WebRTC源码分析--RateTracker
RateTracker主要作用是求最近一段时间间隔内的平均速率，先看它的定义：
class RateTracker {
public:
RateTracker(int64_t bucket_milliseconds, size_t bucket_count);
virtual ~RateTracker();
// Computes the average rate over the most recent interval_milliseconds,
// or if the first sample was added within this period, computes the rate
// since the first sample was added.
double ComputeRateForInterval(int64_t interval_milliseconds) const;
// Computes the average rate over the rate tracker's recording interval
// of bucket_milliseconds * bucket_count.
double ComputeRate() const {
return ComputeRateForInterval(bucket_milliseconds_ *
static_cast<int64_t>(bucket_count_));
}
// Computes the average rate since the first sample was added to the
// rate tracker.
double ComputeTotalRate() const;
// The total number of samples added.
int64_t TotalSampleCount() const;
// Reads the current time in order to determine the appropriate bucket for
// these samples, and increments the count for that bucket by sample_count.
void AddSamples(int64_t sample_count);
protected:
// overrideable for tests
virtual int64_t Time() const;
private:
void EnsureInitialized();
size_t NextBucketIndex(size_t bucket_index) const;
const int64_t bucket_milliseconds_;
const size_t bucket_count_;
int64_t* sample_buckets_;
size_t total_sample_count_;
size_t current_bucket_;
int64_t bucket_start_time_milliseconds_;
int64_t initialization_time_milliseconds_;
};
构造函数
RateTracker::RateTracker(int64_t bucket_milliseconds, size_t bucket_count)
: bucket_milliseconds_(bucket_milliseconds),
bucket_count_(bucket_count),
sample_buckets_(new in// 进行初始化
void RateTracker::EnsureInitialized() {
if (bucket_start_time_milliseconds_ == kTimeUnset) {
initialization_time_milliseconds_ = Time();
bucket_start_time_milliseconds_ = initialization_time_milliseconds_;
// 当前桶的序号
current_bucket_ = 0;
// We only need to initialize the first bucket because we reset buckets when
// current_bucket_ increments.
// 初始化第一个桶的数量
sample_buckets_[current_bucket_] = 0;
}
}t64_t[bucket_count + 1]),
total_sample_count_(0u),
bucket_start_time_milliseconds_(kTimeUnset) {
RTC_CHECK(bucket_milliseconds > 0);
RTC_CHECK(bucket_count > 0);
}
bucket_milliseconds: 表示桶的时间间隔，在RateStatistic里，桶的间隔是1ms，也就是每毫秒一个桶，而这里是bucket_milliseconds；bucket_count: 预设的桶的数量，也即准备使用的桶的数量是bucket_count_+1。
EnsureInitialized： 初始化
void RateTracker::EnsureInitialized() {
if (bucket_start_time_milliseconds_ == kTimeUnset) {
initialization_time_milliseconds_ = Time();
bucket_start_time_milliseconds_ = initialization_time_milliseconds_;
// 当前桶的序号
current_bucket_ = 0;
// We only need to initialize the first bucket because we reset buckets when
// current_bucket_ increments.
// 初始化第一个桶的数量
sample_buckets_[current_bucket_] = 0;
}
}
NextBucketIndex： 下一个桶的序号
size_t RateTracker::NextBucketIndex(size_t bucket_index) const {
return (bucket_index + 1u) % (bucket_count_ + 1u);
}
求模，这回导致形成一个循环，即桶的数量虽然是一定的，但是是循环利用的。
AddSamples： 添加sample
void RateTracker::AddSamples(int64_t sample_count) {
RTC_DCHECK_LE(0, sample_count);
// 确保进行初始化
EnsureInitialized();
int64_t current_time = Time();
// Advance the current bucket as needed for the current time, and reset
// bucket counts as we advance.
// 根据当前时间，对比当前桶的起始时间bucket_start_time_milliseconds_，每一个bucket_milliseconds_间隔，就初始化一个桶
// 在当前桶的时间范围内，就停止
for (size_t i = 0;
i <= bucket_count_ &&
current_time >= bucket_start_time_milliseconds_ + bucket_milliseconds_;
++i) {
bucket_start_time_milliseconds_ += bucket_milliseconds_;
current_bucket_ = NextBucketIndex(current_bucket_);
sample_buckets_[current_bucket_] = 0;
}
// Ensure that bucket_start_time_milliseconds_ is updated appropriately if
// the entire buffer of samples has been expired.
// // 确保bucket_start_time_milliseconds_的时间正确（有种情况就是桶的数量已达上限）
bucket_start_time_milliseconds_ +=
bucket_milliseconds_ *
((current_time - bucket_start_time_milliseconds_) / bucket_milliseconds_);
// Add all samples in the bucket that includes the current time.
// 更新当前桶的样本数量和总的样本数量
sample_buckets_[current_bucket_] += sample_count;
total_sample_count_ += sample_count;
}
ComputeTotalRate: 统计自初始化开始后的平均速率
double RateTracker::ComputeTotalRate() const {
if (bucket_start_time_milliseconds_ == kTimeUnset) {
return 0.0;
}
int64_t current_time = Time();
if (current_time <= initialization_time_milliseconds_) {
return 0.0;
}
return static_cast<double>(total_sample_count_ * 1000) /
static_cast<double>(
TimeDiff(current_time, initialization_time_milliseconds_));
}
ComputeRateForInterval： 给出最近interval_milliseconds的时间内的平均速率
double RateTracker::ComputeRateForInterval(
int64_t interval_milliseconds) const {
if (bucket_start_time_milliseconds_ == kTimeUnset) {
return 0.0;
}
int64_t current_time = Time();
// Calculate which buckets to sum up given the current time. If the time
// has passed to a new bucket then we have to skip some of the oldest buckets.
// 时间间隔限制在当前所有桶的范围，已经被覆盖的不能包含在内
int64_t available_interval_milliseconds =
std::min(interval_milliseconds,
bucket_milliseconds_ * static_cast<int64_t>(bucket_count_));
// number of old buckets (i.e. after the current bucket in the ring buffer)
// that are expired given our current time interval.
size_t buckets_to_skip;
// Number of milliseconds of the first bucket that are not a portion of the
// current interval.
int64_t milliseconds_to_skip;
// 判断发生了桶覆盖的情况，也即超过当前桶的表示范围
if (current_time >
initialization_time_milliseconds_ + available_interval_milliseconds) {
//需要跳过的时间
int64_t time_to_skip =
current_time - bucket_start_time_milliseconds_ +
static_cast<int64_t>(bucket_count_) * bucket_milliseconds_ -
available_interval_milliseconds;
//需要跳过的桶数量
buckets_to_skip = time_to_skip / bucket_milliseconds_;
//桶内时间偏移
milliseconds_to_skip = time_to_skip % bucket_milliseconds_;
} else {
buckets_to_skip = bucket_count_ - current_bucket_;
milliseconds_to_skip = 0;
available_interval_milliseconds =
TimeDiff(current_time, initialization_time_milliseconds_);
// 连一个桶的时间都不到
// Let one bucket interval pass after initialization before reporting.
if (available_interval_milliseconds < bucket_milliseconds_) {
return 0.0;
}
}
// If we're skipping all buckets that means that there have been no samples
// within the sampling interval so report 0.
if (buckets_to_skip > bucket_count_ || available_interval_milliseconds == 0) {
return 0.0;
}
size_t start_bucket = NextBucketIndex(current_bucket_ + buckets_to_skip);
// Only count a portion of the first bucket according to how much of the
// first bucket is within the current interval.
int64_t total_samples = ((sample_buckets_[start_bucket] *
(bucket_milliseconds_ - milliseconds_to_skip)) +
(bucket_milliseconds_ >> 1)) /
bucket_milliseconds_;
// All other buckets in the interval are counted in their entirety.
for (size_t i = NextBucketIndex(start_bucket);
i != NextBucketIndex(current_bucket_); i = NextBucketIndex(i)) {
total_samples += sample_buckets_[i];
}
// Convert to samples per second.
return static_cast<double>(total_samples * 1000) /
static_cast<double>(available_interval_milliseconds);
}
看的还是有些糊涂，大致意思就是求最近一段时间间隔内的平均速率(当间隔超过所有桶能表示的范围，就是所有桶周期内的平均速率)。在webrtc中主要用来进行帧率统计等工作。
