addSample getPercentile

依据下载sampleBytesTransferred开方数作为weight参数调用addSample，意味着下载码率越高weight越大

  public synchronized void onTransferEnd(DataSource source, DataSpec dataSpec, boolean isNetwork) {
    if (!isNetwork) {
      return;
    }
    Assertions.checkState(streamCount > 0);
    long nowMs = clock.elapsedRealtime();
    int sampleElapsedTimeMs = (int) (nowMs - sampleStartTimeMs);
    totalElapsedTimeMs += sampleElapsedTimeMs;
    totalBytesTransferred += sampleBytesTransferred;
    if (sampleElapsedTimeMs > 0) {
      float bitsPerSecond = (sampleBytesTransferred * 8000) / sampleElapsedTimeMs;
      slidingPercentile.addSample((int) Math.sqrt(sampleBytesTransferred), bitsPerSecond);
      if (totalElapsedTimeMs >= ELAPSED_MILLIS_FOR_ESTIMATE
          || totalBytesTransferred >= BYTES_TRANSFERRED_FOR_ESTIMATE) {
        bitrateEstimate = (long) slidingPercentile.getPercentile(0.5f);
      }
    }
    notifyBandwidthSample(sampleElapsedTimeMs, sampleBytesTransferred, bitrateEstimate);
    if (--streamCount > 0) {
      sampleStartTimeMs = nowMs;
    }
    sampleBytesTransferred = 0;
  }

按照INDEX插入weight，value，超出weight部分删除最旧index对应的sample

 /**
  * Adds a new weighted value.
  *
  * @param weight The weight of the new observation.
  * @param value The value of the new observation.
  */
  public void addSample(int weight, float value) {
    ensureSortedByIndex();
    Sample newSample = recycledSampleCount > 0 ? recycledSamples[--recycledSampleCount]
        : new Sample();
    newSample.index = nextSampleIndex++;
    newSample.weight = weight;
    newSample.value = value;
    samples.add(newSample);
    totalWeight += weight;
for (int i = 0; i < samples.size(); i++) {
      Sample currentSample = samples.get(i);
}
    while (totalWeight > maxWeight) {
      int excessWeight = totalWeight - maxWeight;
      Sample oldestSample = samples.get(0);
      if (oldestSample.weight <= excessWeight) {
        totalWeight -= oldestSample.weight;
        samples.remove(0);
        if (recycledSampleCount < MAX_RECYCLED_SAMPLES) {
          recycledSamples[recycledSampleCount++] = oldestSample;
        }
      } else {
        oldestSample.weight -= excessWeight;
        totalWeight -= excessWeight;
      }
    }
  }

获取当前value时，依据value排序：
如果weight较小，窗口中累加weight次数较多，依据下载速度排序后会选择value相对较大的sample
如果weight较大，累加weight次数较少，但在切片均匀的情况下通常weight也跟网速成正比(网速快才会下载更高码率，sample size也会更大)，此时选择value可能直接就拿第一个sample了

  /**
   * Computes a percentile by integration.
   *
   * @param percentile The desired percentile, expressed as a fraction in the range (0,1].
   * @return The requested percentile value or {@link Float#NaN} if no samples have been added.
   */
  public float getPercentile(float percentile) {
    ensureSortedByValue();
    float desiredWeight = percentile * totalWeight;
    int accumulatedWeight = 0;
    for (int i = 0; i < samples.size(); i++) {
      Sample currentSample = samples.get(i);
      accumulatedWeight += currentSample.weight;
      if (accumulatedWeight >= desiredWeight) {
        return currentSample.value;
      }
    }
    // Clamp to maximum value or NaN if no values.
    return samples.isEmpty() ? Float.NaN : samples.get(samples.size() - 1).value;
  }