Module file_processor 

File Processor Service Implementation

This module provides the concrete implementation of the file processor service interface for the adaptive pipeline system. It handles file reading, chunking, processing coordination, and result aggregation with high performance and reliability.

Overview

The file processor service implementation provides:

• File Chunking: Efficient division of files into processing chunks
• Parallel Processing: Concurrent processing of multiple chunks
• Progress Tracking: Real-time progress monitoring and reporting
• Error Handling: Comprehensive error handling and recovery
• Statistics Collection: Detailed processing statistics and metrics

Architecture

The implementation follows the infrastructure layer patterns:

• Service Implementation: StreamingFileProcessor implements domain interface
• Dependency Injection: File I/O service is injected as a dependency
• Configuration Management: Runtime configuration with thread-safe updates
• Statistics Tracking: Comprehensive processing statistics collection

Processing Workflow

File Reading and Chunking

The service processes files through these stages:

1. File Analysis: Analyze file size and determine optimal chunk size
2. Chunk Creation: Divide file into appropriately sized chunks
3. Parallel Processing: Process chunks concurrently using worker pools
4. Result Aggregation: Collect and aggregate processing results
5. Statistics Reporting: Generate comprehensive processing statistics

Chunk Processing

• Adaptive Sizing: Dynamic chunk size adjustment based on performance
• Memory Management: Efficient memory usage with chunk recycling
• Error Isolation: Isolate errors to individual chunks when possible
• Progress Reporting: Real-time progress updates during processing

Usage Examples

Basic File Processing

Parallel Chunk Processing

Configuration and Statistics

Performance Features

Parallel Processing

• Concurrent Chunks: Process multiple chunks simultaneously
• Worker Pools: Configurable worker thread pools for processing
• Load Balancing: Dynamic load balancing across available workers
• Resource Management: Efficient resource allocation and cleanup

Memory Optimization

• Chunk Recycling: Reuse chunk buffers to reduce allocations
• Streaming Processing: Process files without loading entirely
• Memory Pooling: Efficient memory pool management
• Garbage Collection: Proactive cleanup of unused resources

Adaptive Processing

• Dynamic Chunk Sizing: Adjust chunk size based on performance
• Performance Monitoring: Real-time performance monitoring
• Auto-tuning: Automatic optimization of processing parameters
• Resource Scaling: Scale resources based on system load

Error Handling

Chunk-Level Errors

• Error Isolation: Isolate errors to individual chunks
• Retry Logic: Automatic retry for transient failures
• Fallback Strategies: Fallback processing for failed chunks
• Error Reporting: Detailed error reporting with context

File-Level Errors

• Validation: Comprehensive file validation before processing
• Recovery: Automatic recovery from file system errors
• Partial Results: Return partial results when possible
• Cleanup: Automatic cleanup of resources on errors

Statistics and Monitoring

Processing Statistics

• Throughput: Processing throughput in MB/s
• Latency: Average and percentile processing latencies
• Chunk Metrics: Chunk processing statistics and timing
• Error Rates: Error rates and failure analysis

Performance Metrics

• Resource Utilization: CPU, memory, and I/O utilization
• Concurrency: Active worker and queue statistics
• Efficiency: Processing efficiency and optimization metrics
• Trends: Performance trends and historical analysis

Configuration Management

Runtime Configuration

• Dynamic Updates: Update configuration without restart
• Thread Safety: Thread-safe configuration updates
• Validation: Configuration validation and error handling
• Defaults: Sensible default configuration values

Performance Tuning

• Chunk Size: Optimal chunk size for different file types
• Concurrency: Optimal worker count for system resources
• Buffer Size: I/O buffer size optimization
• Memory Limits: Memory usage limits and management

Integration

The file processor service integrates with:

• File I/O Service: Efficient file reading and writing operations
• Chunk Processors: Pluggable chunk processing implementations
• Progress Reporting: Real-time progress monitoring and reporting
• Statistics Collection: Comprehensive statistics and metrics

Thread Safety

The implementation is fully thread-safe:

• Concurrent Processing: Safe concurrent chunk processing
• Shared State: Thread-safe access to shared configuration and statistics
• Lock-Free Operations: Lock-free operations where possible
• Atomic Updates: Atomic updates for critical shared data

Future Enhancements

Planned enhancements include:

• Streaming API: Streaming API for real-time processing
• Custom Schedulers: Pluggable chunk scheduling strategies
• Compression Integration: Built-in compression for chunk data
• Distributed Processing: Support for distributed chunk processing

Structs

StreamingFileProcessor

Implementation of FileProcessorService