Chapter 3: Query Processing Parser to Executor in PostgreSQL
Tags: apacheage, postgres, postgressql
Published: 2023-06-30 17:01:24

Several subsystems are used by PostgreSQL, a robust and feature-rich relational database management system (RDBMS), to effectively handle queries. We'll explore each stage of the query processing process in PostgreSQL in this blog.
 
###Parser:
The parser, which accepts a SQL statement as input and produces a parse tree, is at the heart of query processing. The parser does not perform any semantic tests; instead, it concentrates on examining the query's syntax. The structure of the query and its individual components are represented by the parse tree, which is rooted in the SelectStmt structure.
 
###Analyzer: 
Once the parse tree is generated, it is passed to the analyzer. The analyzer performs semantic analysis, ensuring that the query is valid and meaningful. It generates a query tree, with the Query structure as its root, capturing metadata about the query's type and various clauses. The target list, range table, join tree, and sort clause are some key components of the query tree.
 
###Rewriter: 
The rewriter intervenes to apply system catalog-stored rules to the query tree. These rules can be used to alter the query tree, enabling capabilities like PostgreSQL views. The rewriter examines the range table node when it comes across a view and replaces it with the relevant parse tree specified by the view's rule.
 
###Planner: 
The planner oversees creating an optimised plan tree for query execution using the modified query tree as a starting point. Utilising cost-based optimisation, the planner examines alternative execution techniques and chooses the most effective one. It builds a plan tree made up of plan nodes that contains the data required for query execution.
 
###Executor:
The planner then sends the plan tree it created to the executor so it may be carried out. From leaf nodes to root nodes, the executor processes the plan nodes. It makes use of memory spaces, generates temporary files as necessary, and reads and writes data using the buffer manager. Using concurrency control methods, the executor makes sure that isolation and consistency are maintained throughout tuple access.
 
####pg_hint_plan/Planner:
While PostgreSQL does not by default provide planner hints in SQL, a workaround is provided via the pg_hint_plan extension. With the use of this plugin, users may add suggestions to their queries to sway the planner's judgement. Users can use this addon to optimise queries by consulting the official documentation.


It's essential to comprehend PostgreSQL's query processing flow to maximise database performance. The subsystems collaborate flawlessly to translate a SQL statement into results that can be acted on, starting with the first parsing phase and ending with the final execution. The parser checks the syntax, the analyst does semantic analysis, the rewriter makes changes, the planner creates an optimised plan tree, and the executor carries out the plan. Developers and database managers may improve the effectiveness of their PostgreSQL databases by understanding these procedures and making educated decisions.

This blog is summary of chapter 3 part 1 of book [The Internals of PostgreSQL](https://www.interdb.jp/pg/pgsql03.html) written by Hironobu SUZUKI