL JOIN retrieves all data from all joined tables. Once more, if there's no matching data in the respective table, the absent values will be displayed as NULL.

Let's adjust the join type in the query accordingly:

Code:

SELECT
??fp.id,
??first_name,
??last_name,
??national_team_id,
??country,
??games_played
FROM?football_players fp
FULL?JOIN?national_team nt
ON?fp.national_team_id = nt.id
ORDER?BY?fp.id;?        

The FULL JOIN retrieves all data from both tables. Any non-matching data is replaced by NULLs. All players are included in the result, even if they lack a corresponding country in the other table.

Similarly, all countries are present in the result, even if they lack players in the football_player table. The FULL JOIN outcome is essentially the combination of LEFT JOIN and RIGHT JOIN.

Check out this SQL JOINs Cheat Sheet?for a quick refresher.

13) What Is a CROSS JOIN?

A CROSS JOIN is an additional join type in SQL. It yields a Cartesian product, meaning it returns every row from the first table combined with every row from the second table.

It's not commonly utilized because retrieving all row combinations can be time-consuming, and there's a risk the query might not finish at all.

Let's consider the tables from the previous examples for this query. To construct the query, employ the CROSS JOIN keyword. Since this join type returns all possible row combinations from the tables involved, there's no need for an ON clause. Here's how you can do it:

Code:

SELECT
??fp.id,
??first_name,
??last_name,
??national_team_id,
??country,
??games_played
FROM?football_players fp
CROSS?JOIN?national_team nt;        

The output displays all players from the football_players table alongside all countries from the national_team table.

Are you seeking to Improve Your SQL JOIN Skills? Check Out this...

14) What’s the Difference Between WHERE and HAVING?

If you're familiar with the responses to the preceding two questions, you likely know the answer to this one.

The primary distinction lies in their roles: WHERE filters data before grouping, positioned before GROUP BY in the SELECT statement. Consequently, aggregate functions aren't permissible in WHERE due to its function.

Conversely, HAVING filters data after grouping, positioned after GROUP BY. Additionally, HAVING permits conditions that incorporate aggregate functions.

15) What’s the Difference Between UNION and UNION ALL?

Both are set operators, used for merging data from multiple SELECT statements. They share similarities in terms of requirements for the number of columns and their data types.

However, they differ in their handling of records. UNION returns only unique records, while UNION ALL includes all records, including duplicates.

Typically, UNION ALL is faster because it doesn’t sort the result to remove duplicates. As a rule of thumb, use UNION ALL by default. Reserve UNION for cases requiring unique results or when certain of avoiding duplicate data in the query.

16) What Is a Subquery in SQL?

A subquery refers to a query written within another SQL query. The encompassing query is termed the main query, while a subquery is sometimes referred to as a nested query.

Subqueries find application in various SQL statements such as SELECT, INSERT, UPDATE, and DELETE. They can also be incorporated into clauses like FROM or WHERE, with the latter being the most prevalent usage.

Here's an illustration using an example: Consider a table named products, which stores details about product names, quantities, and categories.

Here's the solution:

Code: ?

SELECT
??product_category,
??SUM(quantity)?AS?product_quantity
FROM?products
WHERE?quantity > (SELECT?AVG(quantity)
????????????FROM?products)
GROUP?BY?product_category;        

The query selects the product category and calculates the total quantity by using the SUM() aggregate function. A condition in the WHERE clause ensures that only individual products with a quantity above the average are included in the sum. To obtain this average, a subquery with the AVG() function is utilized.

The resulting output consists of two rows:

One category is absent because it fails to meet the filtering criteria – mobile phones.

Subqueries come in various types, including scalar, multiple-row, and correlated queries. You can delve deeper into their specifics in our article on subquery types.

17) What Are Window Functions in SQL?

SQL window functions derive their name from their operation on a data window, which is essentially a set of rows related to the current row.

The OVER() clause initiates window functions. Another crucial clause is PARTITION BY, which delineates data partitions within a window frame. If omitted, the partition encompasses the entire result table. When PARTITION BY is utilized, one or more columns can be specified to partition the data, akin to GROUP BY for window functions.

ORDER BY is another significant clause. It arranges data within the window, providing instructions on the sequence in which the function will execute within the window context.

18) What’s the Difference Between Window Functions and GROUP BY?

The only commonality between GROUP BY and window functions is that they can both be - and frequently are - used with aggregate functions, operating on a set of rows.

However, GROUP BY presents the output as groups, obscuring the individual rows within each group.

In contrast, window functions lack this limitation. One of their distinctive features is that they preserve individual rows while displaying aggregated data. Consequently, it's feasible to exhibit both aggregated and non-aggregated data concurrently.

19) What’s the Difference Between RANK() and DENSE_RANK()?

In practice, the difference between RANK() and DENSE_RANK() becomes evident.

RANK() allocates identical ranks to rows with the same values. Upon encountering the subsequent non-tied row, it skips the rank by the number of tied ranks.

On the other hand, DENSE_RANK() also assigns the same rank to tied values, but it does not skip ranks when moving to the following non-tied row. Essentially, DENSE_RANK() ranks data sequentially without gaps.

20) What’s the Difference Between ROWS and RANGE?

Both ROWS and RANGE are clauses utilized for defining a window frame, constraining the data range used in a window function within a partition.

The ROWS clause confines the rows by specifying a fixed number of rows preceding and following the current row, irrespective of their values.

In contrast, the RANGE clause delimits the data range logically by considering the values of preceding and following rows in relation to the current row. It disregards the actual number of rows involved.

21) What are ACID properties in SQL?

The ACID properties are:

Atomicity: Changes to the data must occur as a single operation, ensuring that either all changes are applied or none at all.

Consistency: The data must remain consistent before and after the transaction, adhering to all constraints, rules, and integrity constraints.

Isolation: Transactions can be executed concurrently without interfering with one another, with each transaction operating as if it were the only one being executed.

Durability: Once a transaction is successfully completed, its changes are permanently stored and remain unaffected even in the event of system failures or crashes.

22) Event Friends Recommendation [ Meta Facebook Facebook SQL Interview Questions]

Meta Facebook To recommend new friends to individuals interested in attending two or more of the same private events, we can query the friendship_status table.

This table denotes the status of friendships between user_a_id and user_b_id.

Input/Output Data:

friendship_status?Example Input:

event_rsvp?Table:

event_rsvp?Example Input:

Example Output:

Users 222 and 333, who are not currently friends, have both expressed interest in attending two or more of the same private events.

Code:

WITH private_events AS ( 
SELECT user_id, event_id 
FROM event_rsvp 
WHERE attendance_status IN ('going', 'maybe') 
	AND event_type = 'private' 
) 
SELECT friends.user_a_id, friends.user_b_id 
FROM private_events AS events_1 
INNER JOIN private_events AS events_2 
	ON events_1.user_id != events_2.user_id 
	AND events_1.event_id = events_2.event_id 
INNER JOIN friendship_status AS friends 
	ON events_1.user_id = friends.user_a_id 
	AND events_2.user_id = friends.user_b_id 
WHERE friends.status = 'not_friends' 
GROUP BY friends.user_a_id, friends.user_b_id 
HAVING COUNT(*) >= 2;        

The query should be sorted in ascending order by user_a_id and user_b_id.

23) Uniquely Staffed Consultants [Accenture SQL Interview Questions]

As a Data Analyst within 埃森哲 's People Operations team, your responsibility is to ascertain the number of consultants assigned to each client and identify the count of consultants exclusively allocated to a single client.

Please write a query that presents the client name along with the total count of staffed consultants and the number of consultants uniquely staffed to each client, arranged alphabetically by client name.

Code:

WITH exclusive_employees AS (

SELECT employee_id

FROM employees

JOIN consulting_engagements AS ce

ON employees.engagement_id = ce.engagement_id

GROUP BY employee_id

HAVING count(ce.client_name) = 1

)

SELECT

ce.client_name,

COUNT(employees.employee_id) AS total_staffed,

COUNT(ee.employee_id) AS exclusive_staffed

FROM employees

INNER JOIN consulting_engagements AS ce

ON employees.engagement_id = ce.engagement_id

LEFT JOIN exclusive_employees AS ee

ON employees.employee_id = ee.employee_id

GROUP by ce.client_name

ORDER BY ce.client_name;        

24) Server Utilization Time [Amazon SQL Interview Question]

Amazon Web Services (AWS) relies on fleets of servers to operate.

Senior management seeks data-driven strategies to enhance server utilization.

Compose a query to compute the cumulative duration that the server fleet was operational. The output should be expressed in full days.

Assumptions:

- Servers may initiate and terminate multiple times.

- The collective runtime of the server fleet can be derived by summing the uptime of each individual server.

Code:

WITH running_time 
AS ( 
	SELECT 
	server_id, 
	session_status, 
	status_time AS start_time, 
	LEAD(status_time) OVER ( 
		PARTITION BY server_id 
		ORDER BY status_time) AS stop_time 
	FROM server_utilization 
        ) 
       SELECT 
	DATE_PART('days', JUSTIFY_HOURS(SUM(stop_time - start_time))) AS total_uptime_days 
       FROM running_time 
       WHERE session_status = 'start' 
	AND stop_time IS NOT NULL;        

The Bottom Line:

In a nutshell I could say, The most effective method to prepare for an SQL interview is through consistent practice.

In addition to tackling previous SQL interview questions, it's essential to engage with over 200 SQL coding challenges sourced from companies such as FAANG tech giants and tech start-ups.

Check out this Monthly SQL Practice Sets is absolutely free throughout June 2024!

I Hope my this month's newsletter is insightful for you all about this topic, "Advanced SQL Interview Questions."

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1. It features 201 interview questions commonly asked at Facebook, Google, and various start-ups.
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People also ask - FAQs

Q1. What type of advanced SQL interview questions are asked in technical interviews?

In technical interviews, advanced SQL questions often revolve around core concepts such as keys, parameters, functions, stored procedures, commands, and crafting queries to efficiently manage, organize, and retrieve data from databases.

Q2. Is your knowledge of SQL tested in coding and design interviews at FAANG+ companies?

Knowledge of SQL is primarily assessed in systems design interviews at FAANG+ companies. These interviews are a crucial component of the technical evaluation process.

Q3. What do you understand about SQL Limit?

SQL Limit is a feature that restricts the number of entries or records returned from a query, ensuring consistency and facilitating seamless data retrieval from the database.

Q4. Which are the different types of user-defined functions in SQL?

The main types of user-defined functions in SQL are Inline Table-Valued Functions, Multi-Statement Table-Valued Functions, and Scalar Functions.

Q5. What are your main responsibilities as an SQL developer?

As an SQL developer, your primary responsibilities include managing and storing data in relational databases, collaborating with database administrators to ensure database security and performance, and optimizing database operations for efficiency and reliability.

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