Master SQL Interviews: Essential Questions for Senior Developers

Fundamental SQL Concepts

1. WHERE vs. HAVING: Differentiate WHERE and HAVING clauses in SQL, focusing on their application in filtering data before and after grouping.
2. JOIN Types: Explain the distinctions between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN, illustrating their functionalities with examples.
3. PRIMARY KEY & UNIQUE KEY: Define the roles of PRIMARY KEY and UNIQUE KEY constraints in ensuring data integrity and uniqueness.
4. FOREIGN KEY: Describe the purpose of FOREIGN KEY constraints in establishing relationships between tables and maintaining referential integrity.
5. SQL Indexes: Explain SQL indexes, their impact on query performance, and the trade-offs involved in their creation and maintenance.
6. SQL Views: Define SQL views, outlining their advantages (data abstraction, security, simplified queries) and limitations (potential performance overhead, dependency on base tables).
7. GROUP BY Clause: Explain the GROUP BY clause's function in grouping rows with similar values and provide a practical example.
8. TRUNCATE, DELETE, and DROP: Compare and contrast the TRUNCATE, DELETE, and DROP commands, highlighting their differences in data manipulation and reversibility.
9. Subqueries vs. Joins: Compare subqueries and joins, emphasizing their distinct approaches to combining data from multiple tables.
10. Aggregate Functions: Define aggregate functions (e.g., SUM, AVG, COUNT, MIN, MAX) and illustrate their usage with examples.

Intermediate SQL Proficiency

1. Database Normalization: Explain database normalization, its various normal forms (1NF, 2NF, 3NF, BCNF), and their importance in reducing data redundancy and improving data integrity.
2. Denormalization: Define denormalization, discussing its trade-offs and scenarios where it is beneficial (performance optimization).
3. CASE Statement: Illustrate the use of the CASE statement for conditional logic within SQL queries.
4. CHAR vs. VARCHAR: Compare and contrast CHAR and VARCHAR data types, highlighting their storage characteristics and appropriate use cases.
5. ACID Properties: Explain the ACID properties (Atomicity, Consistency, Isolation, Durability) in the context of SQL database transactions and their role in ensuring data reliability.
6. Clustered vs. Non-Clustered Indexes: Distinguish between clustered and non-clustered indexes, focusing on their impact on data storage and query performance.
7. Optimizing Slow Queries: Present strategies for optimizing slow SQL queries, including query rewriting, indexing, and analyzing execution plans.
8. Common Table Expressions (CTEs): Define CTEs, comparing and contrasting them with subqueries in terms of readability and reusability.
9. Handling Duplicate Rows: Provide methods for handling duplicate rows in SQL, including identifying, deleting, and retaining only unique records.
10. UNION and UNION ALL: Explain the UNION and UNION ALL set operators, focusing on their differences in handling duplicate rows.

Advanced SQL Expertise

1. Window Functions: Explain window functions (e.g., ROW_NUMBER(), RANK(), DENSE_RANK()), illustrating their use in performing calculations across a set of table rows related to the current row.
2. Materialized Views: Define materialized views, comparing and contrasting them with regular views in terms of storage, update mechanisms, and performance implications.
3. SQL Partitioning: Explain database partitioning, its different types (range, list, hash), and its advantages in managing and querying large datasets.
4. Pagination in SQL: Describe techniques for implementing pagination in SQL queries to retrieve data in manageable chunks.
5. OLTP vs. OLAP: Differentiate OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) databases, highlighting their distinct architectures and use cases.
6. Sharded Databases: Explain sharding, its purpose in scaling databases horizontally, and its associated challenges.
7. Deadlock Detection and Resolution: Describe methods for detecting and resolving deadlocks in SQL databases.
8. Query Execution Plans: Explain query execution plans, their role in performance analysis, and techniques for optimizing them.
9. Stored Procedures vs. Functions: Compare and contrast stored procedures and functions, emphasizing their differences in functionality and usage.
10. SQL Triggers: Define SQL triggers, illustrating their use cases in automating database actions based on specific events.

Practical Application Scenarios

1. E-commerce Database Design: Design a database schema for a simple e-commerce platform, considering entities, relationships, and data integrity.
2. Zero-Downtime Database Migration: Outline a strategy for migrating a database with zero downtime, minimizing disruption to applications and users.
3. Handling Schema Changes: Describe a process for managing schema changes in a production environment, ensuring data consistency and minimizing disruption.
4. Large-Scale Database Backup and Restoration: Explain a strategy for backing up and restoring large-scale databases efficiently and reliably.
5. Database Replication for High Availability: Describe how to implement database replication to enhance high availability and fault tolerance.
6. Indexing a Large Table: Explain the process of indexing a very large table in a live system, minimizing performance impact.
7. Securing Sensitive Data: Describe methods for securing sensitive data in a database (e.g., encryption, access control).
8. Optimizing Queries with Large Datasets: Outline strategies for optimizing queries involving large datasets (10M rows).
9. Troubleshooting Slow Queries: Describe your approach to troubleshooting a query that has suddenly become slow.
10. Implementing RBAC: Explain how to implement Role-Based Access Control (RBAC) in a SQL database to manage user permissions effectively.

Query-Based Exercises

1. Second Highest Salary: Write a SQL query to find the second highest salary in an employee table.
2. Running Total of Sales: Write a query to calculate the running total of sales over time.
3. Employees with Same Manager: Write a query to find all employees who share the same manager.
4. Deleting Duplicate Rows: Write a query to remove duplicate rows from a table, keeping one instance of each unique row.
5. Top 3 Customers by Revenue: Write a query to retrieve the top 3 customers based on their total revenue.
6. Retrieving the nth Row: Write a query to retrieve the nth row from a table.
7. First and Last Records: Write a query to retrieve the first and last records from a table.
8. Purchases in Every Month: Write a query to find customers who made purchases in every month of a given year.
9. Percentage Contribution of Products: Write a query to calculate the percentage contribution of each product to the total sales.
10. Products Not Sold Recently: Write a query to find products that haven't been sold in the last 30 days.

Performance Tuning and Optimization

1. Covering Indexes: Explain covering indexes and their role in enhancing query performance.
2. Query Hints: Explain the use of query hints in SQL and their potential benefits and drawbacks.
3. Database Partitioning for Performance: Explain how database partitioning improves query performance.
4. Temp Tables: Describe the purpose and usage of temporary tables in SQL.
5. Large Data Imports: Outline strategies for efficiently importing large datasets into a database without performance degradation.
6. Batch Processing: Explain batch processing in SQL and its advantages.
7. Optimizing Multiple Joins: Describe techniques for optimizing queries with multiple joins.
8. Correlated Subqueries and Optimization: Explain correlated subqueries and strategies for optimizing their performance.
9. Indexing Composite Keys: Discuss indexing strategies for composite keys.
10. Indexing Impact on DML Operations: Explain how indexing affects INSERT, UPDATE, and DELETE operations.

Data Integrity, Security, and Compliance

1. Optimistic vs. Pessimistic Locking: Compare and contrast optimistic and pessimistic locking mechanisms.
2. Implementing Auditing: Describe how to implement auditing in an SQL database to track data changes.
3. Preventing SQL Injection: Explain SQL injection vulnerabilities and techniques to prevent them.
4. Row-Level Security: Explain row-level security (RLS) in SQL and its implementation.
5. Enforcing Data Validation: Describe methods for enforcing data validation rules in SQL databases.
6. Soft Deletes vs. Hard Deletes: Compare and contrast soft deletes and hard deletes.
7. CHECK Constraints: Explain the use of CHECK constraints in enforcing data integrity.
8. Encrypting Sensitive Data: Describe methods for encrypting sensitive data within a database.
9. Access Control Mechanisms: Discuss various access control mechanisms in SQL databases.
10. Database Masking: Explain database masking techniques for protecting sensitive data.

Scalability and High Availability

1. Scaling Relational Databases: Discuss the challenges of scaling relational databases.
2. Read Replica Setup: Explain how to design and implement a read-replica setup for SQL databases.
3. Eventual Consistency: Explain eventual consistency in distributed databases.
4. Multi-Master Replication: Explain multi-master replication and its use cases.
5. Monitoring Database Performance: Describe methods for monitoring database performance in high-traffic environments.
6. Data Archiving: Explain data archiving strategies in SQL databases.
7. Hot Standby vs. Read Replica: Compare and contrast hot standby and read replica configurations.
8. Database Failover: Describe how to handle database failover in a high-availability setup.
9. Connection Pooling: Explain the role of connection pooling in database scalability.
10. Distributed Transactions: Describe how to implement distributed transactions across multiple databases.

Complex SQL Topics

1. Transaction Isolation Levels: Explain transaction isolation levels and their use cases.
2. Hash Join vs. Nested Loop Join: Compare and contrast hash joins and nested loop joins.
3. Logical vs. Physical Data Models: Differentiate logical and physical data models.
4. Null Values in Aggregate Functions: Explain how SQL handles NULL values in aggregate functions.
5. Trade-offs of Denormalization: Discuss the trade-offs associated with denormalizing data.
6. Identifying and Resolving Fragmented Indexes: Explain how to identify and resolve fragmented indexes.
7. Phantom Reads and Prevention: Explain phantom reads and methods to prevent them.
8. Serializable vs. Snapshot Isolation: Compare and contrast serializable and snapshot isolation.
9. Sequences in SQL: Explain the purpose and usage of sequences in SQL.
10. Change Data Capture (CDC): Explain change data capture (CDC) and its implementation in SQL databases.

Behavioral Questions and Best Practices

1. Challenging SQL Problem: Describe a challenging SQL problem you solved in a previous project, highlighting your approach and solution.
2. Documenting SQL Queries: Explain your approach to documenting complex SQL queries for other developers.
3. Query Maintainability: Describe steps you take to ensure the maintainability of SQL queries.
4. Optimizing a Poorly Performing Query: Describe a situation where you successfully optimized a poorly performing query.
5. SQL vs. NoSQL: Discuss how you decide between SQL and NoSQL databases for a project.
6. Schema Design: Describe your approach to designing a database schema for a new application.
7. Testing Database Backups: Explain how you ensure that database backups are regularly tested.
8. Complex Database Migration: Describe a time when you implemented a complex database migration.
9. Staying Updated: Discuss how you stay updated on the latest SQL and database technologies.
10. Tools for Monitoring and Debugging: List the tools you use for monitoring and debugging SQL queries.

This expanded version provides more detailed explanations and clearer distinctions between concepts, making it more suitable for senior developer interviews. Remember to tailor your answers to your specific experience and the context of the interview.

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