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chrislu
7e755c70ce
This commit adds an LRU cache for disk chunks to optimize repeated reads of historical data. When multiple consumers read the same historical offsets, or a single consumer refetches the same data, the cache eliminates redundant disk I/O. Cache Design: - Chunk size: 1000 messages per chunk - Max chunks: 16 (configurable, ~16K messages cached) - Eviction policy: LRU (Least Recently Used) - Thread-safe with RWMutex - Chunk-aligned offsets for efficient lookups New Components: 1. DiskChunkCache struct - manages cached chunks 2. CachedDiskChunk struct - stores chunk data with metadata 3. getCachedDiskChunk() - checks cache before disk read 4. cacheDiskChunk() - stores chunks with LRU eviction 5. extractMessagesFromCache() - extracts subset from cached chunk How It Works: 1. Read request for offset N (e.g., 2500) 2. Calculate chunk start: (2500 / 1000) * 1000 = 2000 3. Check cache for chunk starting at 2000 4. If HIT: Extract messages 2500-2999 from cached chunk 5. If MISS: Read chunk 2000-2999 from disk, cache it, extract 2500-2999 6. If cache full: Evict LRU chunk before caching new one Benefits: - Eliminates redundant disk I/O for popular historical data - Reduces latency for repeated reads (cache hit ~1ms vs disk ~100ms) - Supports multiple consumers reading same historical offsets - Automatically evicts old chunks when cache is full - Zero impact on hot path (in-memory reads unchanged) Performance Impact: - Cache HIT: ~99% faster than disk read - Cache MISS: Same as disk read (with caching overhead ~1%) - Memory: ~16MB for 16 chunks (16K messages x 1KB avg) Example Scenario (CI tests): - Producer writes offsets 0-4 - Data flushes to disk - Consumer 1 reads 0-4 (cache MISS, reads from disk, caches chunk 0-999) - Consumer 2 reads 0-4 (cache HIT, served from memory) - Consumer 1 rebalances, re-reads 0-4 (cache HIT, no disk I/O) This optimization is especially valuable in CI environments where: - Small memory buffers cause frequent flushing - Multiple consumers read the same historical data - Disk I/O is relatively slow compared to memory access