SQL command lifecycle

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The SQL Lifecycle: From Query to Result

When a SQL command hits a database like PostgreSQL, it transforms from a text string into a set of physical operations. This process is generally handled by the Query Processor.

1. Parsing (Syntax & Grammar)

The Parser checks the SQL string against the formal grammar of the SQL language.

• Tokens: It breaks the string into "tokens" (keywords, identifiers, literals).

• Parse Tree: It generates a tree structure representing the query logic. If you wrote SELECT FROM table (missing columns), the parser throws an error here.

2. Validation & Semantic Analysis

The database consults the System Catalog (the database’s internal dictionary).

• Existence: Do these tables and columns actually exist?

• Types: Are you trying to sum a TEXT column?

• Permissions: Does the current user have SELECT or DELETE rights?

3. Query Rewrite (The Transformation)

The logical plan is often expanded. For example, if you query a View, the rewriter replaces the view name with the actual query that defines that view. It also handles constant folding (e.g., changing 2+2 to 4 so the engine doesn't calculate it for every row).

Other rewrites:

• Subquery flattening

• Predicate pushdown

• Join elimination

4. Optimization (The "Brain")

The Query Optimizer is the most complex part. It generates multiple Physical Plans and assigns a "Cost" to each based on table statistics (from ANALYZE).

• Decisions: Should I use a Sequential Scan or an Index Scan? Should I use a Nested Loop or a Hash Join?

• The Winner: The plan with the lowest estimated cost is passed to the executor.

The optimizer uses:

• Cardinality estimates (row count predictions)

• Selectivity of predicates

• Available indexes

5. Execution & Data Access

The Executor follows the plan steps. It doesn't usually talk to the disk directly; it talks to the Buffer Manager.

• The Buffer Manager checks if the required data "pages" are already in RAM (Buffer Cache).

• If not, it requests them from the storage engine (Disk).

6. Result Return

The executor formats the rows into the communication protocol (e.g., the Postgres wire protocol) and streams them back to the client.

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Visualizing the Pipeline

Additional information:

• Plan Caching: In many systems, if you run the exact same query twice, the database skips Parsing and Optimization and re-uses the cached Execution Plan.

• Statistics: This is why ANALYZE is vital. If the statistics are old, the Optimizer (Step 4) will make a "bad guess" and choose a slow plan.

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