Table of Contents
introduction
Review of SQL Basics
Analysis of core SQL interview questions
Question: How to find out the second most paid employee on the table?
Question: How to find out the highest paid employees in each department?
Question: How to use SQL for window functions?
Example of usage
Basic usage: query and filter data
Advanced Usage: Complex Query and Optimization
Common Errors and Debugging Tips
Performance optimization and best practices
Summarize
Home Database SQL SQL Interview Questions and Answers: Ace Your Data Engineer/Analyst Interview

SQL Interview Questions and Answers: Ace Your Data Engineer/Analyst Interview

Apr 06, 2025 am 12:13 AM

Answers to SQL interview questions include: 1. Find the second highest-salary employees using subqueries and sorts; 2. Find the most-salary employees using grouping and subqueries in each department; 3. Use window functions for complex analysis. Mastering these SQL techniques and best practices will help you stand out in the interviews for data engineering and data analysis and be at ease in real work.

introduction

In the fields of data engineering and data analysis, SQL (Structured Query Language) is undoubtedly one of the core skills. Whether you are a data engineer or a data analyst preparing for an interview, proficiency in SQL will not only allow you to stand out in the interview, but also be at ease in actual work. This article aims to help you improve your SQL skills and pass the interview smoothly through a series of carefully selected SQL interview questions and answers.

By reading this article, you will be able to:

  • Understand common SQL interview questions and their solutions
  • Master some advanced SQL tips and best practices
  • Learn how to demonstrate your SQL abilities in interviews

Review of SQL Basics

SQL is the standard language used to manage and operate relational databases. Whether it is querying, inserting, updating or deleting data, SQL is competent. Let's quickly review several key concepts of SQL:

  • SELECT statement is used to query data from database tables
  • JOIN is used to combine two or more tables
  • WHERE clause is used to filter records
  • GROUP BY and HAVING are used to group and aggregate data

These basic knowledge is the cornerstone of understanding and solving SQL interview problems.

Analysis of core SQL interview questions

Question: How to find out the second most paid employee on the table?

This question examines your understanding of subqueries and sorting. Let's see how to solve this problem:

 SELECT MAX(Salary) AS SecondHighestSalary
FROM Employee
WHERE Salary < (SELECT MAX(Salary) FROM Employee);
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This query first finds the highest salary, and then finds the highest salary of the remaining salary, which is the second highest salary. This method is simple and straightforward, but it should be noted that if there is only one employee in the table or all employees are paid the same, this method will return NULL.

Question: How to find out the highest paid employees in each department?

This problem needs to be solved by combining grouping and subquery:

 SELECT e1.Name, e1.Department, e1.Salary
FROM Employee e1
WHERE e1.Salary = (
    SELECT MAX(e2.Salary)
    FROM Employee e2
    WHERE e2.Department = e1.Department
);
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This query finds out the maximum salary for each department through a subquery, and then matches the main query to find out the employees who meet the criteria. Although this approach works, it may affect performance in the case of large amounts of data.

Question: How to use SQL for window functions?

Window functions are an advanced feature of SQL that allows you to perform complex analysis of data without changing the result set structure. For example, find out how each employee ranks within their department:

 SELECT Name, Department, Salary,
       RANK() OVER (PARTITION BY Department ORDER BY Salary DESC) AS SalaryRank
FROM Employee;
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This query uses RANK() window function, grouped by department and ranked in descending order of salary. Window functions are very useful when dealing with complex analysis tasks, but it should be noted that different databases may support window functions differently.

Example of usage

Basic usage: query and filter data

Let's look at a simple example to find all employees who have a salary of more than 5,000:

 SELECT Name, Salary
FROM Employee
WHERE Salary > 5000;
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This query shows how to use SELECT and WHERE clauses to filter data, which is very basic but is very common in actual work.

Advanced Usage: Complex Query and Optimization

Suppose we need to find out the top three high salaries in each department, this is a more complex query:

 SELECT e1.Name, e1.Department, e1.Salary
FROM Employee e1
WHERE 3 > (
    SELECT COUNT(DISTINCT e2.Salary)
    FROM Employee e2
    WHERE e2.Salary > e1.Salary AND e1.Department = e2.Department
);
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This query uses a subquery and COUNT function to find out the top three employees in each department. Although this approach works, it can cause performance problems when the data volume is high. One way to optimize this query is to use window functions:

 SELECT Name, Department, Salary
FROM (
    SELECT Name, Department, Salary,
           DENSE_RANK() OVER (PARTITION BY Department ORDER BY Salary DESC) AS SalaryRank
    FROM Employee
) ranked
WHERE SalaryRank <= 3;
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This problem can be solved more efficiently using the DENSE_RANK() window function, because it only requires scanning the table once.

Common Errors and Debugging Tips

Common errors in SQL queries include syntax errors, logic errors, and performance issues. Here are some common errors and debugging tips:

  • Syntax error : For example, forget to use the semicolon end statement, or use an incorrect keyword. The solution is to double-check the SQL statements to make sure the syntax is correct.
  • Logical error : For example, a query condition is written incorrectly, resulting in an incorrect result being returned. The solution is to gradually verify each part of the query to ensure the logic is correct.
  • Performance issues : For example, query execution time is too long. The solution is to use EXPLAIN command to analyze the query plan, find out the bottlenecks and optimize it.

Performance optimization and best practices

In practical applications, it is very important to optimize SQL queries. Here are some optimization tips and best practices:

  • Using Indexes : Indexes can significantly improve query performance, especially on large tables. Make sure to create an index on frequently queried columns.
  • **Avoid SELECT ***: Select only the columns you need, which can reduce data transfer and processing time.
  • Using JOIN instead of subquery : In some cases, using JOIN can be more efficient than subquery.
  • Pagination query : When processing large amounts of data, using LIMIT and OFFSET can improve query performance.

For example, suppose we have a table with millions of records, how to optimize query performance:

 -- Use index CREATE INDEX idx_employee_salary ON Employee(Salary);

-- Select only the required columns SELECT Name, Salary
FROM Employee
WHERE Salary > 5000;

-- Use JOIN instead of subquery SELECT e1.Name, e1.Department, e1.Salary
FROM Employee e1
JOIN (
    SELECT Department, MAX(Salary) AS MaxSalary
    FROM Employee
    GROUP BY Department
) e2 ON e1.Department = e2.Department AND e1.Salary = e2.MaxSalary;

-- Pagination query SELECT Name, Salary
FROM Employee
WHERE Salary > 5000
ORDER BY Salary DESC
LIMIT 10 OFFSET 0;
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These optimization techniques can significantly improve query performance, but need to be adjusted according to the specific situation.

Summarize

Through this article, you should have mastered some common SQL interview questions and their solutions. Remember, SQL is not only an important skill in interviews, but also a core tool in data engineering and data analysis. Continue to practice and learn, constantly improve your SQL skills, and you will perform better in interviews and in actual work.

The above is the detailed content of SQL Interview Questions and Answers: Ace Your Data Engineer/Analyst Interview. For more information, please follow other related articles on the PHP Chinese website!

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