作者: 韩晨旭 10225101440 李畅 10225102463
25개 이상의 토픽을 선택하실 수 없습니다. Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 

272 lines
5.2 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 "util/histogram.h"
#include <cmath>
#include <cstdio>
#include "port/port.h"
namespace leveldb {
const double Histogram::kBucketLimit[kNumBuckets] = {
1,
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20000,
25000,
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35000,
40000,
45000,
50000,
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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];
std::snprintf(buf, sizeof(buf), "Count: %.0f Average: %.4f StdDev: %.2f\n",
num_, Average(), StandardDeviation());
r.append(buf);
std::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];
std::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;
}
} // namespace leveldb