10a12b2a6f
Summary: Closes https://github.com/facebook/rocksdb/pull/2226 Differential Revision: D4967547 Pulled By: siying fbshipit-source-id: dd3b58ae1e7a106ab6bb6f37ab5c88575b125ab4
294 lines
10 KiB
C++
294 lines
10 KiB
C++
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under the BSD-style license found in the
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// LICENSE file in the root directory of this source tree. An additional grant
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// of patent rights can be found in the PATENTS file in the same directory.
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// This source code is also licensed under the GPLv2 license found in the
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// COPYING file in the root directory of this source tree.
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//
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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#ifndef __STDC_FORMAT_MACROS
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#define __STDC_FORMAT_MACROS
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#endif
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#include "monitoring/histogram.h"
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#include <inttypes.h>
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#include <cassert>
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#include <math.h>
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#include <stdio.h>
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#include "port/port.h"
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namespace rocksdb {
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HistogramBucketMapper::HistogramBucketMapper()
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:
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// Add newer bucket index here.
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// Should be always added in sorted order.
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// If you change this, you also need to change
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// size of array buckets_ in HistogramImpl
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bucketValues_(
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{1, 2, 3, 4, 5, 6,
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7, 8, 9, 10, 12, 14,
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16, 18, 20, 25, 30, 35,
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40, 45, 50, 60, 70, 80,
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90, 100, 120, 140, 160, 180,
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200, 250, 300, 350, 400, 450,
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500, 600, 700, 800, 900, 1000,
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1200, 1400, 1600, 1800, 2000, 2500,
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3000, 3500, 4000, 4500, 5000, 6000,
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7000, 8000, 9000, 10000, 12000, 14000,
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16000, 18000, 20000, 25000, 30000, 35000,
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40000, 45000, 50000, 60000, 70000, 80000,
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90000, 100000, 120000, 140000, 160000, 180000,
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200000, 250000, 300000, 350000, 400000, 450000,
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500000, 600000, 700000, 800000, 900000, 1000000,
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1200000, 1400000, 1600000, 1800000, 2000000, 2500000,
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3000000, 3500000, 4000000, 4500000, 5000000, 6000000,
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7000000, 8000000, 9000000, 10000000, 12000000, 14000000,
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16000000, 18000000, 20000000, 25000000, 30000000, 35000000,
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40000000, 45000000, 50000000, 60000000, 70000000, 80000000,
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90000000, 100000000, 120000000, 140000000, 160000000, 180000000,
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200000000, 250000000, 300000000, 350000000, 400000000, 450000000,
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500000000, 600000000, 700000000, 800000000, 900000000, 1000000000}),
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maxBucketValue_(bucketValues_.back()),
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minBucketValue_(bucketValues_.front()) {
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for (size_t i =0; i < bucketValues_.size(); ++i) {
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valueIndexMap_[bucketValues_[i]] = i;
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}
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}
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size_t HistogramBucketMapper::IndexForValue(const uint64_t value) const {
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if (value >= maxBucketValue_) {
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return bucketValues_.size() - 1;
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} else if ( value >= minBucketValue_ ) {
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std::map<uint64_t, uint64_t>::const_iterator lowerBound =
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valueIndexMap_.lower_bound(value);
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if (lowerBound != valueIndexMap_.end()) {
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return static_cast<size_t>(lowerBound->second);
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} else {
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return 0;
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}
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} else {
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return 0;
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}
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}
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namespace {
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const HistogramBucketMapper bucketMapper;
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}
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HistogramStat::HistogramStat()
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: num_buckets_(bucketMapper.BucketCount()) {
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assert(num_buckets_ == sizeof(buckets_) / sizeof(*buckets_));
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Clear();
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}
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void HistogramStat::Clear() {
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min_.store(bucketMapper.LastValue(), std::memory_order_relaxed);
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max_.store(0, std::memory_order_relaxed);
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num_.store(0, std::memory_order_relaxed);
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sum_.store(0, std::memory_order_relaxed);
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sum_squares_.store(0, std::memory_order_relaxed);
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for (unsigned int b = 0; b < num_buckets_; b++) {
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buckets_[b].store(0, std::memory_order_relaxed);
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}
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};
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bool HistogramStat::Empty() const { return num() == 0; }
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void HistogramStat::Add(uint64_t value) {
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// This function is designed to be lock free, as it's in the critical path
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// of any operation. Each individual value is atomic and the order of updates
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// by concurrent threads is tolerable.
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const size_t index = bucketMapper.IndexForValue(value);
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assert(index < num_buckets_);
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buckets_[index].fetch_add(1, std::memory_order_relaxed);
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uint64_t old_min = min();
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while (value < old_min && !min_.compare_exchange_weak(old_min, value)) {}
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uint64_t old_max = max();
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while (value > old_max && !max_.compare_exchange_weak(old_max, value)) {}
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num_.fetch_add(1, std::memory_order_relaxed);
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sum_.fetch_add(value, std::memory_order_relaxed);
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sum_squares_.fetch_add(value * value, std::memory_order_relaxed);
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}
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void HistogramStat::Merge(const HistogramStat& other) {
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// This function needs to be performned with the outer lock acquired
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// However, atomic operation on every member is still need, since Add()
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// requires no lock and value update can still happen concurrently
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uint64_t old_min = min();
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uint64_t other_min = other.min();
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while (other_min < old_min &&
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!min_.compare_exchange_weak(old_min, other_min)) {}
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uint64_t old_max = max();
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uint64_t other_max = other.max();
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while (other_max > old_max &&
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!max_.compare_exchange_weak(old_max, other_max)) {}
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num_.fetch_add(other.num(), std::memory_order_relaxed);
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sum_.fetch_add(other.sum(), std::memory_order_relaxed);
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sum_squares_.fetch_add(other.sum_squares(), std::memory_order_relaxed);
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for (unsigned int b = 0; b < num_buckets_; b++) {
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buckets_[b].fetch_add(other.bucket_at(b), std::memory_order_relaxed);
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}
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}
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double HistogramStat::Median() const {
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return Percentile(50.0);
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}
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double HistogramStat::Percentile(double p) const {
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double threshold = num() * (p / 100.0);
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uint64_t cumulative_sum = 0;
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for (unsigned int b = 0; b < num_buckets_; b++) {
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uint64_t bucket_value = bucket_at(b);
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cumulative_sum += bucket_value;
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if (cumulative_sum >= threshold) {
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// Scale linearly within this bucket
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uint64_t left_point = (b == 0) ? 0 : bucketMapper.BucketLimit(b-1);
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uint64_t right_point = bucketMapper.BucketLimit(b);
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uint64_t left_sum = cumulative_sum - bucket_value;
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uint64_t right_sum = cumulative_sum;
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double pos = 0;
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uint64_t right_left_diff = right_sum - left_sum;
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if (right_left_diff != 0) {
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pos = (threshold - left_sum) / right_left_diff;
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}
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double r = left_point + (right_point - left_point) * pos;
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uint64_t cur_min = min();
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uint64_t cur_max = max();
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if (r < cur_min) r = static_cast<double>(cur_min);
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if (r > cur_max) r = static_cast<double>(cur_max);
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return r;
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}
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}
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return static_cast<double>(max());
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}
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double HistogramStat::Average() const {
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uint64_t cur_num = num();
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uint64_t cur_sum = sum();
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if (cur_num == 0) return 0;
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return static_cast<double>(cur_sum) / static_cast<double>(cur_num);
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}
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double HistogramStat::StandardDeviation() const {
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uint64_t cur_num = num();
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uint64_t cur_sum = sum();
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uint64_t cur_sum_squares = sum_squares();
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if (cur_num == 0) return 0;
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double variance =
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static_cast<double>(cur_sum_squares * cur_num - cur_sum * cur_sum) /
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static_cast<double>(cur_num * cur_num);
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return sqrt(variance);
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}
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std::string HistogramStat::ToString() const {
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uint64_t cur_num = num();
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std::string r;
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char buf[1650];
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snprintf(buf, sizeof(buf),
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"Count: %" PRIu64 " Average: %.4f StdDev: %.2f\n",
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cur_num, Average(), StandardDeviation());
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r.append(buf);
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snprintf(buf, sizeof(buf),
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"Min: %" PRIu64 " Median: %.4f Max: %" PRIu64 "\n",
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(cur_num == 0 ? 0 : min()), Median(), (cur_num == 0 ? 0 : max()));
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r.append(buf);
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snprintf(buf, sizeof(buf),
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"Percentiles: "
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"P50: %.2f P75: %.2f P99: %.2f P99.9: %.2f P99.99: %.2f\n",
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Percentile(50), Percentile(75), Percentile(99), Percentile(99.9),
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Percentile(99.99));
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r.append(buf);
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r.append("------------------------------------------------------\n");
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const double mult = 100.0 / cur_num;
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uint64_t cumulative_sum = 0;
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for (unsigned int b = 0; b < num_buckets_; b++) {
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uint64_t bucket_value = bucket_at(b);
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if (bucket_value <= 0.0) continue;
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cumulative_sum += bucket_value;
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snprintf(buf, sizeof(buf),
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"[ %7" PRIu64 ", %7" PRIu64 " ) %8" PRIu64 " %7.3f%% %7.3f%% ",
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(b == 0) ? 0 : bucketMapper.BucketLimit(b-1), // left
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bucketMapper.BucketLimit(b), // right
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bucket_value, // count
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(mult * bucket_value), // percentage
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(mult * cumulative_sum)); // cumulative percentage
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r.append(buf);
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// Add hash marks based on percentage; 20 marks for 100%.
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size_t marks = static_cast<size_t>(mult * bucket_value / 5 + 0.5);
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r.append(marks, '#');
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r.push_back('\n');
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}
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return r;
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}
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void HistogramStat::Data(HistogramData * const data) const {
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assert(data);
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data->median = Median();
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data->percentile95 = Percentile(95);
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data->percentile99 = Percentile(99);
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data->max = static_cast<double>(max());
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data->average = Average();
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data->standard_deviation = StandardDeviation();
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}
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void HistogramImpl::Clear() {
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std::lock_guard<std::mutex> lock(mutex_);
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stats_.Clear();
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}
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bool HistogramImpl::Empty() const {
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return stats_.Empty();
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}
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void HistogramImpl::Add(uint64_t value) {
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stats_.Add(value);
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}
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void HistogramImpl::Merge(const Histogram& other) {
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if (strcmp(Name(), other.Name()) == 0) {
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Merge(dynamic_cast<const HistogramImpl&>(other));
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}
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}
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void HistogramImpl::Merge(const HistogramImpl& other) {
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std::lock_guard<std::mutex> lock(mutex_);
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stats_.Merge(other.stats_);
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}
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double HistogramImpl::Median() const {
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return stats_.Median();
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}
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double HistogramImpl::Percentile(double p) const {
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return stats_.Percentile(p);
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}
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double HistogramImpl::Average() const {
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return stats_.Average();
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}
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double HistogramImpl::StandardDeviation() const {
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return stats_.StandardDeviation();
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}
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std::string HistogramImpl::ToString() const {
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return stats_.ToString();
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}
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void HistogramImpl::Data(HistogramData * const data) const {
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stats_.Data(data);
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}
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} // namespace levedb
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