Memory Management and Large Dataset Optimization

[DrunkOnJava]

💾 Memory Optimization for Large Inventories

Current State

• In-memory filtering/sorting in ViewModels
• Loading all items at once
• No pagination or virtualization
• Memory pressure with large datasets

Performance Issues

• Loading 10,000+ items causes memory spike
• UI lag when scrolling large lists
• Slow filter/sort operations
• High memory footprint

Required Optimizations

1. Data Loading Strategy

   • Implement pagination/lazy loading
   • Virtual scrolling for large lists
   • Progressive data loading
   • Memory-efficient data structures

2. Caching Layer

   • LRU cache for images
   • Query result caching
   • Computed property caching
   • Memory pressure handling

3. Background Processing

   • Move filtering to background queue
   • Async sort operations
   • Incremental search indexing
   • Batch processing for updates

4. UI Optimizations

   • Cell reuse optimization
   • Image lazy loading
   • Prefetch strategies
   • Smooth scrolling techniques

Performance Targets

• Handle 50,000+ items smoothly
• < 100MB memory for 10,000 items
• < 16ms frame time while scrolling
• < 100ms filter/sort operations

Acceptance Criteria

• No memory warnings with large datasets
• Smooth 60fps scrolling
• Responsive UI during operations
• Performance regression tests

Parent Epic

Related to #109 (Performance Optimization)

[DrunkOnJava]

Closing: This issue has been resolved/superseded by the complete modular architecture restructure now in main branch (commit 33a0ead). The new architecture implements a comprehensive solution that addresses the core needs this issue was tracking.