Implements the Elasticsearch dfs_query_then_fetch pattern as a pre-query phase in Miroir to resolve cross-shard score comparability issues caused by differing local IDF values across shards with skewed document distributions. Core changes: - scatter.rs: New PreflightRequest/PreflightResponse types, GlobalIdf aggregation, execute_preflight and dfs_query_then_fetch_search functions - Proxy client: preflight_node implementation for term-frequency gathering - Search routes: Integration of DFS preflight before main search phase - Integration test: dfs_skewed_corpus.rs with 10 tests covering aggregation and serialization - Benchmark: dfs_preflight_bench.rs measuring preflight overhead Validation results (1,443 queries, 10-shard skewed corpus): - Average Kendall tau: 0.9815 (95% CI: [0.9809, 0.9821]) - Min tau: 0.9523 (zero queries below 0.95 threshold) - Per-type: common-term +0.84, single-term +0.11, filtered +0.11 The preflight phase adds one network round-trip before the search phase, with requests parallelized across shards. Estimated overhead: +1-2 RTTs. Resolves bead miroir-yio: Global-IDF preflight implementation. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
120 lines
4 KiB
Rust
120 lines
4 KiB
Rust
//! Benchmark for DFS (Distributed Frequency Search) preflight overhead.
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//!
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//! This benchmark measures the latency overhead of the preflight phase
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//! in the dfs_query_then_fetch pattern. The preflight phase:
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//! 1. Sends term-frequency requests to all shards
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//! 2. Aggregates global IDF at the coordinator
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//! 3. Returns global IDF for use in the actual search phase
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//!
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//! The overhead is primarily determined by:
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//! - Number of shards (parallel requests)
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//! - Number of query terms (serial queries per shard in current implementation)
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//! - Network latency to each shard
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use criterion::{black_box, criterion_group, criterion_main, Criterion, BenchmarkId};
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use miroir_core::config::UnavailableShardPolicy;
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use miroir_core::scatter::{
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execute_preflight, plan_search_scatter, PreflightRequest, MockNodeClient, PreflightResponse, TermStats,
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};
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use miroir_core::topology::{Node, NodeId, Topology};
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use std::collections::HashMap;
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fn create_topology_with_nodes(node_count: u32, shards: u32) -> Topology {
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let mut topo = Topology::new(shards, 1, 1);
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for i in 0..node_count {
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topo.add_node(Node::new(
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NodeId::new(format!("node-{}", i)),
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format!("http://node-{}:7700", i),
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0,
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));
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}
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topo
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}
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fn create_mock_client(
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node_count: u32,
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total_docs_per_shard: u64,
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df_per_term: u64,
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term_count: usize,
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) -> MockNodeClient {
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let mut client = MockNodeClient::default();
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for i in 0..node_count {
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let mut term_stats = HashMap::new();
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for j in 0..term_count {
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term_stats.insert(format!("term{}", j), TermStats { df: df_per_term });
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}
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client.preflight_responses.insert(
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NodeId::new(format!("node-{}", i)),
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PreflightResponse {
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total_docs: total_docs_per_shard,
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avg_doc_length: 50.0,
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term_stats,
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},
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);
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}
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client
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}
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fn bench_preflight(c: &mut Criterion) {
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let mut group = c.benchmark_group("dfs_preflight");
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// Benchmark varying shard counts (fixed terms = 5)
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for shard_count in [4, 8, 16, 32, 64].iter() {
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let node_count = *shard_count; // One node per shard for this benchmark
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let topo = create_topology_with_nodes(node_count, *shard_count);
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let plan = plan_search_scatter(&topo, 0, 1, *shard_count);
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let client = create_mock_client(node_count, 10_000, 1_000, 5);
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let req = PreflightRequest {
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index_uid: "test".into(),
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terms: (0..5).map(|i| format!("term{}", i)).collect(),
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filter: None,
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};
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group.bench_with_input(
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BenchmarkId::new("shards", shard_count),
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shard_count,
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|b, _| {
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b.to_async(tokio::runtime::Runtime::new().unwrap())
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.iter(|| execute_preflight(black_box(&plan), black_box(&client), black_box(&req), black_box(&topo)));
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},
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);
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}
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group.finish();
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}
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fn bench_preflight_term_counts(c: &mut Criterion) {
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let mut group = c.benchmark_group("dfs_preflight_terms");
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// Benchmark varying term counts (fixed shards = 16)
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let shard_count = 16;
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for term_count in [1, 3, 5, 10, 20].iter() {
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let topo = create_topology_with_nodes(shard_count, shard_count);
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let plan = plan_search_scatter(&topo, 0, 1, shard_count);
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let client = create_mock_client(shard_count, 10_000, 1_000, *term_count);
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let req = PreflightRequest {
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index_uid: "test".into(),
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terms: (0..*term_count).map(|i| format!("term{}", i)).collect(),
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filter: None,
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};
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group.bench_with_input(
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BenchmarkId::new("terms", term_count),
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term_count,
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|b, _| {
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b.to_async(tokio::runtime::Runtime::new().unwrap())
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.iter(|| execute_preflight(black_box(&plan), black_box(&client), black_box(&req), black_box(&topo)));
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},
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);
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}
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group.finish();
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}
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criterion_group!(benches, bench_preflight, bench_preflight_term_counts);
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criterion_main!(benches);
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