Top 25 Facebook SQL Interview Questions & Answers

1. Introduction

Navigating the interview process can be daunting, especially when it comes to technical roles at major tech companies like Facebook. A critical component for data-related positions is the SQL interview, where candidates must demonstrate their ability to work with databases effectively. In this article, we’ll dive into common facebook sql interview questions to help you prepare for your upcoming interview with confidence.

2. Inside Data Roles at Meta Platforms, Inc.

Meta Platforms, Inc., formerly known as Facebook, is renowned for its innovative and data-driven culture. SQL proficiency is essential for many roles within the company, from data analysts to software engineers. Understanding SQL allows professionals to extract meaningful insights from vast amounts of data, inform decision-making, and drive strategic initiatives. A candidate’s ability to navigate complex SQL queries is not just preferred but pivotal in maintaining the robust databases that support Meta’s expansive network of services. This article aims to provide aspirants with the necessary preparatory questions that reflect the depth and practicality of SQL use at Meta Platforms, Inc.

3. Facebook SQL Interview Questions

Q1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL? (SQL Concepts)

INNER JOIN and LEFT JOIN are two types of joins that allow you to query data from multiple tables based on a related column between them.

• INNER JOIN: This join returns rows when there is a match in both tables. If a row in one table does not have a corresponding match in the other table, that row is not included in the result set.

  SELECT table1.column1, table2.column2
  FROM table1
  INNER JOIN table2 ON table1.common_field = table2.common_field;
  

• LEFT JOIN (or LEFT OUTER JOIN): This join returns all rows from the left table (table1), and the matched rows from the right table (table2). If there is no match, the result is NULL on the right side.

  SELECT table1.column1, table2.column2
  FROM table1
  LEFT JOIN table2 ON table1.common_field = table2.common_field;
  

An easy way to visualize the difference is to think of Venn diagrams: INNER JOIN gives you the intersection between two tables, while LEFT JOIN gives you all records from the left table and the intersection.

Q2. Why do you want to work at Facebook? (Motivation & Cultural Fit)

How to Answer

When answering a question about your motivation for working at a company like Facebook, you should be honest and specific about your reasons. Focus on the company’s culture, values, impact, and opportunities for growth and learning that align with your own professional goals.

My Answer

"I am passionate about connecting people and building communities, and I believe Facebook’s mission aligns perfectly with that passion. Facebook has been at the forefront of innovation in technology, and the opportunity to contribute to projects that impact billions of people is truly exciting. Moreover, I am attracted to the culture of collaboration and continuous learning at Facebook, where I can grow as a data professional and work alongside some of the brightest minds in the industry."

Q3. How would you write an SQL query to find the second highest salary from an ‘Employees’ table? (SQL Queries)

To find the second highest salary, you can use a subquery with DISTINCT to get all salaries except the highest and then retrieve the maximum of the remaining salaries. Here’s an example query:

SELECT MAX(E.salary) AS SecondHighestSalary
FROM Employees E
WHERE E.salary < (SELECT MAX(salary) FROM Employees);

Alternatively, you can use the DENSE_RANK or ROW_NUMBER window functions to rank salaries and then select the one with rank 2:

WITH SalaryRanks AS (
  SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) AS rank
  FROM Employees
)
SELECT salary AS SecondHighestSalary
FROM SalaryRanks
WHERE rank = 2;

Q4. Describe a situation where you would use a self-join and provide an example query. (SQL Concepts)

A self-join is used when you need to join a table to itself to compare rows within the same table. A common scenario is when you have hierarchical data or need to find duplicates.

For example, consider an Employees table with a manager-employee relationship, where each employee has a reference to their manager’s ID:

SELECT e1.name AS EmployeeName, e2.name AS ManagerName
FROM Employees e1
JOIN Employees e2 ON e1.manager_id = e2.id;

This query retrieves each employee’s name along with their manager’s name.

Q5. Explain the use of indexes in a database and how they improve query performance. (Database Performance)

Indexes are database objects that can help speed up the retrieval of rows from a table. They are similar to indexes in a textbook: they allow the database to find data without having to scan the whole table.

• Indexes are created on one or more columns of a database table.
• When you run a query, the database can use the index to quickly locate the rows that match the query conditions.
• An index is particularly useful for WHERE clauses, JOIN operations, and sorting with ORDER BY.

However, indexes also come with trade-offs:

• They can speed up read operations, but they may slow down write operations (INSERT, UPDATE, DELETE) because the index must be maintained.
• Indexes take up additional disk space.

Here’s a simplistic example of an index creation on the salary column of an Employees table:

CREATE INDEX idx_salary ON Employees(salary);

By creating this index, any query filtering or sorting by salary can potentially be much faster.

Q6. Write an SQL query to fetch duplicate records from a table. (SQL Queries)

To fetch duplicate records from a table, you can use the GROUP BY and HAVING clauses in SQL. These clauses allow you to group rows that have the same values in specified columns and filter groups by certain conditions.

Here’s a generic SQL query that demonstrates how to find duplicate records based on a single column ColumnA of a table YourTable:

SELECT ColumnA, COUNT(*)
FROM YourTable
GROUP BY ColumnA
HAVING COUNT(*) > 1;

If you need to check for duplicates based on multiple columns, you can include them in the GROUP BY clause as follows:

SELECT ColumnA, ColumnB, COUNT(*)
FROM YourTable
GROUP BY ColumnA, ColumnB
HAVING COUNT(*) > 1;

Q7. How would you normalize a database and what are the normal forms? (Database Design)

Normalization is the process of structuring a relational database in a way that reduces data redundancy and improves data integrity.

How to Normalize a Database:

• Step 1: Start with Unnormalized Data: Begin with an unnormalized table that may contain duplicate data and multivalued attributes.
• Step 2: Apply First Normal Form (1NF): Ensure that the table has a primary key and that each field contains only atomic (indivisible) values.
• Step 3: Apply Second Normal Form (2NF): Make sure that all non-key attributes are fully functionally dependent on the primary key.
• Step 4: Apply Third Normal Form (3NF): Remove transitive dependencies, where non-key attributes depend on other non-key attributes.
• Step 5: Apply Boyce-Codd Normal Form (BCNF): Address any anomalies not handled in 3NF.
• Further Normalization: Higher normal forms like 4NF and 5NF deal with multi-valued and join dependencies.

Normal Forms:

Normal Form	Description
1NF	Ensures that all columns have atomic values and each row is unique.
2NF	Ensures that each attribute is fully dependent on the primary key.
3NF	Ensures that no non-key attribute depends on another non-key attribute.
BCNF	A stricter version of 3NF that handles certain types of 3NF anomalies.
4NF	Ensures no multi-valued dependencies other than a candidate key.
5NF	Ensures no join dependencies and that the table cannot be decomposed further without loss of data.

Q8. What are the ACID properties in a database system? (Database Theory)

The ACID properties are a set of principles that ensure reliable processing of database transactions. ACID stands for Atomicity, Consistency, Isolation, and Durability.

• Atomicity: Ensures that each transaction is treated as a single unit, which either succeeds completely or fails completely.
• Consistency: Ensures that a transaction can only bring the database from one valid state to another, maintaining database invariants.
• Isolation: Ensures that concurrently executing transactions do not affect each other’s execution.
• Durability: Ensures that once a transaction has been committed, it will remain committed even in the case of a system failure.

Q9. Describe how you would implement pagination in SQL queries. (SQL Queries)

Pagination in SQL can be implemented using the LIMIT and OFFSET clauses. These clauses allow you to constrain the number of rows returned by a query and specify the starting point for the set of rows returned.

Here’s an example of how to use pagination in an SQL query:

SELECT * 
FROM YourTable
ORDER BY SomeColumn
LIMIT 10 OFFSET 20;

• LIMIT 10 returns only 10 records.
• OFFSET 20 skips the first 20 records and starts returning from the 21st record.

In some database systems such as SQL Server, you would use the TOP keyword and a common table expression (CTE) with ROW_NUMBER() for pagination.

Q10. What is a stored procedure and how is it different from a function in SQL? (SQL Concepts)

A stored procedure is a prepared SQL code that you can save and reuse. In contrast, a function in SQL is a type of stored procedure that returns a single value and can be used in SQL statements.

Differences between stored procedures and functions:

• Return Value: Stored procedures may return zero, one, or multiple values (through output parameters or result sets), while functions must return exactly one single value.
• Usage in SQL Statements: Functions can be called from within SQL statements, such as SELECT, whereas stored procedures cannot be called from within SQL statements; they are executed using the CALL statement.
• Transactions: Stored procedures can manage transactions (BEGIN, COMMIT, ROLLBACK), but functions cannot.
• Performance: Functions can be used in SQL statements and may be optimized as part of the query execution plan, while stored procedures are usually executed as a separate batch of code.
• Context: Functions are designed to be deterministic and are typically used for computations, while stored procedures are better suited for performing complex business logic and operations that affect the state of the database.

Q11. How do you optimize a slow-running SQL query? (Database Performance)

Optimizing a slow-running SQL query involves several steps. Here’s how you can approach the optimization:

• Indexing: Ensure that indexes are used effectively. This includes adding indexes on columns used in WHERE, JOIN, ORDER BY, and GROUP BY clauses.

• Query Analysis: Use the EXPLAIN plan to analyze the query execution path. Look for full table scans and try to convert them to index scans.

• Optimize Joins: Ensure that joins are done on indexed columns and try to reduce the number of rows to join by filtering data early in the query.

• Subqueries: Revisit subqueries to see if they can be replaced with JOINs, which are often more efficient, or if they can be eliminated altogether.

• Limit the Result Set: Only retrieve the data that you need. Avoid using SELECT * and instead, specify the columns you need.

• Avoid Functions on Indexed Columns in WHERE Clause: Using functions can prevent the use of indexes.

• Query Refactoring: Break complex queries into simpler ones and, if possible, pre-aggregate data.

• Hardware and Configuration: Ensure the database server has sufficient resources and is configured for optimal performance.

As an example, consider the following query optimization:

Before optimization:

SELECT * FROM Orders
WHERE MONTH(orderDate) = 1 AND YEAR(orderDate) = 2021;

After adding an index on orderDate and refactoring:

SELECT orderId, customerName, amount FROM Orders
WHERE orderDate BETWEEN '2021-01-01' AND '2021-01-31';

Q12. Explain the concept of a database transaction and its importance. (Database Theory)

A database transaction is a sequence of one or more SQL operations performed as a single logical unit of work that must be either entirely completed or aborted. Key properties of transactions (often referred to as ACID properties) include:

• Atomicity: The entire transaction is treated as a single unit. It either commits (succeeds completely) or rolls back (no effect).

• Consistency: Transactions ensure that the database state transitions from one valid state to another, maintaining database invariants.

• Isolation: The ability of a transaction to operate independently of other transactions. Intermediate results within a transaction are invisible to other concurrent transactions.

• Durability: Once a transaction commits, the changes are permanent, even in the case of system failures.

Transactions are important because they help maintain data integrity and consistency in applications, especially in the presence of concurrent users and potential system failures.

Q13. How would you write a SQL query to perform a batch update? (SQL Queries)

Batch updating refers to updating multiple rows in a database table at once. Here’s how you can perform a batch update with a SQL query:

UPDATE Employees SET salary = salary * 1.05
WHERE departmentId = 3;

This query will update the salary of all employees in department 3 by a 5% raise.

Q14. What is a database cursor and when would you use it? (SQL Concepts)

A database cursor is a database object used to retrieve data from a result set one row at a time. It is useful when you need to handle row-by-row processing for more complex transactions or processing logic. Cursors can be used when:

• You need to perform operations on a row before moving to the next one.
• You are dealing with large data sets and want to minimize memory usage by processing one record at a time.
• You need to perform conditional logic based on data within rows as you iterate through them.

However, cursors are generally slower than set-based operations and should be used judiciously.

Q15. Discuss the differences between DELETE, TRUNCATE, and DROP commands in SQL. (SQL Concepts)

Here is a comparison table highlighting the key differences:

Feature	DELETE	TRUNCATE	DROP
Scope	Removes specific rows based on a condition.	Removes all rows from a table.	Removes the entire table structure along with its data.
WHERE Clause	Can be used to specify conditions.	Cannot be used.	Not applicable.
Speed	Slower, as it logs individual row deletions.	Faster, as it logs page deallocations.	Fastest, as it removes table definition as well as data.
Rollback	Possible to rollback.	Possible to rollback (except in some databases like MySQL with AUTOCOMMIT enabled).	Not possible to rollback.
Space Reclamation	Does not reclaim space immediately.	Reclaims space immediately.	Reclaims space immediately.
Reset Identity	Does not reset identity columns.	Resets identity columns to seed value.	Not applicable.

• DELETE: Used to delete specific rows from a table and can utilize a WHERE clause to filter rows. It logs each deletion and is slower compared to TRUNCATE.

  DELETE FROM Customers WHERE lastPurchaseDate < '2020-01-01';
  

• TRUNCATE: Quickly removes all rows from a table, but does not log individual row deletions. It is faster and typically reclaims disk space immediately.

  TRUNCATE TABLE Customers;
  

• DROP: Completely removes a table from the database, including its structure and data, and cannot be rolled back.

  DROP TABLE Customers;
  

Q16. How do you handle NULL values in a SQL query to ensure accurate calculations? (SQL Queries)

Handling NULL values in SQL is crucial for ensuring accurate calculations as NULL represents missing or unknown data which can affect the outcome of your calculations.

• Use COALESCE to provide a default value when NULL is encountered. This function returns the first non-null value in a list.
• Use IS NULL or IS NOT NULL in the WHERE clause to filter out or include NULL values.
• Use conditional aggregation functions like COUNT(*) for counting rows regardless of NULL values, whereas COUNT(column) excludes NULL values.
• Be mindful when using arithmetic operations as any operation with NULL results in NULL. You might need to use COALESCE or IFNULL to substitute NULLs with a numerical value before performing the operation.

Here’s an example of using COALESCE to substitute NULL with 0 in a calculation:

SELECT 
    id, 
    COALESCE(column_with_nulls, 0) as column_with_default
FROM 
    table_name;

Q17. Describe a time you had to work with a large dataset and the approaches you used to manage it. (Data Handling & Performance)

How to Answer

When answering this question, you should focus on specific challenges that come with large datasets such as performance issues, memory constraints, and long-running queries. You should then discuss the strategies you employed to address these challenges, such as indexing, batching, or using more efficient SQL queries.

My Answer

In my previous role, I was tasked with generating analytical reports from a dataset containing several million records. To manage this effectively, I used the following approaches:

• Indexing: I created indexes on columns that were frequently used in WHERE clauses to speed up query performance.
• Batch Processing: Rather than processing the entire dataset at once, I broke the task into smaller batches to reduce the strain on system resources.
• Summary Tables: I created summary tables that aggregated key metrics, which reduced the need to query the entire dataset for repeated analyses.
• Query Optimization: I reviewed and optimized the SQL queries to ensure they were using the most efficient joins and subqueries.

Q18. Explain the difference between clustered and non-clustered indexes. (Database Performance)

Clustered and non-clustered indexes are both types of indexes used to speed up the retrieval of data in a SQL database but differ in how they store data.

• Clustered Index
  • Only one per table as it defines the physical order of data storage.
  • Faster for range queries as the data is physically stored in index order.

Attribute	Clustered Index
Physical Storage	Defines the physical order of data.
Number per Table	One.
Range Queries	Faster due to sequential data access.

• Non-Clustered Index
  • Can have many per table.
  • Contains a separate structure from the data rows, with pointers to the physical rows.

Attribute	Non-Clustered Index
Physical Storage	Separate from data rows.
Number per Table	Multiple.
Range Queries	Slower compared to clustered; uses pointers.

Q19. How would you write a SQL query to clone a table without copying the data in it? (SQL Queries)

To clone a table structure without copying the data, you can use the CREATE TABLE ... AS SELECT statement with a WHERE clause that is always false:

CREATE TABLE new_table AS 
SELECT * 
FROM original_table 
WHERE 1=0;

This statement creates a new table with the same structure as original_table but does not insert any rows because the WHERE clause 1=0 never holds true.

Q20. What are the advantages of using SQL subqueries? Provide an example. (SQL Concepts)

SQL subqueries can be a powerful tool. The advantages include:

• Encapsulation: They allow you to encapsulate complex queries, making your SQL scripts cleaner and more readable.
• Reusability: Subqueries can be used to reuse SQL code within a larger query.
• Logical Separation: They help in breaking down complex problems into smaller, more manageable parts.
• Versatility: Subqueries can be used in the SELECT, FROM, and WHERE clauses, among others.

Here’s an example of a subquery used in a WHERE clause:

SELECT 
    employee_id, 
    name 
FROM 
    employees 
WHERE 
    department_id = (SELECT department_id 
                     FROM departments 
                     WHERE name = 'Engineering');

This query retrieves the employee_id and name for employees who are in the ‘Engineering’ department. The subquery finds the department_id corresponding to the ‘Engineering’ department, and the outer query uses this department_id to filter the employees.

Q21. Can you explain what a ‘WITH’ clause is and provide a use case for it? (SQL Queries)

The WITH clause, also known as Common Table Expressions (CTE), is a temporary result set that you can reference within a SELECT, INSERT, UPDATE, or DELETE statement. A CTE can be thought of as a way to create a temporary result set that is defined within the execution scope of a single statement and can be referenced multiple times. It helps to simplify complex queries by breaking them down into simpler, more readable sections.

Here is an example of a use case for a WITH clause:

WITH RegionalSales AS (
    SELECT region, SUM(amount) AS total_sales
    FROM sales
    GROUP BY region
)
SELECT region, total_sales
FROM RegionalSales
WHERE total_sales > (SELECT AVG(total_sales) FROM RegionalSales);

In this example, the CTE RegionalSales is used to calculate the total sales per region. The main query then selects regions where the total sales are above the average total sales across all regions. Without the WITH clause, you would have to write a subquery twice or more, which can make the query more complex and less readable.

Q22. How do you ensure data integrity in a database? (Database Design)

How to Answer:
To answer this question, you should focus on explaining the methods and constraints you can use to ensure that the data in a database remains accurate, consistent, and reliable.

My Answer:
To ensure data integrity in a database, there are several mechanisms and constraints that can be applied during database design:

• Primary keys: Ensure that each row in a table is unique and identifiable.
• Foreign keys: Enforce referential integrity by ensuring that the value in one table matches values in another, usually primary keys.
• Unique constraints: Prevent duplicate entries in certain columns that must be unique.
• Check constraints: Enforce domain integrity by limiting the values that can be placed in a column.
• Not NULL constraints: Ensure that a column cannot have a NULL value, which ensures that all records have valid data in certain fields.

Additionally, maintaining data integrity includes:

• Implementing proper transaction control with ACID (Atomicity, Consistency, Isolation, Durability) properties.
• Using stored procedures and triggers to encapsulate business rules.
• Regularly backing up the database and testing restore procedures to prevent data loss.
• Implementing proper access controls to protect data from unauthorized access or updates.

Q23. What is a view in SQL and why would you use it? (SQL Concepts)

A view in SQL is a virtual table based on the result-set of an SQL statement. It contains rows and columns, just like a real table, and the fields in a view are fields from one or more real tables in the database. You can use views to:

• Simplify complex queries: By encapsulating complex joins and calculations.
• Enhance security: By restricting user access to a subset of data.
• Provide data independence: By allowing changes in underlying tables without affecting the view.
• Present aggregated or summarized data: Such as totals and averages, which can simplify reporting and analysis.

Here’s an example of creating a view:

CREATE VIEW vEmployeeDetails AS
SELECT employee_id, first_name, last_name, department
FROM employees
WHERE active = 1;

This view vEmployeeDetails shows details for active employees only, thus simplifying queries that need to filter out inactive employees.

Q24. Describe how you would handle a scenario where a database schema change is required due to a new feature implementation. (Database Design & Management)

How to Answer:
This question gauges your ability to manage database changes, which is a critical part of database design and management. Your answer should reflect a systematic approach to handling schema changes.

My Answer:
Handling a database schema change for a new feature implementation involves several steps:

1. Understand the Requirements: First, clearly understand the new feature and how it impacts the current schema.
2. Design the Changes: Plan the changes, design new tables, and decide on alterations to existing tables.
3. Review and Test: Review the changes with a team, and perform thorough testing in a development or staging environment.
4. Prepare Rollback Plan: Always have a plan to revert the changes in case something goes wrong.
5. Migration Script: Write SQL scripts for the changes to ensure repeatability and documentation.
6. Schedule Downtime (if necessary): Inform stakeholders and schedule any required downtime.
7. Backup: Take a full backup of the database before making changes.
8. Implement Changes: Apply the schema changes during a maintenance window.
9. Monitor: After implementation, monitor the database performance and functionality to ensure everything is working as expected.

Q25. What are the considerations for choosing between using a temporary table versus a table variable in SQL Server? (Database Performance)

When deciding between using a temporary table and a table variable in SQL Server, several considerations come into play:

• Scope: Table variables are visible only within the batch or stored procedure they are declared in, while temporary tables are visible to any session in the server.
• Transaction Logs: Transactions involving table variables are minimally logged, which can lead to performance gains, whereas temporary tables are fully logged.
• Statistics and Recompilation: SQL Server does not maintain statistics for table variables, which can lead to less optimal query plans compared to temporary tables for which statistics are kept and recompilations can occur.
• Size of Data Set: For small datasets, table variables may perform better; however, for larger datasets, temporary tables are often preferred due to better optimization by the query processor.
• Durability: Table variables are cleaned up automatically at the end of the block in which they’re defined, whereas temporary tables exist until they are explicitly dropped or the session ends.

Here is a markdown table summarizing some key differences:

Consideration	Temporary Table	Table Variable
Scope	Session-wide	Batch/Procedure scoped
Transaction Logs	Fully logged	Minimally logged
Statistics	Maintained	Not maintained
Recompilation	Can trigger recompilations	Does not trigger
Size of Data Set	Better for larger datasets	Better for smaller datasets
Durability	Removed at session end or drop	Removed after block execution

4. Tips for Preparation

To enhance your candidacy, focus on familiarizing yourself with Facebook’s tech stack and database architecture. Begin by refreshing your understanding of SQL fundamentals, as these will undoubtedly form the core of the technical interview. Delve into complex queries, optimization techniques, and understand Facebook’s products and how they may relate to data management.

Expand your preparation to include soft skills. Facebook values collaborative and solution-oriented individuals, so be prepared to discuss past experiences where you demonstrated these qualities. Additionally, consider how you’ve handled leadership tasks or resolved conflicts in team settings.

5. During & After the Interview

During the interview, communicate clearly and concisely. Interviewers appreciate candidates who can explain their thought processes and solve problems systematically. Be attentive to the questions asked and don’t rush your answers; it’s okay to pause and think.

Avoid common pitfalls like focusing too much on technical skills and neglecting to showcase your collaborative nature and cultural fit for Facebook. Approach the interview as a conversation, not just a test. Ask insightful questions about team dynamics, project management, and growth opportunities, as these can demonstrate your genuine interest in the role and company.

After the interview, follow up with a professional thank-you email that reiterates your interest in the position and reflects on a key part of the discussion that excited you about the opportunity. Generally, you can expect feedback within a couple of weeks, but this can vary, so be patient and considerate in your follow-up communications.