memgraph/tests/benchmark/query/planner.cpp
Teon Banek 0aee18544d Add caching VerticesCount during planning and estimation
Summary:
Benchmark planning and estimating indexed ScanAll. According to the benchmark,
caching speeds up the whole process of planning and estimation by a factor of
2. Most of the performance gain is in the `CostEstimator` itself, due to plenty
of calls to `VerticesCount` when estimating all of the generated plans.

Reviewers: mislav.bradac, florijan

Reviewed By: mislav.bradac

Subscribers: pullbot

Differential Revision: https://phabricator.memgraph.io/D765
2017-09-09 12:26:48 +02:00

156 lines
5.5 KiB
C++

#include <string>
#include <benchmark/benchmark_api.h>
#include "database/dbms.hpp"
#include "query/frontend/semantic/symbol_generator.hpp"
#include "query/plan/cost_estimator.hpp"
#include "query/plan/planner.hpp"
#include "query/plan/vertex_count_cache.hpp"
// Add chained MATCH (node1) -- (node2), MATCH (node2) -- (node3) ... clauses.
static void AddChainedMatches(int num_matches, query::AstTreeStorage &storage) {
for (int i = 0; i < num_matches; ++i) {
auto *match = storage.Create<query::Match>();
auto *pattern = storage.Create<query::Pattern>();
pattern->identifier_ = storage.Create<query::Identifier>("path");
match->patterns_.emplace_back(pattern);
std::string node1_name = "node" + std::to_string(i - 1);
pattern->atoms_.emplace_back(storage.Create<query::NodeAtom>(
storage.Create<query::Identifier>(node1_name)));
pattern->atoms_.emplace_back(storage.Create<query::EdgeAtom>(
storage.Create<query::Identifier>("edge" + std::to_string(i)),
query::EdgeAtom::Direction::BOTH));
pattern->atoms_.emplace_back(storage.Create<query::NodeAtom>(
storage.Create<query::Identifier>("node" + std::to_string(i))));
storage.query()->clauses_.emplace_back(match);
}
}
static void BM_PlanChainedMatches(benchmark::State &state) {
Dbms dbms;
auto dba = dbms.active();
while (state.KeepRunning()) {
state.PauseTiming();
query::AstTreeStorage storage;
int num_matches = state.range(0);
AddChainedMatches(num_matches, storage);
query::SymbolTable symbol_table;
query::SymbolGenerator symbol_generator(symbol_table);
storage.query()->Accept(symbol_generator);
state.ResumeTiming();
query::plan::MakeLogicalPlan<query::plan::VariableStartPlanner>(
storage, symbol_table, *dba);
}
}
BENCHMARK(BM_PlanChainedMatches)
->RangeMultiplier(2)
->Range(50, 400)
->Unit(benchmark::kMillisecond);
static void AddIndexedMatches(
int num_matches, const GraphDbTypes::Label &label,
const std::pair<std::string, GraphDbTypes::Property> &property,
query::AstTreeStorage &storage) {
for (int i = 0; i < num_matches; ++i) {
auto *match = storage.Create<query::Match>();
auto *pattern = storage.Create<query::Pattern>();
pattern->identifier_ = storage.Create<query::Identifier>("path");
match->patterns_.emplace_back(pattern);
std::string node1_name = "node" + std::to_string(i - 1);
auto *node = storage.Create<query::NodeAtom>(
storage.Create<query::Identifier>(node1_name));
node->labels_.emplace_back(label);
node->properties_[property] = storage.Create<query::PrimitiveLiteral>(i);
pattern->atoms_.emplace_back(node);
storage.query()->clauses_.emplace_back(match);
}
}
static auto CreateIndexedVertices(int index_count, int vertex_count,
Dbms &dbms) {
auto dba = dbms.active();
auto label = dba->Label("label");
auto prop = dba->Property("prop");
dba->BuildIndex(label, prop);
dba = dbms.active();
for (int vi = 0; vi < vertex_count; ++vi) {
for (int index = 0; index < index_count; ++index) {
auto vertex = dba->InsertVertex();
vertex.add_label(label);
vertex.PropsSet(prop, index);
}
}
dba->Commit();
return std::make_pair(label, prop);
}
static void BM_PlanAndEstimateIndexedMatching(benchmark::State &state) {
Dbms dbms;
GraphDbTypes::Label label;
GraphDbTypes::Property prop;
int index_count = state.range(0);
int vertex_count = state.range(1);
std::tie(label, prop) =
CreateIndexedVertices(index_count, vertex_count, dbms);
auto dba = dbms.active();
while (state.KeepRunning()) {
state.PauseTiming();
query::AstTreeStorage storage;
AddIndexedMatches(index_count, label, std::make_pair("prop", prop),
storage);
query::SymbolTable symbol_table;
query::SymbolGenerator symbol_generator(symbol_table);
storage.query()->Accept(symbol_generator);
state.ResumeTiming();
auto plans =
query::plan::MakeLogicalPlan<query::plan::VariableStartPlanner>(
storage, symbol_table, *dba);
for (auto &plan : plans) {
query::plan::EstimatePlanCost(*dba, *plan);
}
}
}
static void BM_PlanAndEstimateIndexedMatchingWithCachedCounts(
benchmark::State &state) {
Dbms dbms;
GraphDbTypes::Label label;
GraphDbTypes::Property prop;
int index_count = state.range(0);
int vertex_count = state.range(1);
std::tie(label, prop) =
CreateIndexedVertices(index_count, vertex_count, dbms);
auto dba = dbms.active();
auto vertex_counts = query::plan::MakeVertexCountCache(*dba);
while (state.KeepRunning()) {
state.PauseTiming();
query::AstTreeStorage storage;
AddIndexedMatches(index_count, label, std::make_pair("prop", prop),
storage);
query::SymbolTable symbol_table;
query::SymbolGenerator symbol_generator(symbol_table);
storage.query()->Accept(symbol_generator);
state.ResumeTiming();
auto plans =
query::plan::MakeLogicalPlan<query::plan::VariableStartPlanner>(
storage, symbol_table, vertex_counts);
for (auto &plan : plans) {
query::plan::EstimatePlanCost(vertex_counts, *plan);
}
}
}
BENCHMARK(BM_PlanAndEstimateIndexedMatching)
->RangeMultiplier(4)
->Ranges({{1, 100}, {100, 1000}})
->Unit(benchmark::kMicrosecond);
BENCHMARK(BM_PlanAndEstimateIndexedMatchingWithCachedCounts)
->RangeMultiplier(4)
->Ranges({{1, 100}, {100, 1000}})
->Unit(benchmark::kMicrosecond);
BENCHMARK_MAIN();