--- /dev/null
+============================================
+BlueStore Bufferbloat Mitigation Using CoDel
+============================================
+
+
+Introduction
+------------
+Bufferbloat happens when a frontend buffer too much data to a backend.
+This can introduce latency spikes to the backend and compromise the
+request schedulability of the frontend.
+
+BlueStore has the bufferbloat problem due to its large queue. All
+write requests are submitted immediately to BlueStore to achieve high
+performance. However, this can compromise request schedulability in OSD.
+As a solution, the CoDel algorithm is implemented in the BlueStore as
+an admission control system to control the amount of transaction
+submitted to BlueStore. This mechanism will negatively impact the
+throughput of BlueStore. However, a tradeoff parameter has been introduced
+to control BlueStore throughput loss versus BlueStore latency decrease.
+
+Configurations
+--------------
+CoDel can be enabled using "*bluestore_codel*" config. The other important
+config that needs to be set is "*bluestore_codel_throughput_latency_tradeoff*".
+This config adjust the tradeoff between BlueStore throughput loss and
+BlueStore latency decrease. This parameter defines the amount of throughput
+loss in MB/s for one ms decrease in BlueStore latency. For example, a value
+of 5 means that we are willing to lose maximum of 5 MB/s of throughput for
+every 1 ms decrease in BlueStore latency.
+
+Experiments
+-----------
+For measuring the impact of BlueStore CoDel on BlueStore, we measured the
+transaction latency inside the BlueStore (BlueStore latency) and BlueStore
+throughput. We compared this measurements with measurements from Vanilla BlueStore.
+These experiments shows that:
+
+1. The BlueStore CoDel can decrease the BlueStore latency by small and controllable
+impact on throughput.
+2. The BlueStore CoDel can react to workload changes to keep the desired tradeoff
+between latency and throughput.
--- /dev/null
+overrides:
+ thrashosds:
+ bdev_inject_crash: 2
+ bdev_inject_crash_probability: .5
+ ceph:
+ fs: xfs
+ conf:
+ osd:
+ osd objectstore: bluestore
+ bluestore block size: 96636764160
+ debug bluestore: 20
+ debug bluefs: 20
+ debug rocksdb: 10
+ bluestore fsck on mount: true
+ bluestore allocator: bitmap
+ # lower the full ratios since we can fill up a 100gb osd so quickly
+ mon osd full ratio: .9
+ mon osd backfillfull_ratio: .85
+ mon osd nearfull ratio: .8
+ osd failsafe full ratio: .95
+ # this doesn't work with failures bc the log writes are not atomic across the two backends
+ # bluestore bluefs env mirror: true
+ bdev enable discard: true
+ bdev async discard: true
+ bluestore codel: true
+ ceph-deploy:
+ fs: xfs
+ bluestore: yes
+ conf:
+ osd:
+ osd objectstore: bluestore
+ bluestore block size: 96636764160
+ debug bluestore: 20
+ debug bluefs: 20
+ debug rocksdb: 10
+ bluestore fsck on mount: true
+ # lower the full ratios since we can fill up a 100gb osd so quickly
+ mon osd full ratio: .9
+ mon osd backfillfull_ratio: .85
+ mon osd nearfull ratio: .8
+ osd failsafe full ratio: .95
+ bdev enable discard: true
+ bdev async discard: true
+ bluestore codel: true
+
default: 0
services:
- mgr
+- name: bluestore_codel
+ type: bool
+ level: advanced
+ desc: enable/disable bluestore SlowFastCodel
+ default: false
+ with_legacy: true
+- name: bluestore_codel_throughput_latency_tradeoff
+ type: float
+ level: advanced
+ desc: adjust the tradeoff between throughput and bluestore latency in SlowFastCodel
+ long_desc: This parameter defines the amount of throughput loss (MB/s) for one ms
+ decrease in bluestore latency. (a value of 5 means that we are willing to lose
+ maximum of 5 MB/s of throughput for every 1 ms decrease in bluestore latency)
+ default: 5
+ with_legacy: true
+- name: bluestore_codel_initial_target_latency
+ type: float
+ level: advanced
+ desc: initial target latency for SlowFastCodel in ms
+ default: 5.0
+ with_legacy: true
+- name: bluestore_codel_slow_interval
+ type: float
+ level: advanced
+ desc: the interval of slow loop in SlowFastCodel in ms (this parameter should be larger that 'bluestore_codel_fast_interval')
+ default: 500.0
+ with_legacy: true
+- name: bluestore_codel_fast_interval
+ type: float
+ level: advanced
+ desc: the interval of the fast loop in SlowFastCodel in ms
+ default: 50.0
+ with_legacy: true
+- name: bluestore_codel_min_target_latency
+ type: float
+ level: advanced
+ desc: the minimum possible target latency in SlowFastCodel in ms
+ default: 1.0
+ with_legacy: true
+- name: bluestore_codel_max_target_latency
+ type: float
+ level: advanced
+ desc: the maximum possible target latency in SlowFastCodel in ms
+ default: 1000.0
+ with_legacy: true
+- name: bluestore_codel_initial_budget_bytes
+ type: size
+ level: advanced
+ desc: the initial bluestore throttle budget in SlowFastCodel
+ default: 100_K
+ with_legacy: true
+- name: bluestore_codel_min_budget_bytes
+ type: size
+ level: advanced
+ desc: the minimum bluestore throttle budget in SlowFastCodel
+ default: 100_K
+ with_legacy: true
+- name: bluestore_codel_budget_increment_bytes
+ type: size
+ level: advanced
+ desc: the increment size for opening the bluestore throttle in SlowFastCodel
+ default: 10_K
+ with_legacy: true
+- name: bluestore_codel_regression_history_size
+ type: int
+ level: advanced
+ desc: number of the slow interval throughput and latency samples that SlowFastCodel keeps for regression
+ default: 100
+ with_legacy: true
--- /dev/null
+// -*- mode:C++; tab-width:8; c-basic-offset:2; indent-tabs-mode:t -*-
+
+#pragma once
+
+#include <iostream>
+#include <vector>
+#include <cmath>
+#include <boost/numeric/ublas/matrix.hpp>
+
+#define Z_P 2.33 // z score for 99th percentile
+
+
+namespace ceph {
+ /***
+ * Calculate the inverse of a 2x2 matrix.
+ * @param matrix<double>& m, an square 2x2 matrix
+ * @return the inverse of the m (m^-1)
+ */
+ static boost::numeric::ublas::matrix<double>
+ matrix_inverse(boost::numeric::ublas::matrix<double> &m) {
+ assert(m.size1() == m.size2() &&
+ "Can only calculate the inverse of square matrices");
+ assert(m.size1() == 2 && m.size2() == 2 && "Only for 2x2 matrices");
+ boost::numeric::ublas::matrix<double> m_inverse(2, 2);
+ const double a = m(0, 0);
+ const double b = m(0, 1);
+ const double c = m(1, 0);
+ const double d = m(1, 1);
+ const double determinant = 1.0 / ((a * d) - (b * c));
+ m_inverse(0, 0) = d * determinant;
+ m_inverse(0, 1) = -b * determinant;
+ m_inverse(1, 0) = -c * determinant;
+ m_inverse(1, 1) = a * determinant;
+ return m_inverse;
+ }
+
+ /***
+ * Find a logarithmic function in form of "y = a + b * ln(x)" which fits
+ * the given points (x_values and y_values).
+ * @param std::vector<double> x_values, x values for sample points
+ * @param std::vector<double> y_values, y values for sample points
+ * @param double theta[2], holds the a and b as output (theta[0] = a and theta[1] = b)
+ */
+ static void regression(
+ const std::vector<double> &x_values,
+ const std::vector<double> &y_values,
+ double theta[2]) {
+ assert(x_values.size() == y_values.size() &&
+ "x and y values vectors should have a same size.");
+ const int n = x_values.size();
+
+ boost::numeric::ublas::matrix<double> y_m(n, 1);
+ for (int i = 0; i < n; i++) {
+ y_m(i, 0) = y_values[i];
+ }
+
+ boost::numeric::ublas::scalar_matrix<double> sm(n, 2, 1);
+ boost::numeric::ublas::matrix<double> x_new_m(sm);
+ for (int i = 0; i < n; i++) {
+ x_new_m(i, 0) = 1;
+ x_new_m(i, 1) = std::log(x_values[i]);
+ }
+ boost::numeric::ublas::matrix<double> x_new_trans_m = boost::numeric::ublas::trans(
+ x_new_m);
+ boost::numeric::ublas::matrix<double> x_new_trans_dot_x_new_m = boost::numeric::ublas::prod(
+ x_new_trans_m, x_new_m);
+ boost::numeric::ublas::matrix<double> temp_1_m = matrix_inverse(
+ x_new_trans_dot_x_new_m);
+ boost::numeric::ublas::matrix<double> temp_2_m = boost::numeric::ublas::prod(
+ x_new_trans_m, y_m);
+ boost::numeric::ublas::matrix<double> theta_m = boost::numeric::ublas::prod(
+ temp_1_m, temp_2_m);
+ theta[0] = theta_m(0, 0);
+ theta[1] = theta_m(1, 0);
+ }
+
+ /***
+ * Finds the x location on a fitted logarithmic curve on sample points where
+ * the slope is equal to target_slope
+ * @param x_values, x values for sample points
+ * @param y_values, y values for sample points
+ * @param target_slope, the slope that we are looking for
+ * @return the x location where the slope of the curve is target_slope
+ */
+ static double find_slope_on_curve(
+ const std::vector<double> &x_values,
+ const std::vector<double> &y_values,
+ double target_slope) {
+ assert(x_values.size() == y_values.size() &&
+ "x and y values vectors should have a same size.");
+ assert(target_slope != 0 &&
+ "The target slope of zero will result to a inf x, try a nonzero value.");
+ assert(target_slope >= 0 &&
+ "The target slope for a logarithmic function should be positive.");
+ double theta[2]; // theta[0] + theta[1] * ln(x)
+ regression(x_values, y_values,
+ theta); // find the logarithmic function using regression
+ double target_x = theta[1] /
+ target_slope; // find the x where the slope is close to target_slope
+ return target_x;
+ }
+
+ /***
+ * Finds the mu and std parameters of the lognormal distribution from its mode
+ * and x boundaries.
+ * @param mode, the mode of the distribution.
+ * @param min_x, x lower boundary of distribution (zero percentile)
+ * @param max_x, x upper boundary of distribution (99th percentile)
+ * @param params, holds the calculated distribution parameters (mu and std) as
+ * output (params[0] = mu and params[1] = std)
+ */
+ static void
+ find_log_normal_dist_params(double mode, double min_x, double max_x,
+ double params[2]) {
+ assert(min_x < max_x && "The min_x should be smaller than max_x");
+ assert(mode >= min_x && mode < max_x &&
+ "The mode should be between min_x and max_x");
+ double max_x_normalized = max_x - min_x;
+ double mode_normalized = mode - min_x;
+ double std_dev = (-Z_P + std::sqrt(
+ Z_P * Z_P + 4 * std::log(max_x_normalized) -
+ 4 * std::log(mode_normalized))) / 2;
+ double mu = std::log(max_x_normalized) - Z_P * std_dev;
+ params[0] = mu;
+ params[1] = std_dev;
+ }
+}
${PROJECT_SOURCE_DIR}/src/os/bluestore/BlueStore.cc
${PROJECT_SOURCE_DIR}/src/os/bluestore/simple_bitmap.cc
${PROJECT_SOURCE_DIR}/src/os/bluestore/bluestore_types.cc
+ ${PROJECT_SOURCE_DIR}/src/os/bluestore/BlueStoreSlowFastCoDel.cc
${PROJECT_SOURCE_DIR}/src/os/bluestore/fastbmap_allocator_impl.cc
${PROJECT_SOURCE_DIR}/src/os/bluestore/FreelistManager.cc
${PROJECT_SOURCE_DIR}/src/os/bluestore/HybridAllocator.cc
bluestore/BlueStore.cc
bluestore/simple_bitmap.cc
bluestore/bluestore_types.cc
+ bluestore/BlueStoreSlowFastCoDel.cc
bluestore/fastbmap_allocator_impl.cc
bluestore/FreelistManager.cc
bluestore/StupidAllocator.cc
_init_logger();
cct->_conf.add_observer(this);
set_cache_shards(1);
+ if ( cct->_conf->bluestore_codel) {
+ codel = std::make_unique<BlueStoreSlowFastCoDel>(
+ cct, [this](int64_t x) mutable {
+ this->throttle.reset_kv_throttle_max(x);
+ },
+ [this]() mutable {
+ return this->throttle.get_kv_throttle_current();
+ });
+ }
}
BlueStore::~BlueStore()
"bluestore_warn_on_no_per_pool_omap",
"bluestore_warn_on_no_per_pg_omap",
"bluestore_max_defer_interval",
+ "bluestore_codel",
+ "bluestore_codel_slow_interval",
+ "bluestore_codel_fast_interval",
+ "bluestore_codel_initial_target_latency",
+ "bluestore_codel_min_target_latency",
+ "bluestore_codel_max_target_latency",
+ "bluestore_codel_throughput_latency_tradeoff",
+ "bluestore_codel_initial_budget_bytes",
+ "bluestore_codel_min_budget_bytes",
+ "bluestore_codel_budget_increment_bytes",
+ "bluestore_codel_regression_history_size",
NULL
};
return KEYS;
changed.count("bluestore_throttle_deferred_bytes") ||
changed.count("bluestore_throttle_trace_rate")) {
throttle.reset_throttle(conf);
+ if (codel) {
+ codel->reset_bluestore_budget();
+ }
}
if (changed.count("bluestore_max_defer_interval")) {
if (bdev) {
changed.count("osd_memory_expected_fragmentation")) {
_update_osd_memory_options();
}
+ if (changed.count("bluestore_codel") ||
+ changed.count("bluestore_codel_slow_interval") ||
+ changed.count("bluestore_codel_fast_interval") ||
+ changed.count("bluestore_codel_initial_target_latency") ||
+ changed.count("bluestore_codel_min_target_latency") ||
+ changed.count("bluestore_codel_max_target_latency") ||
+ changed.count("bluestore_codel_throughput_latency_tradeoff") ||
+ changed.count("bluestore_codel_initial_budget_bytes") ||
+ changed.count("bluestore_codel_min_budget_bytes") ||
+ changed.count("bluestore_codel_budget_increment_bytes") ||
+ changed.count("bluestore_codel_regression_history_size")) {
+ if (codel) {
+ codel->on_config_changed(cct);
+ }
+ }
}
void BlueStore::_set_compression()
case TransContext::STATE_KV_DONE:
throttle.log_state_latency(*txc, logger, l_bluestore_state_kv_done_lat);
+ if (codel) {
+ codel->update_from_txc_info(txc->txc_state_proc_start, txc->bytes);
+ }
if (txc->deferred_txn) {
txc->set_state(TransContext::STATE_DEFERRED_QUEUED);
_deferred_queue(txc);
logger->inc(l_bluestore_txc);
// execute (start)
+ txc->txc_state_proc_start = mono_clock::now();
_txc_state_proc(txc);
if (bdev->is_smr()) {
#include "bluestore_types.h"
#include "BlueFS.h"
#include "common/EventTrace.h"
+#include "BlueStoreSlowFastCoDel.h"
#ifdef WITH_BLKIN
#include "common/zipkin_trace.h"
uint64_t seq = 0;
ceph::mono_clock::time_point start;
ceph::mono_clock::time_point last_stamp;
+ ceph::mono_clock::time_point txc_state_proc_start;
uint64_t last_nid = 0; ///< if non-zero, highest new nid we allocated
uint64_t last_blobid = 0; ///< if non-zero, highest new blobid we allocated
trace_period_mcs = rate > 0 ? floor((1/rate) * 1000000.0) : 0;
#endif
}
+ int64_t get_kv_throttle_current() {
+ return throttle_bytes.get_current();
+ }
+ void reset_kv_throttle_max(int64_t m) {
+ throttle_bytes.reset_max(m);
+ }
} throttle;
+ std::unique_ptr<BlueStoreSlowFastCoDel> codel;
+
typedef boost::intrusive::list<
TransContext,
boost::intrusive::member_hook<
--- /dev/null
+// -*- mode:C++; tab-width:8; c-basic-offset:2; indent-tabs-mode:t -*-
+
+#include "BlueStoreSlowFastCoDel.h"
+
+#include "common/regression_utils.h"
+
+BlueStoreSlowFastCoDel::BlueStoreSlowFastCoDel(
+ CephContext *_cct,
+ std::function<void(int64_t)> _bluestore_budget_reset_callback,
+ std::function<int64_t()> _get_kv_throttle_current) :
+ fast_timer(_cct, fast_timer_lock),
+ slow_timer(_cct, slow_timer_lock),
+ bluestore_budget_reset_callback(_bluestore_budget_reset_callback),
+ get_kv_throttle_current(_get_kv_throttle_current) {
+ on_config_changed(_cct);
+}
+
+BlueStoreSlowFastCoDel::~BlueStoreSlowFastCoDel() {
+ {
+ std::lock_guard l1{fast_timer_lock};
+ fast_timer.cancel_all_events();
+ fast_timer.shutdown();
+ }
+
+ {
+ std::lock_guard l2{slow_timer_lock};
+ slow_timer.cancel_all_events();
+ slow_timer.shutdown();
+ }
+
+ regression_throughput_history.clear();
+ regression_target_latency_history.clear();
+}
+
+void BlueStoreSlowFastCoDel::update_from_txc_info(
+ ceph::mono_clock::time_point txc_start_time,
+ uint64_t txc_bytes) {
+ std::lock_guard l(register_lock);
+ ceph::mono_clock::time_point now = ceph::mono_clock::now();
+ int64_t latency = std::chrono::nanoseconds(now - txc_start_time).count();
+
+ if (activated && max_queue_length < get_kv_throttle_current()) {
+ max_queue_length = get_kv_throttle_current();
+ }
+ if (min_latency == INITIAL_LATENCY_VALUE || latency < min_latency) {
+ min_latency = latency;
+ }
+ slow_interval_txc_cnt++;
+ slow_interval_registered_bytes += txc_bytes;
+}
+
+void BlueStoreSlowFastCoDel::on_min_latency_violation() {
+ if (target_latency > 0) {
+ double diff = (double) (target_latency - min_latency);
+ auto error_ratio = std::abs(diff) / min_latency;
+ if (error_ratio > 0.5) {
+ error_ratio = 0.5;
+ }
+ bluestore_budget = std::max(bluestore_budget * (1 - error_ratio),
+ min_bluestore_budget * 1.0);
+ }
+}
+
+void BlueStoreSlowFastCoDel::on_no_violation() {
+ if (bluestore_budget < max_queue_length * 1.5) {
+ bluestore_budget = bluestore_budget + bluestore_budget_increment;
+ }
+}
+
+void BlueStoreSlowFastCoDel::on_config_changed(CephContext *cct) {
+ {
+ std::lock_guard l(register_lock);
+
+ activated = cct->_conf->bluestore_codel;
+ target_slope = cct->_conf->bluestore_codel_throughput_latency_tradeoff;
+ slow_interval = ((int64_t) cct->_conf->bluestore_codel_slow_interval) *
+ 1000 * 1000;
+ initial_fast_interval = ((int64_t)
+ cct->_conf->bluestore_codel_fast_interval) * 1000 * 1000;
+ initial_target_latency = ((int64_t)
+ cct->_conf->bluestore_codel_initial_target_latency) * 1000 * 1000;
+ min_target_latency = ((int64_t)
+ cct->_conf->bluestore_codel_min_target_latency) * 1000 * 1000;
+ max_target_latency = ((int64_t)
+ cct->_conf->bluestore_codel_max_target_latency) * 1000 * 1000;
+ initial_bluestore_budget = cct->_conf->bluestore_codel_initial_budget_bytes;
+ min_bluestore_budget = cct->_conf->bluestore_codel_min_budget_bytes;
+ bluestore_budget_increment =
+ cct->_conf->bluestore_codel_budget_increment_bytes;
+ regression_history_size =
+ cct->_conf->bluestore_codel_regression_history_size;
+
+ bluestore_budget = initial_bluestore_budget;
+ min_bluestore_budget = initial_bluestore_budget;
+ max_queue_length = min_bluestore_budget;
+ fast_interval = initial_fast_interval;
+ target_latency = initial_target_latency;
+ min_latency = INITIAL_LATENCY_VALUE;
+ slow_interval_registered_bytes = 0;
+ regression_throughput_history.clear();
+ regression_target_latency_history.clear();
+ slow_interval_start = ceph::mono_clock::zero();
+ }
+
+ {
+ std::lock_guard l1{fast_timer_lock};
+ fast_timer.cancel_all_events();
+ fast_timer.init();
+ }
+ _fast_interval_process();
+ {
+ std::lock_guard l2{slow_timer_lock};
+ slow_timer.cancel_all_events();
+ slow_timer.init();
+ }
+ _slow_interval_process();
+}
+
+void BlueStoreSlowFastCoDel::reset_bluestore_budget() {
+ if (activated) {
+ bluestore_budget = std::max(min_bluestore_budget, bluestore_budget);
+ bluestore_budget_reset_callback(bluestore_budget);
+ }
+}
+
+void BlueStoreSlowFastCoDel::_fast_interval_process() {
+ std::lock_guard l(register_lock);
+ if (target_latency != INITIAL_LATENCY_VALUE &&
+ min_latency != INITIAL_LATENCY_VALUE) {
+ if (activated) {
+ if (_check_latency_violation()) {
+ // min latency violation
+ violation_count++;
+ _update_interval();
+ on_min_latency_violation(); // handle the violation
+ } else {
+ // no latency violation
+ violation_count = 0;
+ fast_interval = initial_fast_interval;
+ on_no_violation();
+ }
+ bluestore_budget = std::max(min_bluestore_budget, bluestore_budget);
+ bluestore_budget_reset_callback(bluestore_budget);
+ }
+
+ // reset interval
+ min_latency = INITIAL_LATENCY_VALUE;
+
+ on_fast_interval_finished();
+ }
+
+ auto codel_ctx = new LambdaContext(
+ [this](int r) {
+ _fast_interval_process();
+ });
+ auto interval_duration = std::chrono::nanoseconds(fast_interval);
+ fast_timer.add_event_after(interval_duration, codel_ctx);
+}
+
+void BlueStoreSlowFastCoDel::_slow_interval_process() {
+ std::lock_guard l(register_lock);
+ ceph::mono_clock::time_point now = ceph::mono_clock::now();
+ if (activated && !ceph::mono_clock::is_zero(slow_interval_start)
+ && slow_interval_txc_cnt > 0) {
+ double time_sec = nanosec_to_sec(
+ std::chrono::nanoseconds(now - slow_interval_start).count());
+
+ double slow_interval_throughput =
+ (slow_interval_registered_bytes * 1.0) / time_sec;
+ slow_interval_throughput = slow_interval_throughput / (1024.0 * 1024.0);
+ regression_target_latency_history.push_back(
+ nanosec_to_millisec(target_latency));
+ regression_throughput_history.push_back(slow_interval_throughput);
+ if (regression_target_latency_history.size() > regression_history_size) {
+ regression_target_latency_history.erase(
+ regression_target_latency_history.begin());
+ regression_throughput_history.erase(
+ regression_throughput_history.begin());
+ }
+ std::vector<double> targets;
+ std::vector<double> throughputs;
+ double target_ms = nanosec_to_millisec(initial_target_latency);
+ // If there is sufficient number of points, use the regression to find the
+ // target_ms. Otherwise, target_ms will be initial_target_latency
+ if (regression_target_latency_history.size() >= regression_history_size) {
+ target_ms = ceph::find_slope_on_curve(
+ regression_target_latency_history,
+ regression_throughput_history,
+ target_slope);
+ }
+
+ target_latency_without_noise = millisec_to_nanosec(target_ms);
+ target_latency_without_noise = std::max(target_latency_without_noise,
+ min_target_latency);
+ target_latency_without_noise = std::min(target_latency_without_noise,
+ max_target_latency);
+ target_ms = nanosec_to_millisec(target_latency_without_noise);
+
+ // add log_normal noise
+ unsigned seed = std::chrono::system_clock::now().time_since_epoch().count();
+ std::default_random_engine generator(seed);
+ double dist_params[2];
+ double rnd_std_dev = 5;
+ ceph::find_log_normal_dist_params(
+ target_ms,
+ nanosec_to_millisec(min_target_latency),
+ target_ms * rnd_std_dev,
+ dist_params);
+ std::lognormal_distribution<double> distribution(dist_params[0],
+ dist_params[1]);
+
+ target_latency = millisec_to_nanosec(distribution(generator));
+ target_latency += min_target_latency;
+
+ if (target_latency < millisec_to_nanosec(target_ms)) {
+ std::uniform_real_distribution<> distr(0, 0.5);
+ target_latency = target_latency +
+ (target_latency - millisec_to_nanosec(target_ms)) *
+ distr(generator);
+ }
+
+ if (target_latency != INITIAL_LATENCY_VALUE) {
+ target_latency = std::max(target_latency, min_target_latency);
+ target_latency = std::min(target_latency, max_target_latency);
+ }
+
+ on_slow_interval_finished();
+ }
+
+ slow_interval_start = ceph::mono_clock::now();
+ slow_interval_registered_bytes = 0;
+ slow_interval_txc_cnt = 0;
+ max_queue_length = min_bluestore_budget;
+
+ auto codel_ctx = new LambdaContext(
+ [this](int r) {
+ _slow_interval_process();
+ });
+ auto interval_duration = std::chrono::nanoseconds(slow_interval);
+ slow_timer.add_event_after(interval_duration, codel_ctx);
+}
+
+
+/**
+* check if the min latency violate the target
+* @return true if min latency violate the target, false otherwise
+*/
+bool BlueStoreSlowFastCoDel::_check_latency_violation() {
+ if (target_latency != INITIAL_LATENCY_VALUE &&
+ min_latency != INITIAL_LATENCY_VALUE) {
+ if (min_latency > target_latency) {
+ return true;
+ }
+ }
+ return false;
+}
+
+void BlueStoreSlowFastCoDel::_update_interval() {
+ auto sqrt = (int) std::round(std::sqrt(violation_count));
+ fast_interval = initial_fast_interval / sqrt;
+ if (fast_interval <= 0) {
+ fast_interval = 1000;
+ }
+}
+
+int64_t BlueStoreSlowFastCoDel::get_bluestore_budget() {
+ return bluestore_budget;
+}
+
+int64_t BlueStoreSlowFastCoDel::get_target_latency() {
+ return target_latency;
+}
--- /dev/null
+// -*- mode:C++; tab-width:8; c-basic-offset:2; indent-tabs-mode:t -*-
+
+#pragma once
+
+#include <iostream>
+
+#include "include/Context.h"
+#include "common/Timer.h"
+#include "common/ceph_time.h"
+
+class BlueStoreSlowFastCoDel {
+public:
+ BlueStoreSlowFastCoDel(
+ CephContext *_cct,
+ std::function<void(int64_t)> _bluestore_budget_reset_callback,
+ std::function<int64_t()> _get_kv_throttle_current);
+
+ virtual ~BlueStoreSlowFastCoDel();
+
+ void on_config_changed(CephContext *cct);
+
+ void reset_bluestore_budget();
+
+ void update_from_txc_info(
+ ceph::mono_clock::time_point txc_start_time,
+ uint64_t txc_bytes);
+
+ int64_t get_bluestore_budget();
+
+ int64_t get_target_latency();
+
+ bool is_activated();
+
+protected:
+ static const int64_t INITIAL_LATENCY_VALUE = -1;
+
+ /* config values */
+ // Config value 'bluestore_codel',true if SlowFastCodel is activated
+ bool activated = false;
+ // Config value 'bluestore_codel_fast_interval', Initial interval for fast loop
+ int64_t initial_fast_interval = INITIAL_LATENCY_VALUE;
+ // Config value 'bluestore_codel_initial_target_latency', Initial target latency
+ // to start the algorithm
+ int64_t initial_target_latency = INITIAL_LATENCY_VALUE;
+ // Config value 'bluestore_codel_slow_interval', the interval for the slow loop
+ int64_t slow_interval = INITIAL_LATENCY_VALUE;
+ // Config value 'bluestore_codel_min_target_latency', min possible value for target
+ int64_t min_target_latency = INITIAL_LATENCY_VALUE; // in ns
+ // Config value 'bluestore_codel_max_target_latency', max possible value for target
+ int64_t max_target_latency = INITIAL_LATENCY_VALUE; // in ns
+ // Config value 'bluestore_codel_throughput_latency_tradeoff', define the
+ // tradeoff between throughput and latency (MB/s loss for every 1ms latency drop)
+ double target_slope = 5;
+ // Config value 'bluestore_codel_regression_history_size', regression history size
+ int64_t regression_history_size = 100;
+ // Config value 'bluestore_codel_min_budget_bytes', the minimum bluestore
+ // throttle budget
+ int64_t min_bluestore_budget = 102400;
+ // Config value 'bluestore_codel_initial_budget_bytes', the initial bluestore
+ // throttle budget
+ int64_t initial_bluestore_budget = 102400;
+ // Config value 'bluestore_codel_budget_increment_bytes', the increment size
+ // for opening the bluestore throttle
+ int64_t bluestore_budget_increment = 102400;
+
+ /* internal state variables */
+ // current interval for the fast loop
+ int64_t fast_interval = INITIAL_LATENCY_VALUE;
+ // current target latency that fast loop is using
+ int64_t target_latency = INITIAL_LATENCY_VALUE;
+ int64_t target_latency_without_noise = INITIAL_LATENCY_VALUE;
+ // min latency in the current fast interval
+ int64_t min_latency = INITIAL_LATENCY_VALUE;
+ int64_t violation_count = 0;
+ ceph::mutex fast_timer_lock = ceph::make_mutex("CoDel::fast_timer_lock");
+ ceph::mutex slow_timer_lock = ceph::make_mutex("CoDel::slow_timer_lock");
+ ceph::mutex register_lock = ceph::make_mutex("CoDel::register_lock");
+ SafeTimer fast_timer; // fast loop timer
+ SafeTimer slow_timer; // slow loop timer
+ // marks the start of the current slow interval
+ ceph::mono_clock::time_point slow_interval_start = ceph::mono_clock::zero();
+ // amount of bytes that has been processed in current slow interval
+ int64_t slow_interval_registered_bytes = 0;
+ // number of transactions that has been processed in current slow interval
+ int64_t slow_interval_txc_cnt = 0;
+ // target latency history for regression
+ std::vector<double> regression_target_latency_history;
+ // throughput history for regression
+ std::vector<double> regression_throughput_history;
+ int64_t bluestore_budget = 102400; // current bluestore throttle budget
+ // maximum amount of inflight data in current slow interval
+ int64_t max_queue_length = 102400;
+ std::function<void(int64_t)> bluestore_budget_reset_callback;
+ std::function<int64_t(void)> get_kv_throttle_current;
+
+ void on_min_latency_violation();
+
+ void on_no_violation();
+
+ virtual void on_fast_interval_finished() {}
+
+ virtual void on_slow_interval_finished() {}
+
+private:
+
+ bool _check_latency_violation();
+
+ void _update_interval();
+
+ void _fast_interval_process();
+
+ void _slow_interval_process();
+
+ template<typename T>
+ double millisec_to_nanosec(T ms) {
+ return ms * 1000.0 * 1000.0;
+ }
+
+ template<typename T>
+ double nanosec_to_millisec(T ns) {
+ return ns / (1000.0 * 1000.0);
+ }
+
+ template<typename T>
+ double nanosec_to_sec(T ns) {
+ return ns / (1000.0 * 1000.0 * 1000.0);
+ }
+};
projects / ceph.git / commitdiff