Page Cache

How page cache works

The page cache operates as an intermediary layer between a database's storage engine and the physical disk. When data is read from disk, the operating system stores a copy of the data pages in the page cache. Subsequent reads for the same data can be served directly from memory, avoiding expensive disk operations.

This caching mechanism works in conjunction with mmap (memory-mapped files) in many database implementations, allowing direct memory access to file contents through the operating system's virtual memory system.

Impact on database performance

The page cache significantly influences database performance in several ways:

1. Reduced I/O operations: By caching frequently accessed pages, it minimizes the need for physical disk reads
2. Improved query latency: Cached data can be accessed at memory speeds rather than disk speeds
3. Better resource utilization: The operating system can optimize memory usage across all processes

For time-series databases handling high-velocity data, an efficient page cache implementation is particularly important for managing the balance between write throughput and query performance.

Page cache management

Database administrators and developers need to consider several aspects of page cache management:

Cache size optimization

• Allocating appropriate memory for the page cache based on workload characteristics
• Balancing cache size with other memory requirements
• Monitoring cache hit rates and eviction patterns

Cache coherency

• Ensuring consistency between cached pages and disk storage
• Managing dirty pages (modified cached pages pending write to disk)
• Coordinating with write amplification concerns

Eviction policies

The page cache implements strategies to determine which pages to retain or evict when memory pressure increases:

• Least Recently Used (LRU)
• Adaptive Replacement Cache (ARC)
• Clock algorithm variations

Page cache in time-series workloads

Time-series databases often employ specialized page cache strategies to handle their unique access patterns:

1. Sequential access optimization: Pre-fetching and caching strategies optimized for time-ordered data
2. Write-heavy workloads: Balanced management of cache space between read and write operations
3. Temporal locality: Leveraging the time-based nature of data access patterns

For example, QuestDB uses careful page cache management to optimize both real-time ingestion and historical data queries, ensuring efficient memory utilization while maintaining high performance.

Best practices

To maximize page cache effectiveness:

1. Monitor cache metrics

   • Cache hit rates
   • Memory pressure
   • I/O patterns

2. Optimize queries

   • Design queries to leverage cached data effectively
   • Avoid scanning large datasets that exceed cache size
   • Consider temporal access patterns

3. System configuration

   • Allocate appropriate memory for the page cache
   • Configure appropriate I/O scheduler settings
   • Balance with other system resources

The page cache remains a critical component in modern database systems, particularly for time-series workloads where efficient data access patterns can significantly impact overall system performance.