/* * Copyright (C) 2017 ScyllaDB */ /* * This file is part of Scylla. * * Scylla is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * Scylla is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with Scylla. If not, see . */ #pragma once #include #include #include #include // Simple proportional controller to adjust shares for processes for which a backlog can be clearly // defined. // // Goal is to consume the backlog as fast as we can, but not so fast that we steal all the CPU from // incoming requests, and at the same time minimize user-visible fluctuations in the quota. // // What that translates to is we'll try to keep the backlog's firt derivative at 0 (IOW, we keep // backlog constant). As the backlog grows we increase CPU usage, decreasing CPU usage as the // backlog diminishes. // // The exact point at which the controller stops determines the desired CPU usage. As the backlog // grows and approach a maximum desired, we need to be more aggressive. We will therefore define two // thresholds, and increase the constant as we cross them. // // Doing that divides the range in three (before the first, between first and second, and after // second threshold), and we'll be slow to grow in the first region, grow normally in the second // region, and aggressively in the third region. // // The constants q1 and q2 are used to determine the proportional factor at each stage. class backlog_controller { public: future<> shutdown() { _update_timer.cancel(); return std::move(_inflight_update); } protected: struct control_point { float input; float output; }; seastar::scheduling_group _scheduling_group; const ::io_priority_class& _io_priority; std::chrono::milliseconds _interval; timer<> _update_timer; std::vector _control_points; std::function _current_backlog; // updating shares for an I/O class may contact another shard and returns a future. future<> _inflight_update; virtual void update_controller(float quota); void adjust(); backlog_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, std::chrono::milliseconds interval, std::vector control_points, std::function backlog) : _scheduling_group(sg) , _io_priority(iop) , _interval(interval) , _update_timer([this] { adjust(); }) , _control_points({{0,0}}) , _current_backlog(std::move(backlog)) , _inflight_update(make_ready_future<>()) { _control_points.insert(_control_points.end(), control_points.begin(), control_points.end()); _update_timer.arm_periodic(_interval); } // Used when the controllers are disabled and a static share is used // When that option is deprecated we should remove this. backlog_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, float static_shares) : _scheduling_group(sg) , _io_priority(iop) , _inflight_update(make_ready_future<>()) { update_controller(static_shares); } virtual ~backlog_controller() {} public: backlog_controller(backlog_controller&&) = default; float backlog_of_shares(float shares) const; seastar::scheduling_group sg() { return _scheduling_group; } }; // memtable flush CPU controller. // // - First threshold is the soft limit line, // - Maximum is the point in which we'd stop consuming request, // - Second threshold is halfway between them. // // Below the soft limit, we are in no particular hurry to flush, since it means we're set to // complete flushing before we a new memtable is ready. The quota is dirty * q1, and q1 is set to a // low number. // // The first half of the virtual dirty region is where we expect to be usually, so we have a low // slope corresponding to a sluggish response between q1 * soft_limit and q2. // // In the second half, we're getting close to the hard dirty limit so we increase the slope and // become more responsive, up to a maximum quota of qmax. class flush_controller : public backlog_controller { static constexpr float hard_dirty_limit = 1.0f; public: flush_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, float static_shares) : backlog_controller(sg, iop, static_shares) {} flush_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, std::chrono::milliseconds interval, float soft_limit, std::function current_dirty) : backlog_controller(sg, iop, std::move(interval), std::vector({{soft_limit, 10}, {soft_limit + (hard_dirty_limit - soft_limit) / 2, 200} , {hard_dirty_limit, 1000}}), std::move(current_dirty) ) {} }; class compaction_controller : public backlog_controller { public: static constexpr unsigned normalization_factor = 30; static constexpr float disable_backlog = std::numeric_limits::infinity(); static constexpr float backlog_disabled(float backlog) { return std::isinf(backlog); } compaction_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, float static_shares) : backlog_controller(sg, iop, static_shares) {} compaction_controller(seastar::scheduling_group sg, const ::io_priority_class& iop, std::chrono::milliseconds interval, std::function current_backlog) : backlog_controller(sg, iop, std::move(interval), std::vector({{0.5, 10}, {1.5, 100} , {normalization_factor, 1000}}), std::move(current_backlog) ) {} };