10225501448 李度 10225101546 陈胤遒 10215501422 高宇菲
選択できるのは25トピックまでです。 トピックは、先頭が英数字で、英数字とダッシュ('-')を使用した35文字以内のものにしてください。

139 行
4.6 KiB

// 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.
#include <math.h>
#include <stdio.h>
#include "port/port.h"
#include "util/histogram.h"
namespace leveldb {
const double Histogram::kBucketLimit[kNumBuckets] = {
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, 1200000000, 1400000000, 1600000000, 1800000000, 2000000000,
2500000000.0, 3000000000.0, 3500000000.0, 4000000000.0, 4500000000.0,
5000000000.0, 6000000000.0, 7000000000.0, 8000000000.0, 9000000000.0,
1e200,
};
void Histogram::Clear() {
min_ = kBucketLimit[kNumBuckets-1];
max_ = 0;
num_ = 0;
sum_ = 0;
sum_squares_ = 0;
for (int i = 0; i < kNumBuckets; i++) {
buckets_[i] = 0;
}
}
void Histogram::Add(double value) {
// Linear search is fast enough for our usage in db_bench
int b = 0;
while (b < kNumBuckets - 1 && kBucketLimit[b] <= value) {
b++;
}
buckets_[b] += 1.0;
if (min_ > value) min_ = value;
if (max_ < value) max_ = value;
num_++;
sum_ += value;
sum_squares_ += (value * value);
}
void Histogram::Merge(const Histogram& other) {
if (other.min_ < min_) min_ = other.min_;
if (other.max_ > max_) max_ = other.max_;
num_ += other.num_;
sum_ += other.sum_;
sum_squares_ += other.sum_squares_;
for (int b = 0; b < kNumBuckets; b++) {
buckets_[b] += other.buckets_[b];
}
}
double Histogram::Median() const {
return Percentile(50.0);
}
double Histogram::Percentile(double p) const {
double threshold = num_ * (p / 100.0);
double sum = 0;
for (int b = 0; b < kNumBuckets; b++) {
sum += buckets_[b];
if (sum >= threshold) {
// Scale linearly within this bucket
double left_point = (b == 0) ? 0 : kBucketLimit[b-1];
double right_point = kBucketLimit[b];
double left_sum = sum - buckets_[b];
double right_sum = sum;
double pos = (threshold - left_sum) / (right_sum - left_sum);
double r = left_point + (right_point - left_point) * pos;
if (r < min_) r = min_;
if (r > max_) r = max_;
return r;
}
}
return max_;
}
double Histogram::Average() const {
if (num_ == 0.0) return 0;
return sum_ / num_;
}
double Histogram::StandardDeviation() const {
if (num_ == 0.0) return 0;
double variance = (sum_squares_ * num_ - sum_ * sum_) / (num_ * num_);
return sqrt(variance);
}
std::string Histogram::ToString() const {
std::string r;
char buf[200];
snprintf(buf, sizeof(buf),
"Count: %.0f Average: %.4f StdDev: %.2f\n",
num_, Average(), StandardDeviation());
r.append(buf);
snprintf(buf, sizeof(buf),
"Min: %.4f Median: %.4f Max: %.4f\n",
(num_ == 0.0 ? 0.0 : min_), Median(), max_);
r.append(buf);
r.append("------------------------------------------------------\n");
const double mult = 100.0 / num_;
double sum = 0;
for (int b = 0; b < kNumBuckets; b++) {
if (buckets_[b] <= 0.0) continue;
sum += buckets_[b];
snprintf(buf, sizeof(buf),
"[ %7.0f, %7.0f ) %7.0f %7.3f%% %7.3f%% ",
((b == 0) ? 0.0 : kBucketLimit[b-1]), // left
kBucketLimit[b], // right
buckets_[b], // count
mult * buckets_[b], // percentage
mult * sum); // cumulative percentage
r.append(buf);
// Add hash marks based on percentage; 20 marks for 100%.
int marks = static_cast<int>(20*(buckets_[b] / num_) + 0.5);
r.append(marks, '#');
r.push_back('\n');
}
return r;
}
}