What Actually Happens When You Run:
SELECT * FROM table_name;
While it might look simple, this SQL query kicks off a powerful chain of events deep inside the PostgreSQL engine. Let’s dive into the journey of your query from command to result.
🔌 1. Database Server Interaction
As soon as you hit Enter, the query is sent to the PostgreSQL server.
PostgreSQL handles multiple databases and interacts with various objects:
Tables 🧱
Views 🔍
Indexes 📚
Functions 🔧
🧠 2. PostgreSQL Server Process
Once received, PostgreSQL does this:
Spawns a backend process just for your query 🧵
Manages this process individually for efficiency and concurrency
Think of each request as getting its own lane on a data highway
⚙️ 3. Query Processing Pipeline
Your query now goes through several stages of transformation:
✅ Parser
Tokenizes the SQL query
Creates a parse tree 🌲
Validates syntax & semantics
🧠 Analyzer
Interprets what the query is trying to do
Builds a query tree 🧩
🔄 Rewriter
Applies PostgreSQL rules to rewrite the query (if needed)
May return multiple new queries
📊 Planner
Analyzes all possible strategies for running the query
Chooses the cheapest & most efficient plan
🏃 Executor
Carries out the plan
Retrieves the actual rows
Returns results to you in milliseconds ⚡
🛠️ 4. Background Processes (Always Working!)
Behind the scenes, these processes support every query:
Checkpointer — Writes dirty pages to disk 💾
WAL Writer — Logs data changes to prevent loss 🧱
AutoVacuum — Cleans up dead rows 🧼
Archiver — Handles backup processes 📦
Background Writer — Smoothens disk writes 📜
Stats Collector — Gathers performance data 📊
🧠 5. Memory Management
PostgreSQL splits memory into:
Shared Memory — Used across all backend processes
Local Memory — Used for individual queries
Efficient memory handling ensures high-speed data access and minimal disk reads.
🎯 Final Thoughts
Every time you run:
SELECT * FROM table_name;
you’re actually triggering a symphony of parsing, planning, optimizing, and executing, backed by an army of helper processes.
