Understanding PostgreSQL Page Structure

“Unlocking PostgreSQL’s Storage Power: Exploring the Architecture and Implementation of Page Structure”

The page structure in PostgreSQL is a fundamental component of its storage system and is designed to efficiently store and retrieve data on disk. Let’s explore the architecture and implementation details of the page structure in PostgreSQL: 

  1. Page Size:
    • PostgreSQL uses a fixed-size page concept, typically set to 8 KB, which is configurable during database creation.
    • The page size is a crucial factor that affects storage efficiency, disk I/O, and performance.
  2. Page Header:
    • Each page starts with a page header that contains metadata and control information.
    • The page header includes important fields such as the page number, page level, flags, and pointers to other pages.
  3. Page Layout:
    • After the page header, the remaining space in the page is allocated for storing tuples (rows) and associated metadata.
    • The tuples are organized into heap pages for tables and index pages for indexes.
    • PostgreSQL uses a modified version of the heap-organized storage model known as the heap file format.
  4. Heap Pages:
    • Heap pages store table data and follow a specific layout optimized for efficient row storage.
    • Each heap page consists of a fixed-size array of ItemId structures, which represent the individual tuples.
    • The ItemId array is followed by the actual tuple data, organized as a heap.
  5. Index Pages:
    • Indexes in PostgreSQL use a B-tree data structure, which is organized into index pages.
    • Index pages store keys and pointers to the corresponding tuples in the table.
    • The B-tree structure allows efficient indexing and retrieval of data based on the index keys.
  6. Free Space Management:
    • PostgreSQL employs a specialized mechanism to manage free space within pages, known as the Heap Page Layout (HPL).
    • The HPL method uses a combination of a header and line pointers to efficiently track and manage free space within a page.
    • The HPL approach helps reduce fragmentation and allows for efficient insertion and updates.
  7. Visibility Map and Free Space Map:
    • PostgreSQL utilizes auxiliary structures called the Visibility Map (VM) and Free Space Map (FSM) to optimize access and reduce I/O.
    • The Visibility Map tracks the visibility status of individual heap pages, indicating whether they need to be considered during query execution.
    • The Free Space Map tracks the amount of free space available in each page, allowing the planner to make informed decisions during query planning.

The implementation of the page structure in PostgreSQL is highly optimized for efficient storage, retrieval, and manipulation of data. It ensures a balance between performance, storage utilization, and data integrity. Understanding the page structure is essential for optimizing performance and making informed decisions regarding storage configuration, indexing strategies, and query planning. 

It’s important to note that the internal details of the page structure and its implementation are subject to changes across different PostgreSQL versions. Therefore, it’s recommended to refer to the official PostgreSQL documentation and relevant technical resources for the most up-to-date information on the page structure implementation. 

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About Shiv Iyer 444 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.