Revision 48fd619a47c17d044aa9d36adab55659fcac1985 authored by Adam Retter on 20 October 2016, 01:21:22 UTC, committed by Yueh-Hsuan Chiang on 20 October 2016, 01:21:22 UTC
* [bugfix] Make sure the Native Library is initialized. Closes https://github.com/facebook/rocksdb/issues/989 * [bugfix] Just load the native libraries once
1 parent 48e4e84
histogram.cc
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree. An additional grant
// of patent rights can be found in the PATENTS file in the same directory.
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS
#endif
#include <inttypes.h>
#include <cassert>
#include <math.h>
#include <stdio.h>
#include "util/histogram.h"
#include "port/port.h"
namespace rocksdb {
HistogramBucketMapper::HistogramBucketMapper()
:
// Add newer bucket index here.
// Should be always added in sorted order.
// If you change this, you also need to change
// size of array buckets_ in HistogramImpl
bucketValues_(
{1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 12, 14,
16, 18, 20, 25, 30, 35,
40, 45, 50, 60, 70, 80,
90, 100, 120, 140, 160, 180,
200, 250, 300, 350, 400, 450,
500, 600, 700, 800, 900, 1000,
1200, 1400, 1600, 1800, 2000, 2500,
3000, 3500, 4000, 4500, 5000, 6000,
7000, 8000, 9000, 10000, 12000, 14000,
16000, 18000, 20000, 25000, 30000, 35000,
40000, 45000, 50000, 60000, 70000, 80000,
90000, 100000, 120000, 140000, 160000, 180000,
200000, 250000, 300000, 350000, 400000, 450000,
500000, 600000, 700000, 800000, 900000, 1000000,
1200000, 1400000, 1600000, 1800000, 2000000, 2500000,
3000000, 3500000, 4000000, 4500000, 5000000, 6000000,
7000000, 8000000, 9000000, 10000000, 12000000, 14000000,
16000000, 18000000, 20000000, 25000000, 30000000, 35000000,
40000000, 45000000, 50000000, 60000000, 70000000, 80000000,
90000000, 100000000, 120000000, 140000000, 160000000, 180000000,
200000000, 250000000, 300000000, 350000000, 400000000, 450000000,
500000000, 600000000, 700000000, 800000000, 900000000, 1000000000}),
maxBucketValue_(bucketValues_.back()),
minBucketValue_(bucketValues_.front()) {
for (size_t i =0; i < bucketValues_.size(); ++i) {
valueIndexMap_[bucketValues_[i]] = i;
}
}
size_t HistogramBucketMapper::IndexForValue(const uint64_t value) const {
if (value >= maxBucketValue_) {
return bucketValues_.size() - 1;
} else if ( value >= minBucketValue_ ) {
std::map<uint64_t, uint64_t>::const_iterator lowerBound =
valueIndexMap_.lower_bound(value);
if (lowerBound != valueIndexMap_.end()) {
return static_cast<size_t>(lowerBound->second);
} else {
return 0;
}
} else {
return 0;
}
}
namespace {
const HistogramBucketMapper bucketMapper;
}
HistogramStat::HistogramStat()
: num_buckets_(bucketMapper.BucketCount()) {
assert(num_buckets_ == sizeof(buckets_) / sizeof(*buckets_));
Clear();
}
void HistogramStat::Clear() {
min_.store(bucketMapper.LastValue(), std::memory_order_relaxed);
max_.store(0, std::memory_order_relaxed);
num_.store(0, std::memory_order_relaxed);
sum_.store(0, std::memory_order_relaxed);
sum_squares_.store(0, std::memory_order_relaxed);
for (unsigned int b = 0; b < num_buckets_; b++) {
buckets_[b].store(0, std::memory_order_relaxed);
}
};
bool HistogramStat::Empty() const { return num() == 0; }
void HistogramStat::Add(uint64_t value) {
// This function is designed to be lock free, as it's in the critical path
// of any operation. Each individual value is atomic and the order of updates
// by concurrent threads is tolerable.
const size_t index = bucketMapper.IndexForValue(value);
assert(index < num_buckets_);
buckets_[index].fetch_add(1, std::memory_order_relaxed);
uint64_t old_min = min();
while (value < old_min && !min_.compare_exchange_weak(old_min, value)) {}
uint64_t old_max = max();
while (value > old_max && !max_.compare_exchange_weak(old_max, value)) {}
num_.fetch_add(1, std::memory_order_relaxed);
sum_.fetch_add(value, std::memory_order_relaxed);
sum_squares_.fetch_add(value * value, std::memory_order_relaxed);
}
void HistogramStat::Merge(const HistogramStat& other) {
// This function needs to be performned with the outer lock acquired
// However, atomic operation on every member is still need, since Add()
// requires no lock and value update can still happen concurrently
uint64_t old_min = min();
uint64_t other_min = other.min();
while (other_min < old_min &&
!min_.compare_exchange_weak(old_min, other_min)) {}
uint64_t old_max = max();
uint64_t other_max = other.max();
while (other_max > old_max &&
!max_.compare_exchange_weak(old_max, other_max)) {}
num_.fetch_add(other.num(), std::memory_order_relaxed);
sum_.fetch_add(other.sum(), std::memory_order_relaxed);
sum_squares_.fetch_add(other.sum_squares(), std::memory_order_relaxed);
for (unsigned int b = 0; b < num_buckets_; b++) {
buckets_[b].fetch_add(other.bucket_at(b), std::memory_order_relaxed);
}
}
double HistogramStat::Median() const {
return Percentile(50.0);
}
double HistogramStat::Percentile(double p) const {
double threshold = num() * (p / 100.0);
uint64_t cumulative_sum = 0;
for (unsigned int b = 0; b < num_buckets_; b++) {
uint64_t bucket_value = bucket_at(b);
cumulative_sum += bucket_value;
if (cumulative_sum >= threshold) {
// Scale linearly within this bucket
uint64_t left_point = (b == 0) ? 0 : bucketMapper.BucketLimit(b-1);
uint64_t right_point = bucketMapper.BucketLimit(b);
uint64_t left_sum = cumulative_sum - bucket_value;
uint64_t right_sum = cumulative_sum;
double pos = 0;
uint64_t right_left_diff = right_sum - left_sum;
if (right_left_diff != 0) {
pos = (threshold - left_sum) / right_left_diff;
}
double r = left_point + (right_point - left_point) * pos;
uint64_t cur_min = min();
uint64_t cur_max = max();
if (r < cur_min) r = static_cast<double>(cur_min);
if (r > cur_max) r = static_cast<double>(cur_max);
return r;
}
}
return static_cast<double>(max());
}
double HistogramStat::Average() const {
uint64_t cur_num = num();
uint64_t cur_sum = sum();
if (cur_num == 0) return 0;
return static_cast<double>(cur_sum) / static_cast<double>(cur_num);
}
double HistogramStat::StandardDeviation() const {
uint64_t cur_num = num();
uint64_t cur_sum = sum();
uint64_t cur_sum_squares = sum_squares();
if (cur_num == 0) return 0;
double variance =
static_cast<double>(cur_sum_squares * cur_num - cur_sum * cur_sum) /
static_cast<double>(cur_num * cur_num);
return sqrt(variance);
}
std::string HistogramStat::ToString() const {
uint64_t cur_num = num();
std::string r;
char buf[200];
snprintf(buf, sizeof(buf),
"Count: %" PRIu64 " Average: %.4f StdDev: %.2f\n",
cur_num, Average(), StandardDeviation());
r.append(buf);
snprintf(buf, sizeof(buf),
"Min: %" PRIu64 " Median: %.4f Max: %" PRIu64 "\n",
(cur_num == 0 ? 0 : min()), Median(), (cur_num == 0 ? 0 : max()));
r.append(buf);
snprintf(buf, sizeof(buf),
"Percentiles: "
"P50: %.2f P75: %.2f P99: %.2f P99.9: %.2f P99.99: %.2f\n",
Percentile(50), Percentile(75), Percentile(99), Percentile(99.9),
Percentile(99.99));
r.append(buf);
r.append("------------------------------------------------------\n");
const double mult = 100.0 / cur_num;
uint64_t cumulative_sum = 0;
for (unsigned int b = 0; b < num_buckets_; b++) {
uint64_t bucket_value = bucket_at(b);
if (bucket_value <= 0.0) continue;
cumulative_sum += bucket_value;
snprintf(buf, sizeof(buf),
"[ %7" PRIu64 ", %7" PRIu64 " ) %8" PRIu64 " %7.3f%% %7.3f%% ",
(b == 0) ? 0 : bucketMapper.BucketLimit(b-1), // left
bucketMapper.BucketLimit(b), // right
bucket_value, // count
(mult * bucket_value), // percentage
(mult * cumulative_sum)); // cumulative percentage
r.append(buf);
// Add hash marks based on percentage; 20 marks for 100%.
size_t marks = static_cast<size_t>(mult * bucket_value / 5 + 0.5);
r.append(marks, '#');
r.push_back('\n');
}
return r;
}
void HistogramStat::Data(HistogramData * const data) const {
assert(data);
data->median = Median();
data->percentile95 = Percentile(95);
data->percentile99 = Percentile(99);
data->average = Average();
data->standard_deviation = StandardDeviation();
}
void HistogramImpl::Clear() {
std::lock_guard<std::mutex> lock(mutex_);
stats_.Clear();
}
bool HistogramImpl::Empty() const {
return stats_.Empty();
}
void HistogramImpl::Add(uint64_t value) {
stats_.Add(value);
}
void HistogramImpl::Merge(const Histogram& other) {
if (strcmp(Name(), other.Name()) == 0) {
Merge(dynamic_cast<const HistogramImpl&>(other));
}
}
void HistogramImpl::Merge(const HistogramImpl& other) {
std::lock_guard<std::mutex> lock(mutex_);
stats_.Merge(other.stats_);
}
double HistogramImpl::Median() const {
return stats_.Median();
}
double HistogramImpl::Percentile(double p) const {
return stats_.Percentile(p);
}
double HistogramImpl::Average() const {
return stats_.Average();
}
double HistogramImpl::StandardDeviation() const {
return stats_.StandardDeviation();
}
std::string HistogramImpl::ToString() const {
return stats_.ToString();
}
void HistogramImpl::Data(HistogramData * const data) const {
stats_.Data(data);
}
} // namespace levedb
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