Module compression 

Compression service adapter

Compression Service Implementation

This module is part of the Infrastructure layer, providing concrete implementations of domain interfaces (ports).

This module provides the concrete implementation of the compression service interface for the adaptive pipeline system. It implements various compression algorithms with optimized performance characteristics and comprehensive error handling.

Overview

The compression service implementation provides:

• Multi-Algorithm Support: Brotli, Gzip, Zstd, and Lz4 compression
• Parallel Processing: Multi-threaded compression for improved performance
• Adaptive Configuration: Algorithm selection based on data characteristics
• Streaming Support: Chunk-by-chunk processing for large files
• Performance Monitoring: Built-in benchmarking and statistics

Architecture

The implementation follows the infrastructure layer patterns:

• Service Implementation: MultiAlgoCompression implements domain interface
• Algorithm Handlers: Specialized handlers for each compression algorithm
• Performance Optimization: Parallel processing and memory management
• Error Handling: Comprehensive error mapping and recovery

Supported Algorithms

Brotli

• Use Case: Best compression ratio for web content and text
• Performance: Slower compression, excellent ratio
• Memory: Higher memory usage during compression

Gzip

• Use Case: General-purpose compression with wide compatibility
• Performance: Good balance of speed and compression ratio
• Memory: Moderate memory usage

Zstd (Zstandard)

• Use Case: Modern algorithm with excellent speed/ratio balance
• Performance: Fast compression with good ratios
• Memory: Efficient memory usage

Lz4

• Use Case: Extremely fast compression for real-time applications
• Performance: Fastest compression, moderate ratio
• Memory: Low memory usage

Performance Optimizations

Parallel Processing

The implementation uses Rayon for parallel processing:

• Chunk Parallelization: Multiple chunks processed simultaneously
• Algorithm Parallelization: Some algorithms support internal parallelism
• Thread Pool Management: Efficient thread utilization

Memory Management

• Buffer Reuse: Efficient buffer management to reduce allocations
• Streaming Processing: Minimal memory footprint for large files
• Adaptive Sizing: Buffer sizes adapted to data characteristics

Error Handling

Comprehensive error handling for:

• Compression Failures: Algorithm-specific error conditions
• Memory Limitations: Out-of-memory scenarios
• Data Corruption: Invalid or corrupted input data
• Configuration Errors: Invalid parameters or settings

Integration

The service integrates with:

• Domain Layer: Implements CompressionService trait
• Pipeline Processing: Chunk-based processing workflow
• Metrics Collection: Performance monitoring and statistics
• Configuration Management: Dynamic configuration updates

Structs

MultiAlgoCompression

Concrete implementation of the compression service for the adaptive pipeline system