Name: PostgreSQL Uncovered: Internals, Trace Analysis, and Performance
Price: 9 USD
Availability: InStock

PostgreSQL Uncovered: Internals, Trace Analysis, and Performance

The course is designed for developers, database administrators, and anyone who wants to understand what actually happens "under the hood" of PostgreSQL.

You will start with familiar SQL queries and dive step by step into the internal workings of the DBMS: you will understand how the query planner works, how transactions and isolation are structured, how MVCC is organized, how B+Tree indexes, shared buffers, WAL (Write-Ahead Logging), vacuum and autovacuum processes, checkpoints, replication, and many other key mechanisms work.

The course combines theory with practice: you will learn to read EXPLAIN ANALYZE (BUFFERS, VERBOSE, TIMING), analyze traces using gdb and perf, understand PostgreSQL logs, and identify performance bottlenecks even in the most complex scenarios.

After completing the course, PostgreSQL will no longer be a "black box" — you will know exactly why a query works the way it does and how to optimize it at the core DBMS level.

About the Author: Bin Wang

An expert in solving complex problems in software development, possessing deep knowledge of the TCP core, MySQL, and PostgreSQL, as well as being passionate about artificial intelligence, history, mathematics, and physics.

Books

Read Book PostgreSQL Uncovered: Internals, Trace Analysis, and Performance

#	Title
1	Lesson 1. Why PostgreSQL Is More Than Just Data Storage
2	Lesson 2. Inside PostgreSQL Unlocking Secrets with Trace Analysis
3	Lesson 3. How a SQL Query Is Executed in PostgreSQL
4	Lesson 4. PostgreSQL Architecture Inside the Database Engine
5	Lesson 5. PostgreSQL Indexes Deep Dive for Developers
6	Lesson 6. Why PostgreSQL Uses Heap Storage
7	Lesson 7. How PostgreSQL Finds Rows in a B+ Tree_A Step-by-Step Example
8	Lesson 8. B+ Tree Depth in PostgreSQL and Its Performance Impact
9	Lesson 9. Index-Only Scans in PostgreSQL When Tables Are Skipped
10	Lesson 10. Shared Buffers Explained What PostgreSQL Caches Internally
11	Lesson 11. Understanding WAL in PostgreSQL The Write-Ahead Log
12	Lesson 12. Inside PostgreSQL Writes From Shared Buffers to Disk
13	Lesson 13. Why Doesn’t PostgreSQL Use Undo Logs for MVCC
14	Lesson 14. MVCC Internals_How PostgreSQL Keeps Old Versions Alive
15	Lesson 15. Autovacuum in PostgreSQL How It Works and When It Fails
16	Lesson 16. PostgreSQL VACUUM Understanding Performance, Benefits, and Costs
17	Lesson 17. System Catalogs The Metadata Control Center of a Database
18	Lesson 18. Inside PostgreSQL How Transactions Really Work
19	Lesson 19. PostgreSQL’s Hidden Strength Transactional DDL
20	Lesson 20. How PostgreSQL Ensures Atomicity Using MVCC, CLOG, and WAL
21	Lesson 21. Data Consistency in PostgreSQL_Constraints and Guarantees
22	Lesson 22. Isolation Levels in PostgreSQL_A Practical Introduction
23	Lesson 23. Same Isolation Level, Different Behavior PostgreSQL vs MySQL
24	Lesson 24. Durability in PostgreSQL_How Crashes Don’t Lose Data
25	Lesson 25. Why ROLLBACK Is So Fast in PostgreSQL
26	Lesson 26. Checkpoints in PostgreSQL_What They Are and Why They Matter
27	Lesson 27. Transaction ID Wraparound Why It Happens and How to Handle It
28	Lesson 28. Locks in PostgreSQL_An Easy Guide to Types and Use Cases
29	Lesson 29. Do Read-Only Queries Really Need VACUUM in PostgreSQL
30	Lesson 30. Inside PostgreSQL’s Planner_From Query to Logical Plan
31	Lesson 31. Inside PostgreSQL’s Cost Model How the Planner Thinks
32	Lesson 32. How JOINs Work Internally in PostgreSQL
33	Lesson 33. Join Tree Structures in Query Optimization
34	Lesson 34. Join Enumeration Strategies Dynamic Programming vs Genetic Search
35	Lesson 35. How PostgreSQL Reduces the Join Search Space
36	Lesson 36. Understanding Join Graph Topology and Its Impact on Query Optimization
37	Lesson 37. Why PostgreSQL Handles This JOIN 10× Faster Than MySQL
38	Lesson 38. How PostgreSQL Aggregates Work Internally
39	Lesson 39. PostgreSQL Parallel Query Execution The Key to Faster Analytics
40	Lesson 40. WITH Queries Demystified How PostgreSQL Plans CTEs
41	Lesson 41. How Databases Execute Window Functions A Deep Dive
42	Lesson 42. Why PostgreSQL Query Optimization Is So Challenging
43	Lesson 43. Planner Challenges in Distributed PostgreSQL
44	Lesson 44. What PostgreSQL Extensions Are and How They Work
45	Lesson 45. Representative PostgreSQL Extensions and Their Capabilities
46	Lesson 46. Understanding Hstore’s Extension Mechanism in PostgreSQL
47	Lesson 47. How pg_trgm Speeds Up Fuzzy Text Search
48	Lesson 48. Inside PostgreSQL Extensions_How FDW Works Under the Hood
49	Lesson 49. Inside PostgreSQL Extensions_How Citus Works Under the Hood
50	Lesson 50. How Citus Teaches the Planner to Think Globally
51	Lesson 51. How Citus Handles Joins Internally
52	Lesson 52. Citus Transactions Uncovered How It Really Works
53	Lesson 53. How Extensions Shape PostgreSQL Planning and Execution
54	Lesson 54. PostgreSQL Extensions_How They Affect Performance and Stability
55	Lesson 55. Why Hotspot Updates Hurt PostgreSQL Performance
56	Lesson 56. Why Long Transactions May Kill Your PostgreSQL Performance
57	Lesson 57. Why Performance Degrades Quickly in Long-Running TPC-C Tests
58	Lesson 58. Trace Analysis_Understanding Its Power and Limitations
59	Lesson 59. Migrating from MySQL to PostgreSQL Key Differences You Need to Know
60	Lesson 60. Becoming a PostgreSQL Expert_Roadmap to Rapid Growth