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Optimize concurrent GetObject performance with Moka cache, comprehensive metrics, complete test suite, cache writeback, and comprehensive documentation #916
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…GetObject - Implement adaptive buffer sizing based on concurrent request load - Add per-request tracking with automatic cleanup using RAII guards - Implement hot object cache (LRU) for frequently accessed small files (<= 10MB) - Add disk I/O semaphore to prevent saturation under extreme load - Integrate concurrency module into GetObject implementation - Buffer sizes now adapt: low concurrency uses large buffers for throughput, high concurrency uses smaller buffers for fairness and memory efficiency - Add comprehensive metrics collection for monitoring performance Co-authored-by: houseme <[email protected]>
…ect optimization - Add detailed technical documentation explaining the solution - Document root cause analysis and solution architecture - Include performance expectations and testing recommendations - Add integration tests for concurrency tracking and buffer sizing - Add cache behavior tests - Include benchmark tests for concurrent request handling Co-authored-by: houseme <[email protected]>
- Fix race condition in cache size tracking by using consistent atomic operations within lock - Correct buffer sizing logic: 1-2 requests use 100%, 3-4 use 75%, 5-8 use 50%, >8 use 40% - Improve error message for semaphore acquire failure - Document limitation of streaming cache implementation (not yet implemented) - Add TODO for proper streaming cache with suggested approaches - Update tests to match corrected buffer sizing thresholds Co-authored-by: houseme <[email protected]>
…ct optimization - Executive summary of problem and solution - Detailed architecture documentation for each optimization - Integration points and code examples - Complete testing strategy and performance validation steps - Monitoring and observability guidelines with Prometheus queries - Deployment considerations and rollout strategy - Future enhancement roadmap - Success criteria and quantitative metrics Co-authored-by: houseme <[email protected]>
…ate-coroutine-performance-issue
Dependency Review✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.OpenSSF ScorecardScorecard details
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@copilot In-depth analysis of all the information described in the issue, as well as in-depth understanding of the project code, design a detailed and elegant and perfect solution, and further improve and improve the design of the getObject function concurrent acquisition method, please stand in the role of a senior developer of RUST and start processing. |
已完成所有优化改进!All optimizations completed! (commit a8a7cc7) 主要改进 Key Improvements:
性能提升 Performance Gains:
filemeta.rs分析: |
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@copilot Reload the code content in pr for in-depth analysis, complete repair and optimization of the errors in the action, where |
…dvanced features - Implement optimized read-first cache access using peek() to reduce write lock contention - Add batch cache operations: get_cached_batch() for efficient multi-object retrieval - Add cache utility methods: is_cached(), remove_cached(), get_hot_keys() - Implement warm_cache() for pre-populating cache on startup - Add get_advanced_buffer_size() with file size and sequential read optimization - Enhance test suite with 8 new comprehensive tests covering: - Batch operations and cache warming - Hot keys tracking and analysis - Cache removal and LRU behavior verification - Concurrent cache access performance - Advanced buffer sizing strategies - Improve documentation and code comments in English throughout Co-authored-by: houseme <[email protected]>
Completed all optimizations! (commit 010e515) Key Improvements:
Performance:
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- Complete technical documentation of all optimizations - Detailed performance analysis and metrics - Production deployment guide with examples - Comprehensive API reference and usage patterns - Migration guide and future enhancement roadmap - All documentation in professional English Co-authored-by: houseme <[email protected]>
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@copilot Use moka to completely replace lru, among which moka github: |
…ate-coroutine-performance-issue
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@copilot You are helping refactor the High-level goals1) Use the concurrency manager's disk read permit ( 2) Based on the disk permit wait time 3) Feed these observed metrics back into 4) Keep the existing metrics histogram:
Project context
You can (and should) use:
Current focusThe main changes are in:
// Acquire disk read permit to prevent I/O saturation under high concurrency
let permit_wait_start = std::time::Instant::now();
let _disk_permit = manager.acquire_disk_read_permit().await;
let permit_wait_duration = permit_wait_start.elapsed();
#[cfg(feature = "metrics")]
{
use metrics::histogram;
histogram!("rustfs.disk.permit.wait.duration.seconds").record(permit_wait_duration.as_secs_f64());
}Detailed refactoring requirementsYou only need to output a replacement code snippet for the above region, written in Rust, and compilable in the async context. The logic you add is the following: 1) After acquiring
2) Provide a simple classification logic for this profile, based on time thresholds in milliseconds. For example:
You may choose or slightly adjust the thresholds, but they must be defined as constants in code so they are easy to tune later. 3) Feed this
This method does not need to be implemented right now; it can be a TODO or stub in Important: At this time, you only need to invoke the feedback logic from within 4) Keep the original metrics reporting, and optionally add new metrics related to the I/O profile. For example, profile-specific counters:
These new metrics must use their own metric names (do not overload the existing one), and must be protected with 5) After refactoring, return a single Rust code block that can be used to replace lines 1795–1804 in ```rust
// new Rust code hereAdditional constraints and style notes
This English specification is intended to make it easier to iterate on and improve the Finally, please stand in the role of senior architect at RUST and start a complete, elegant and high-performance coding process. All information content will be described in English. |
Implements adaptive I/O strategy for GetObject operations based on disk permit wait times, as requested in issue #911. Key changes: 1. New types in concurrency.rs: - IoLoadLevel enum: Low (<10ms), Medium (10-50ms), High (50-200ms), Critical (>200ms) - IoStrategy struct: contains optimized I/O parameters based on load level - IoLoadMetrics: rolling window metrics for load tracking 2. New ConcurrencyManager methods: - calculate_io_strategy(): calculates adaptive strategy from permit wait duration - record_permit_wait(): records observation for load tracking - smoothed_load_level(): returns averaged load level for stability - io_load_stats(): returns (avg_wait, p95_wait, max_wait, count) for monitoring - adaptive_buffer_size(): convenience method for buffer sizing 3. Integration in ecfs.rs get_object: - Calculate IoStrategy after acquiring disk permit - Use strategy buffer_size instead of static sizing - Consider strategy.cache_writeback_enabled in cache decision - Record new metrics: io.load.level gauge, io.buffer.multiplier gauge, io.strategy.selected counter by load level 4. New tests (4 added, 31 total): - test_io_load_level_classification: validates load level thresholds - test_io_strategy_buffer_sizing: validates buffer multipliers - test_calculate_io_strategy: validates manager strategy calculation - test_io_load_stats: validates stats tracking All 31 tests pass. Clippy clean. Formatted. Co-authored-by: houseme <[email protected]>
Implemented adaptive I/O strategy based on disk permit wait time (commit c090b64). Key implementations:
All 31 tests pass, clippy clean. |
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@copilot In-depth and detailed analysis of the modifications and new code content of |
…otification 1. Added CONCURRENCY_ARCHITECTURE.md with complete design documentation: - Executive summary and problem statement - Architecture overview with request flow diagram - Detailed module analysis for concurrency.rs and ecfs.rs - Critical analysis of helper.complete() for cache hits - Adaptive I/O strategy design with algorithm - Cache architecture with CachedGetObject structure - Metrics and monitoring with Prometheus queries - Performance characteristics and future enhancements 2. Fixed critical issue: Cache hit path now calls helper.complete() - S3 bucket notifications (s3:GetObject events) now trigger for cache hits - Event-driven workflows (Lambda, SNS) work correctly for all object access - Maintains audit trail for both cache hits and misses All 31 tests pass. Co-authored-by: houseme <[email protected]>
Completed. Created Critical Finding: The cache hit path was NOT calling Answer to your question: Yes,
The architecture document covers:
All 31 tests pass. |
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@copilot When 'get_object' responds by obtaining cache information in 'ecfs.rs', you need to execute the following code before executing 'let _ = helper.complete(&result);'. let version_id = req.input.version_id.clone().unwrap_or_default();
helper = helper.object(event_info).version_id(version_id);Finally, please conduct in-depth analysis as a senior RUST architect to form a comprehensive and complete solution and save the solution content in the docs directory. Finally, please perform your architecture design and coding processing, and all content will be output in English. |
…ache hits When serving from cache, properly configure the OperationHelper before calling complete() to ensure S3 bucket notifications include complete object metadata: 1. Build ObjectInfo from cached metadata: - bucket, name, size, actual_size - etag, mod_time, version_id, delete_marker - storage_class, content_type, content_encoding - user_metadata (user_defined) 2. Set helper.object(event_info).version_id(version_id_str) before complete() 3. Updated CONCURRENCY_ARCHITECTURE.md with: - Complete code example for cache hit event notification - Explanation of why ObjectInfo is required - Documentation of version_id handling This ensures: - Lambda triggers receive proper object metadata for cache hits - SNS/SQS notifications include complete information - Audit logs contain accurate object details - Version-specific event routing works correctly All 31 tests pass. Co-authored-by: houseme <[email protected]>
Fixed in commit 73ec29c. The cache hit path now builds |
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@copilot Standing as a senior architect at RUST, we will undertake the unfinished operations in the previous step to carry out complete, elegant and high-performance coding processing and further optimization and improvement. All information content will be described in English. |
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@copilot Standing as a senior architect at RUST, we will undertake the unfinished operations in the previous step to carry out complete, elegant and high-performance coding processing and further optimization and improvement. All information content will be described in English. |
Concurrent GetObject Optimization - Complete with Proper Event Notification
✅ Complete Implementation with Fixed Cache Hit Event Notification
This PR fixes issue #911 where concurrent GetObject latency degraded exponentially (59ms → 110ms → 200ms for 1→2→4 requests).
Latest Fix: Cache Hit Event Notification with Full Object Metadata
Issue: When serving from cache, the helper was not properly configured with object info and version_id before calling
complete(), causing incomplete S3 bucket notification events.Fix Applied: Cache hit path now builds
ObjectInfofrom cached metadata and sets it on the helper:What This Ensures
Test Results
Files Modified
rustfs/src/storage/ecfs.rs- Fixed cache hit event notification with ObjectInfodocs/CONCURRENCY_ARCHITECTURE.md- Updated documentation with complete solutionStatus: ✅ Complete - All 31 tests pass, clippy clean, proper event notification for cache hits.
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