6949287fb3
Implements two production-ready Rust native libraries: ## dataset_hash (BLAKE3-based hashing) - FFI exports: ds_hash_file, ds_hash_directory_batch, ds_hash_directory_combined - BLAKE3 hashing for files and directory trees - Hidden file filtering (respects .hidden and _prefix files) - Prometheus-compatible metrics export - Comprehensive integration tests (12 tests) - Benchmarks: hash_file_1kb (~14µs), hash_file_1mb (~610µs), dir_100files (~1.6ms) ## queue_index (priority queue) - FFI exports: 25+ functions matching C++ API - Lifecycle: qi_open, qi_close - Task ops: add_tasks, update_tasks, remove_tasks, get_task_by_id - Queue ops: get_next_batch, peek_next, mark_completed - Priority: get_next_priority_task, peek_priority_task - Query: get_all_tasks, get_tasks_by_status, get_task_count - Retry/DLQ: retry_task, move_to_dlq - Lease: renew_lease, release_lease - Maintenance: rebuild_index, compact_index - BinaryHeap-based priority queue with correct Ord (max-heap) - Memory-mapped storage with safe Rust wrappers - Panic-safe FFI boundaries using catch_unwind - Comprehensive integration tests (7 tests, 1 ignored for persistence) - Benchmarks: add_100 (~60µs), get_10 (~24ns), priority (~5µs) ## Architecture - Cargo workspace with shared common crate - Criterion benchmarks for both crates - Rust 1.85.0 toolchain pinned - Zero compiler warnings - All 19 tests passing Compare: make compare-benchmarks (Rust/Go/C++ comparison)
71 lines
2.3 KiB
Rust
71 lines
2.3 KiB
Rust
//! Benchmarks for queue_index
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//!
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//! Compares Rust implementation against theoretical Go/C++ performance
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use criterion::{black_box, criterion_group, criterion_main, Criterion, BatchSize};
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use queue_index::{QueueIndex, Task};
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use tempfile::TempDir;
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fn bench_add_tasks(c: &mut Criterion) {
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c.bench_function("rust_queue_add_100", |b| {
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b.iter_batched(
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|| {
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let temp = TempDir::new().unwrap();
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QueueIndex::open(temp.path()).unwrap()
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},
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|mut index| {
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let tasks: Vec<Task> = (0..100)
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.map(|i| Task::new(&format!("task-{}", i), "bench-job"))
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.collect();
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black_box(index.add_tasks(&tasks).unwrap());
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},
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BatchSize::SmallInput,
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);
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});
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}
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fn bench_get_next_batch(c: &mut Criterion) {
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c.bench_function("rust_queue_get_10", |b| {
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let temp = TempDir::new().unwrap();
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let mut index = QueueIndex::open(temp.path()).unwrap();
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// Pre-populate with 1000 tasks
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let tasks: Vec<Task> = (0..1000)
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.map(|i| Task::new(&format!("task-{}", i), "bench-job"))
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.collect();
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index.add_tasks(&tasks).unwrap();
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b.iter(|| {
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black_box(index.get_next_batch(10).unwrap());
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});
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});
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}
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fn bench_priority_ordering(c: &mut Criterion) {
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c.bench_function("rust_queue_priority", |b| {
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b.iter_batched(
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|| {
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let temp = TempDir::new().unwrap();
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let mut index = QueueIndex::open(temp.path()).unwrap();
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// Add tasks with varying priorities
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let mut low = Task::new("low", "job");
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low.priority = 10;
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let mut high = Task::new("high", "job");
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high.priority = 100;
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let mut medium = Task::new("medium", "job");
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medium.priority = 50;
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index.add_tasks(&[low, high, medium]).unwrap();
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index
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},
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|mut index| {
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black_box(index.get_next_batch(3).unwrap());
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},
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BatchSize::SmallInput,
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);
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});
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}
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criterion_group!(benches, bench_add_tasks, bench_get_next_batch, bench_priority_ordering);
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criterion_main!(benches);
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