🐬 Advanced SQL (MySQL) Mastery Roadmap
This roadmap is designed for developers who already understand basic SQL (CRUD operations, simple joins, basic constraints) and want to master MySQL for production systems, performance optimization, and large-scale applications.
It covers intermediate to advanced SQL concepts, MySQL-specific features, best practices, and real-world projects.
🎯 Goal: Go beyond SELECT/INSERT and understand relational design, constraints, and deeper query capabilities.
Topics
- Advanced Joins
- LEFT/RIGHT joins
- CROSS joins, SELF joins
- Subqueries
- Correlated vs non-correlated
- Inline views (derived tables)
- Data Integrity
- Constraints (CHECK, UNIQUE, FOREIGN KEY)
- Cascading deletes & updates
- Set Operations
- Window Functions
ROW_NUMBER, RANK, DENSE_RANK, NTILE- Running totals, moving averages
Recommended Resources
- Books
- SQL for Smarties – Joe Celko
- Learning SQL – Alan Beaulieu
- Practice Projects
- Build a student grading system with advanced queries
- Create leaderboards with RANK/DENSE_RANK
- Analyze sales data with moving averages
⚡ Phase 2: MySQL-Specific Mastery
🎯 Goal: Learn MySQL’s unique features, engine behavior, and tuning.
Topics
- MySQL Architecture
- Storage engines (InnoDB vs MyISAM vs MEMORY)
- Query execution process
- Buffer pool, redo/undo logs
- Indexing
- B-Tree vs Hash indexes
- Covering indexes
- Composite indexes & index cardinality
- Indexing strategies for performance
- Transactions & Isolation
- ACID in MySQL
- Isolation levels (READ UNCOMMITTED → SERIALIZABLE)
- Deadlocks and handling
- Views & CTEs
- Recursive CTEs
- When to use views vs materialized tables
Recommended Resources
- Books
- High Performance MySQL – Baron Schwartz, Peter Zaitsev, Vadim Tkachenko
- Tutorials
- Practice Projects
- Design a banking system with transactions & rollback
- Optimize queries with indexes and EXPLAIN
- Experiment with different isolation levels in a simulated ticket-booking system
🎯 Goal: Learn to optimize queries and handle large-scale datasets.
Topics
- Query Optimization
EXPLAIN and EXPLAIN ANALYZE- Query execution plans
- Common performance pitfalls (SELECT *, implicit conversions)
- Partitioning & Sharding
- Horizontal vs vertical partitioning
- Range, list, hash partitioning
- Advanced Indexing
- Full-text search indexes
- Spatial indexes (GIS)
- Caching & Scaling
- Query caching strategies
- Read replicas & master-slave replication
Recommended Resources
- Book: SQL Performance Explained – Markus Winand
- Practice Projects
- Optimize a reporting dashboard with millions of rows
- Build a log analysis system with partitioned tables
- Implement a replication setup (master-slave) in MySQL
🏆 Phase 4: Advanced Topics & Real-World Applications
🎯 Goal: Apply MySQL knowledge to enterprise-level systems and advanced features.
Topics
- Stored Procedures & Functions
- Pros & cons in modern apps
- Error handling inside procedures
- Triggers & Events
- Auditing tables with triggers
- Scheduled tasks with MySQL events
- Security
- User management & roles
- Encryption functions & SSL
- MySQL in Distributed Systems
- Replication (statement vs row-based)
- Group replication & clustering
- Backup & recovery strategies
- NoSQL in MySQL
- JSON data type
- Generated columns & indexes on JSON
Recommended Resources
- Books
- MySQL Cookbook – Paul DuBois
- Practice Projects
- Build an audit log system with triggers
- Create a reporting warehouse with materialized views
- Develop a real-time analytics system using replication
- Implement a hybrid SQL+JSON data store
💡 General Tips
- Use
EXPLAIN on all non-trivial queries.
- Regularly analyze
slow_query_log.
- Benchmark queries with realistic data.
- Normalize for integrity, denormalize for performance.
- Document schema design decisions.
Happy Querying! 🎉
“Fast queries come from good design, not just indexes.”