#pragma once #include #include "data_structures/concurrent/concurrent_map.hpp" #include "database/graph_db.hpp" #include "database/graph_db_accessor.hpp" #include "query/context.hpp" #include "query/frontend/ast/ast.hpp" #include "query/frontend/stripped.hpp" #include "query/interpret/frame.hpp" #include "query/plan/distributed.hpp" #include "query/plan/operator.hpp" #include "utils/thread/sync.hpp" #include "utils/timer.hpp" DECLARE_int32(query_plan_cache_ttl); namespace distributed { class PlanDispatcher; } namespace integrations { namespace kafka { class Streams; } // namespace kafka } // namespace integrations namespace query { class Interpreter { private: /// Encapsulates a plan for caching. Takes care of remote (worker) cache /// updating in distributed memgraph. class CachedPlan { public: /// Creates a cached plan and sends it to all the workers. CachedPlan(plan::DistributedPlan distributed_plan, double cost, distributed::PlanDispatcher *plan_dispatcher); /// Removes the cached plan from all the workers. ~CachedPlan(); const auto &plan() const { return *distributed_plan_.master_plan; } const auto &distributed_plan() const { return distributed_plan_; } double cost() const { return cost_; } const auto &symbol_table() const { return distributed_plan_.symbol_table; } bool IsExpired() const { return cache_timer_.Elapsed() > std::chrono::seconds(FLAGS_query_plan_cache_ttl); }; private: plan::DistributedPlan distributed_plan_; double cost_; utils::Timer cache_timer_; // Optional, only available in a distributed master. distributed::PlanDispatcher *plan_dispatcher_{nullptr}; }; using PlanCacheT = ConcurrentMap>; public: /** * Encapsulates all what's necessary for the interpretation of a query * into a single object that can be pulled (into the given Stream). */ class Results { friend Interpreter; Results(Context ctx, std::shared_ptr plan, std::unique_ptr cursor, std::vector output_symbols, std::vector header, std::map summary, PlanCacheT &plan_cache) : ctx_(std::move(ctx)), plan_(plan), cursor_(std::move(cursor)), frame_(ctx_.symbol_table_.max_position()), output_symbols_(output_symbols), header_(header), summary_(summary), plan_cache_(plan_cache) {} public: Results(const Results &) = delete; Results(Results &&) = default; Results &operator=(const Results &) = delete; Results &operator=(Results &&) = default; /** * Make the interpreter perform a single Pull. Results (if they exists) are * pushed into the given stream. On first Pull the header is written to the * stream, on last the summary. * * @param stream - The stream to push the header, results and summary into. * @return - If this Results is eligible for another Pull. If Pulling * after `false` has been returned, the behavior is undefined. * @tparam TStream - Stream type. */ template bool Pull(TStream &stream) { utils::Timer timer; bool return_value = cursor_->Pull(frame_, ctx_); if (return_value && !output_symbols_.empty()) { std::vector values; values.reserve(output_symbols_.size()); for (const auto &symbol : output_symbols_) { values.emplace_back(frame_[symbol]); } stream.Result(values); } execution_time_ += timer.Elapsed().count(); if (!return_value) { summary_["plan_execution_time"] = execution_time_; if (ctx_.is_index_created_) { auto access = plan_cache_.access(); for (auto &kv : access) { access.remove(kv.first); } } } return return_value; } /** Calls Pull() until exhausted. */ template void PullAll(TStream &stream) { while (Pull(stream)) continue; } const std::vector &header() { return header_; } const std::map &summary() { return summary_; } private: Context ctx_; std::shared_ptr plan_; std::unique_ptr cursor_; Frame frame_; std::vector output_symbols_; std::vector header_; std::map summary_; double execution_time_{0}; // Gets invalidated after if an index has been built. PlanCacheT &plan_cache_; }; explicit Interpreter(database::GraphDb &db); Interpreter(const Interpreter &) = delete; Interpreter &operator=(const Interpreter &) = delete; Interpreter(Interpreter &&) = delete; Interpreter &operator=(Interpreter &&) = delete; /** * Generates an Results object for the parameters. The resulting object * can the be Pulled with it's results written to an arbitrary stream. */ Results operator()(const std::string &query, database::GraphDbAccessor &db_accessor, const std::map ¶ms, bool in_explicit_transaction); integrations::kafka::Streams *kafka_streams_ = nullptr; private: ConcurrentMap ast_cache_; PlanCacheT plan_cache_; std::atomic next_plan_id_{0}; // Antlr has singleton instance that is shared between threads. It is // protected by locks inside of antlr. Unfortunately, they are not protected // in a very good way. Once we have antlr version without race conditions we // can remove this lock. This will probably never happen since antlr // developers introduce more bugs in each version. Fortunately, we have cache // so this lock probably won't impact performance much... utils::SpinLock antlr_lock_; // Optional, not null only in a distributed master. distributed::PlanDispatcher *plan_dispatcher_{nullptr}; // stripped query -> CachedPlan std::shared_ptr QueryToPlan(const StrippedQuery &stripped, Context &ctx); // stripped query -> high level tree AstStorage QueryToAst(const StrippedQuery &stripped, Context &ctx); // high level tree -> (logical plan, plan cost) // AstStorage and SymbolTable may be modified during planning. std::pair, double> MakeLogicalPlan( AstStorage &, Context &); }; } // namespace query