Query processing in PostgreSQL

PostgreSQL is an open-source relational database management system (RDBMS) that offers robust features for data storage and management. One of the most critical components of PostgreSQL is its query processing system, which allows users to extract data from the database efficiently. In this article, we'll explore the query processing system in PostgreSQL and how it works.

What is query processing?

Query processing refers to the process of converting a user's SQL query into executable code that the database can use to retrieve data from its storage. The query processing system in PostgreSQL is responsible for executing these queries in the most efficient way possible.

Query processing is an essential part of database management systems (DBMS) like PostgreSQL. It involves a series of steps that are executed by the system to process user queries and provide accurate and efficient results. In this article, we will explore the five key steps of query processing in PostgreSQL.

Step 1: Parser

The first step of query processing is parsing, where the SQL statement is analyzed for syntax errors and broken down into its constituent parts. The parser generates a parse tree from the SQL statement, which is a hierarchical data structure that represents the SQL statement's structure. This parse tree is then passed on to the next stage of the processing pipeline.

Step 2: Analyzer/Analyser

The second step of query processing is semantic analysis, where the parser's output is further analyzed to ensure that the SQL statement is semantically correct. This stage of query processing is carried out by the analyzer/analyser. The analyzer checks for errors like missing or invalid table or column names and ensures that the query adheres to the database's constraints and data types. If the query passes the semantic analysis, a query tree is generated, which is a logical representation of the query.

Step 3: Rewriter

The third step of query processing is query rewriting. In this stage, the query tree generated by the analyzer is transformed to create an alternative query tree that can be executed more efficiently. The rewriter uses a set of rules stored in the rule system to optimize the query tree. This step is optional and may be skipped if no rules exist for the query.

Step 4: Planner

The fourth step of query processing is the planning stage. The query planner generates an execution plan that can most effectively retrieve the required data. The planner considers factors like the available indexes, the size of the tables, and the query's complexity to generate an optimal execution plan. The planner then generates a plan tree, which represents the physical operations required to execute the query.

Step 5: Executor

The final step of query processing is the execution stage. The executor reads the plan tree generated by the planner and executes the physical operations required to retrieve the data. The executor reads the data from the tables, applies any necessary sorting or grouping, and applies any user-defined functions or operators. The executor then returns the result of the query to the user.