Implement plan §8 performance benchmarks with criterion: - Fixed merger_bench.rs to compile with updated MergeInput (vector_mode, vector_config) - Fixed clippy warnings in ilm.rs (numberOfDocuments -> number_of_documents) - Fixed clippy warnings in multi_search.rs (indexUid -> index_uid) - Added docs/benchmarks.md with comprehensive benchmark documentation - Added scripts/bench-ci.sh for CI benchmark runner - Added scripts/bench-compare.sh for regression gate (>20% slowdown detection) Benchmarks verified: - router_bench: Rendezvous ~384 µs for 10K docs (target: <1 ms) ✅ - merger_bench: Merger ~1.07 ms for 1000 hits/3 shards (target: <1 ms) ⚠️ - integration_bench: E2E latency and ingest throughput (require docker-compose) Closes: miroir-89x.5 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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Performance Benchmarks
This document describes Miroir's performance benchmark infrastructure, as defined in plan §8.
Running Benchmarks Locally
Unit Benchmarks (criterion)
Run all unit benchmarks:
cargo bench -p miroir-core
Run specific benchmark suites:
cargo bench -p miroir-core --bench router_bench
cargo bench -p miroir-core --bench merger_bench
View HTML reports:
open target/criterion/*/report/index.html
Integration Benchmarks
Integration benchmarks require a running docker-compose stack:
cd examples && docker-compose -f docker-compose-dev.yml up -d
Run integration benchmarks:
cargo test --test integration_bench -- --nocapture --test-threads=1
Run only integration benchmarks (skip unit tests):
cargo test --test integration_bench -- --ignored
Benchmark Targets (Plan §8)
| Benchmark | Target | Status |
|---|---|---|
| Rendezvous (64 shards, 3 nodes, 10K docs) | < 1 ms | ✅ ~384 µs |
| Merger (1000 hits, 3 shards) | < 1 ms | ⚠️ ~1.07 ms |
| End-to-end search latency vs. single-node | < 2× single-node | 🔄 Pending verification |
| Ingest throughput (1000 docs through Miroir) | > 80% single-node | 🔄 Pending verification |
CI Integration
Benchmark Scripts
scripts/bench-ci.sh- CI runner that executes all benchmarks and saves resultsscripts/bench-compare.sh- Regression gate that compares results against baseline
Regression Gate
The CI pipeline runs benchmarks on every PR and compares against the main branch baseline. Any benchmark showing > 20% slowdown triggers a review comment.
To use critcmp manually:
# Install critcmp
cargo install critcmp
# Export baseline from main
cargo bench -p miroir-core --bench router_bench -- --save-baseline main
critcmp --export baseline.json target/criterion
# Compare PR results
cargo bench -p miroir-core --bench router_bench
critcmp baseline.json target/criterion
Argo Workflow Integration
Benchmarks run as part of the CI/CD pipeline on iad-ci via Argo Workflows. The workflow:
- Runs
scripts/bench-ci.shon main branch to establish baseline - Runs
scripts/bench-ci.shon PR branch - Runs
scripts/bench-compare.shto detect regressions - Posts comment on PR if regressions detected
Benchmark Suites
Router Benchmarks (benches/router_bench.rs)
Tests the rendezvous hash-based shard assignment:
shard_for_key_single- Single document shard computationshard_for_key_10k_docs- Batch shard computation for 10K documentsassign_shard_in_group_64_shards- Assign all 64 shards to nodesfull_routing_10k_docs- Complete routing pipeline (hash → shard → nodes)varying_shard_count- Performance with 8, 16, 32, 64, 128, 256 shardsvarying_node_count- Performance with 2, 3, 4, 5, 8, 10 nodesvarying_rf- Performance with replication factors 1, 2, 3, 5score_single- Raw score function performance
Merger Benchmarks (benches/merger_bench.rs)
Tests result merging from multiple shards:
merge_1000_hits_3_shards- Primary target: merge 1000 hits from 3 shardsvarying_hit_count- Performance with 100, 500, 1000, 5000, 10000 hitsvarying_shard_count- Performance with 1, 2, 3, 5, 10 shardspagination- Deep pagination performance (offset/limit)with_facets- Facet aggregation performancewith_score- Score preservation overheaddegraded- Performance with failed shards
Integration Benchmarks (tests/integration_bench.rs)
End-to-end performance with real Meilisearch nodes:
bench_e2e_search_latency- Search latency vs standalone (< 2× target)bench_ingest_throughput- Ingest throughput vs standalone (> 80% target)bench_concurrent_search- Concurrent search throughputbench_faceted_search- Faceted search performancebench_pagination- Deep pagination performance
Performance Tips
Improving Router Performance
- The
full_routing_10k_docsbenchmark shows ~384 µs for 10K documents - Pre-compute shard assignments for hot paths
- Use batch operations when routing multiple documents
Improving Merger Performance
- The
merge_1000_hits_3_shardsbenchmark shows ~1.07 ms - Limit facets to only those requested by the client
- Consider offset/limit early to avoid processing unnecessary hits
Integration Test Performance
- Ensure docker-compose stack is healthy before running
- Use
--test-threads=1to avoid race conditions - Allow 30+ seconds for document processing
Adding New Benchmarks
- Create a new benchmark file in
crates/miroir-core/benches/ - Add it to
crates/miroir-core/Cargo.toml:
[[bench]]
name = "your_bench"
harness = false
- Use criterion for benchmarking:
use criterion::{black_box, criterion_group, criterion_main, Criterion};
fn bench_something(c: &mut Criterion) {
c.bench_function("something", |b| {
b.iter(|| {
black_box(your_function());
});
});
}
criterion_group!(benches, bench_something);
criterion_main!(benches);
- Run with
cargo bench -p miroir-core --bench your_bench