246 lines
9.5 KiB
C++
246 lines
9.5 KiB
C++
// Simeon lexical score() latency by term rarity (IDF bucket) benchmark.
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//
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// Produces the decision data for the hot-term posting-list cache (#3):
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// p50/p95 score() latency for the 100 most-common (low-IDF) vs 100 rarest
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// (high-IDF) corpus terms, plus repeat-query hit rate with the existing
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// hot-query score cache on vs off.
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//
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// Environment variables:
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// YAMS_BENCH_DOC_COUNT - corpus size in documents (default: 1000)
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// YAMS_BENCH_VOCAB - vocabulary size (default: 2000)
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// YAMS_BENCH_CALLS - score() calls per term (default: 3)
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// YAMS_BENCH_OUTPUT - JSONL output path
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#define CATCH_CONFIG_MAIN
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#include <catch2/catch_session.hpp>
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#include <catch2/catch_test_macros.hpp>
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#include <algorithm>
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#include <chrono>
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#include <cstdint>
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#include <cstdlib>
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#include <filesystem>
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#include <fstream>
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#include <random>
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#include <string>
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#include <thread>
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#include <unordered_map>
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#include <vector>
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#include <nlohmann/json.hpp>
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#include <spdlog/spdlog.h>
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#include "bench_utils.h"
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#include <yams/metadata/connection_pool.h>
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#include <yams/metadata/metadata_repository.h>
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#include <yams/search/simeon_lexical_backend.h>
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namespace fs = std::filesystem;
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using json = nlohmann::json;
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using namespace yams;
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using namespace yams::metadata;
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using namespace yams::search;
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using yams::bench::isoTimestamp;
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using yams::bench::readIntEnv;
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namespace {
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struct Corpus {
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fs::path dbPath;
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std::unique_ptr<ConnectionPool> pool;
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std::shared_ptr<MetadataRepository> repo;
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std::vector<std::int64_t> docIds;
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std::unordered_map<std::string, int> docFrequency;
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~Corpus() {
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repo.reset();
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if (pool) {
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pool->shutdown();
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}
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pool.reset();
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std::error_code ec;
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fs::remove(dbPath, ec);
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fs::remove(fs::path(dbPath.string() + "-wal"), ec);
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fs::remove(fs::path(dbPath.string() + "-shm"), ec);
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}
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};
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std::unique_ptr<Corpus> makeZipfCorpus(int docCount, int vocabSize) {
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auto corpus = std::make_unique<Corpus>();
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corpus->dbPath =
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fs::temp_directory_path() /
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("simeon_score_bench_" +
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std::to_string(std::chrono::steady_clock::now().time_since_epoch().count()) + ".db");
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ConnectionPoolConfig pcfg;
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corpus->pool = std::make_unique<ConnectionPool>(corpus->dbPath.string(), pcfg);
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REQUIRE(corpus->pool->initialize().has_value());
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corpus->repo = std::make_shared<MetadataRepository>(*corpus->pool);
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std::mt19937_64 rng(0x51DEBE7Cull);
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std::vector<double> weights(static_cast<std::size_t>(vocabSize));
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for (int i = 0; i < vocabSize; ++i) {
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weights[static_cast<std::size_t>(i)] = 1.0 / static_cast<double>(i + 1);
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}
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std::discrete_distribution<int> zipf(weights.begin(), weights.end());
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for (int d = 0; d < docCount; ++d) {
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std::string content;
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std::unordered_map<std::string, bool> seenInDoc;
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for (int t = 0; t < 60; ++t) {
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const auto term = "term" + std::to_string(zipf(rng));
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content += term;
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content += ' ';
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if (!seenInDoc[term]) {
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seenInDoc[term] = true;
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corpus->docFrequency[term]++;
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}
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}
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const auto hash = "hash_" + std::to_string(d);
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DocumentInfo info;
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info.filePath = "/bench/doc_" + std::to_string(d) + ".txt";
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info.fileName = "doc_" + std::to_string(d) + ".txt";
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info.fileExtension = ".txt";
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info.fileSize = static_cast<int64_t>(content.size());
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info.sha256Hash = hash;
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info.mimeType = "text/plain";
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info.createdTime =
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std::chrono::floor<std::chrono::seconds>(std::chrono::system_clock::now());
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info.modifiedTime = info.createdTime;
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info.indexedTime = info.createdTime;
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auto did = corpus->repo->insertDocument(info);
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REQUIRE(did.has_value());
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corpus->docIds.push_back(did.value());
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REQUIRE(corpus->repo->indexDocumentContent(did.value(), hash, content, "text/plain")
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.has_value());
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DocumentContent dc;
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dc.documentId = did.value();
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dc.contentText = content;
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dc.contentLength = static_cast<int64_t>(content.size());
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dc.extractionMethod = "bench";
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dc.language = "en";
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REQUIRE(corpus->repo->insertContent(dc).has_value());
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}
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return corpus;
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}
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bool waitReady(const SimeonLexicalBackend& backend, std::chrono::seconds timeout) {
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const auto deadline = std::chrono::steady_clock::now() + timeout;
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while (std::chrono::steady_clock::now() < deadline) {
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if (backend.ready()) {
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return true;
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}
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std::this_thread::sleep_for(std::chrono::milliseconds(25));
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}
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return backend.ready();
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}
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struct BucketLatency {
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double p50Us = 0.0;
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double p95Us = 0.0;
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double maxUs = 0.0;
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};
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BucketLatency measureBucket(const SimeonLexicalBackend& backend,
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const std::vector<std::string>& terms,
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const std::vector<std::int64_t>& docIds, int callsPerTerm) {
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std::vector<double> samples;
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samples.reserve(terms.size() * static_cast<std::size_t>(callsPerTerm));
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for (const auto& term : terms) {
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for (int c = 0; c < callsPerTerm; ++c) {
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const auto start = std::chrono::steady_clock::now();
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auto result = backend.score(term, docIds);
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const auto us = std::chrono::duration<double, std::micro>(
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std::chrono::steady_clock::now() - start)
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.count();
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REQUIRE(result.has_value());
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samples.push_back(us);
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}
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}
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std::sort(samples.begin(), samples.end());
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BucketLatency out;
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if (!samples.empty()) {
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out.p50Us = samples[samples.size() / 2];
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out.p95Us = samples[static_cast<std::size_t>(static_cast<double>(samples.size()) * 0.95)];
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out.maxUs = samples.back();
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}
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return out;
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}
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} // namespace
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TEST_CASE("Simeon lexical score latency by IDF bucket", "[bench][simeon][score-idf]") {
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const int docCount = readIntEnv("YAMS_BENCH_DOC_COUNT", 1000, 10, 100000);
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const int vocabSize = readIntEnv("YAMS_BENCH_VOCAB", 2000, 100, 100000);
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const int callsPerTerm = readIntEnv("YAMS_BENCH_CALLS", 3, 1, 100);
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std::string outputPath = "bench_results/simeon_lexical_score.jsonl";
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if (const char* out = std::getenv("YAMS_BENCH_OUTPUT")) {
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outputPath = out;
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}
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if (auto parent = fs::path(outputPath).parent_path(); !parent.empty()) {
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fs::create_directories(parent);
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}
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std::ofstream outFile(outputPath, std::ios::app);
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REQUIRE(outFile.is_open());
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auto corpus = makeZipfCorpus(docCount, vocabSize);
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std::vector<std::pair<std::string, int>> byFrequency(corpus->docFrequency.begin(),
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corpus->docFrequency.end());
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std::sort(byFrequency.begin(), byFrequency.end(),
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[](const auto& a, const auto& b) { return a.second > b.second; });
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REQUIRE(byFrequency.size() >= 200);
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std::vector<std::string> commonTerms;
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std::vector<std::string> rareTerms;
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for (std::size_t i = 0; i < 100; ++i) {
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commonTerms.push_back(byFrequency[i].first);
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rareTerms.push_back(byFrequency[byFrequency.size() - 1 - i].first);
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}
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SimeonLexicalBackend::Config cfg;
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SimeonLexicalBackend backend(cfg);
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REQUIRE(backend.buildAsync(corpus->repo).has_value());
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REQUIRE(waitReady(backend, std::chrono::seconds(60)));
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const auto common = measureBucket(backend, commonTerms, corpus->docIds, callsPerTerm);
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const auto rare = measureBucket(backend, rareTerms, corpus->docIds, callsPerTerm);
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SimeonLexicalBackend::Config cachedCfg;
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cachedCfg.score_cache_entries = 256;
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SimeonLexicalBackend cachedBackend(cachedCfg);
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REQUIRE(cachedBackend.buildAsync(corpus->repo).has_value());
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REQUIRE(waitReady(cachedBackend, std::chrono::seconds(60)));
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const auto cachedCold = measureBucket(cachedBackend, commonTerms, corpus->docIds, 1);
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const auto hitsBefore = cachedBackend.scoreCacheHits();
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const auto cachedWarm = measureBucket(cachedBackend, commonTerms, corpus->docIds, 1);
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const auto warmHits = cachedBackend.scoreCacheHits() - hitsBefore;
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json record{{"benchmark", "simeon_lexical_score_idf"},
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{"timestamp", isoTimestamp()},
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{"doc_count", docCount},
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{"vocab_size", vocabSize},
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{"calls_per_term", callsPerTerm},
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{"common_df_min", byFrequency[99].second},
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{"rare_df_max", byFrequency[byFrequency.size() - 100].second},
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{"common_p50_us", common.p50Us},
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{"common_p95_us", common.p95Us},
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{"common_max_us", common.maxUs},
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{"rare_p50_us", rare.p50Us},
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{"rare_p95_us", rare.p95Us},
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{"rare_max_us", rare.maxUs},
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{"cache_cold_p50_us", cachedCold.p50Us},
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{"cache_warm_p50_us", cachedWarm.p50Us},
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{"cache_warm_hit_rate", static_cast<double>(warmHits) / 100.0},
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{"score_calls_total", backend.scoreCalls()},
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{"score_micros_total", backend.scoreMicrosTotal()}};
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outFile << record.dump() << '\n';
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spdlog::info("[simeon_score_idf] docs={} vocab={} common p50/p95={:.1f}/{:.1f}us "
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"rare p50/p95={:.1f}/{:.1f}us cache cold/warm p50={:.1f}/{:.1f}us hit_rate={:.2f}",
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docCount, vocabSize, common.p50Us, common.p95Us, rare.p50Us, rare.p95Us,
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cachedCold.p50Us, cachedWarm.p50Us, static_cast<double>(warmHits) / 100.0);
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}
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