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Pt. 1 Getting into the Weeds of Database Storage: Pages

May 10, 2024By Ellie Najewicz
Ellie Najewicz

It may seem obvious, but understanding how data is stored is paramount to ensuring optimal performance and scalability in your database. There are many mechanisms available to DBAs and developers to slice and divide data stores for optimal efficiency. Central to this endeavor are concepts like buffer pools, table spaces, pages, and partitions, each playing a crucial role in organizing and accessing data effectively. As part of a series, I will break down the many ways a database stores information and can be tuned for best performance. Proper management of page space can significantly impact the performance, scalability, and reliability of a database system. This blog explores the concept of page space, its importance, and best practices for optimizing its use. Let's explore into these technical nuances of pages to understand how they interact and contribute to the robustness of database storage configurations. 

Page Space: A Foundational Element

Database pages are the fundamental units of data storage in a database management system (DBMS). It represents the unit of data storage, typically organized in fixed-size blocks, commonly referred to as pages. Page space refers to the fixed-size blocks of storage that a database uses to store and manage data. These blocks, commonly called pages, are the smallest unit of data that a database engine reads or writes from the storage medium. Typically, pages are of sizes such as 4KB, 8KB, or 16KB, depending on the database system's configuration. Each page contains a portion of the database's data, which could include table rows, index entries, or other relevant information. Pages drive how data is read from a database, and the data is organized in a page when queried. The structure of a database page can be divided into several key sections:

1. Page Header: 

The page header contains metadata about the page itself. This metadata typically includes:
   - Page Type: Indicates whether the page is a data page, index page, or another type of page.
   - Page ID: A unique identifier for the page within the database.
   - Page LSN (Log Sequence Number): Used for recovery purposes, indicating the latest transaction log record that affected the page.
   - Free Space Information: Details about the amount of free space available.
   - Checksum: Used to verify the integrity of the page data.

2. Data Records: 

This section stores the actual data rows. The structure of the data records depends on the table schema and can include fixed-length fields, variable-length fields, and potentially NULL values. Each row is typically prefixed with a header containing metadata about the row, such as:
   - Row ID: A unique identifier for the row within the page.
   - Flags: Indicators for various row states (e.g., deleted, active).
   - Record Length: The length of the row data.

3. Row Directory (Slot Array): 

The row directory is an array that maps logical row IDs to their physical positions on the page. This allows for efficient access and management of rows. When a row is inserted, updated, or deleted, the row directory is updated to reflect the changes without having to move the actual data.

4. Free Space: 

Free space within the page is used for inserting new rows or expanding existing rows. Proper management of free space is crucial for maintaining efficient page utilization and avoiding excessive fragmentation.

Here’s a simplified example of a typical data page structure in a relational database:

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How Pages impact your database:

The relationship between page size, table spaces, and buffer pools is interdependent.

Page size is a critical factor that affects how data is stored in a table space, which is the logical storage area where database objects like tables and indexes reside. The page size determines how much data can be stored within each page. Smaller page sizes can lead to higher overhead due to the metadata that accompanies each page. This can result in less efficient storage because more pages are needed to store the same amount of data, increasing the overall space used by the metadata. Conversely, larger pages can store more data with relatively less metadata overhead, improving storage efficiency. However, if the data rows are significantly smaller than the page size, larger pages may lead to wasted space (known as internal fragmentation).

Buffer pools are memory areas used by the database management system (DBMS) to cache data pages, reducing the need for disk I/O operations and improving performance. The size of the data pages has a significant impact on how the buffer pool is configured and utilized. 

The buffer pool is divided into frames that hold individual pages. With larger page sizes, each frame in the buffer pool will consume more memory. This means that fewer pages can be cached if the buffer pool size remains constant, which could potentially reduce the cache hit ratio and negatively impact performance. Conversely, smaller pages allow more pages to be stored in the buffer pool, potentially increasing the cache hit ratio and improving performance for workloads with high locality. You can see how optimizing the size and configuration of buffer pools is crucial for mitigating performance bottlenecks and ensuring swift data access.

Best Practices for Pages

Appropriate Page Size Selection: Choose a page size that aligns with your workload and storage architecture. Smaller page sizes can reduce wasted space but may increase overhead due to more frequent I/O operations. Conversely, larger page sizes can improve read efficiency but may lead to increased space wastage if the data size is smaller than the page size.

Regular Maintenance: Perform regular database maintenance tasks such as defragmentation and reorganization to ensure that page space is used efficiently. These tasks help in minimizing fragmentation, where data is scattered across non-contiguous pages, leading to inefficient I/O operations.3. 

Monitoring and Tuning: Continuously monitor page space usage metrics, such as page reads, writes, and fill factors. Use this information to tune database configurations and optimize storage layouts. Tools and features provided by database management systems (DBMS) can assist in this process.

Row Compression: Utilize row compression techniques to reduce the amount of space required to store data within a page. Compression can lead to better page space utilization by packing more data into each page, thus reducing the total number of pages required.

Avoid Overfilling Pages: While it might be tempting to fill pages to their maximum capacity, leaving some space (using a fill factor) can improve performance by reducing the need for page splits during inserts and updates.

Database pages are carefully structured to balance the needs of efficient data storage, quick retrieval, and reliable transaction management. Understanding this structure can greatly aid in optimizing and maintaining database performance and integrity. From selecting the appropriate page size to regular maintenance and monitoring, effective page space management is key to building robust, high-performing database systems.