ExponentialWeightedAverageTimeToFirstByteEstimator.java
/*
* Copyright 2021 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package androidx.media3.exoplayer.upstream.experimental;
import androidx.annotation.Nullable;
import androidx.annotation.VisibleForTesting;
import androidx.media3.common.C;
import androidx.media3.common.util.Clock;
import androidx.media3.common.util.UnstableApi;
import androidx.media3.common.util.Util;
import androidx.media3.datasource.DataSpec;
import androidx.media3.exoplayer.upstream.TimeToFirstByteEstimator;
import java.util.LinkedHashMap;
import java.util.Map;
/** Implementation of {@link TimeToFirstByteEstimator} based on exponential weighted average. */
@UnstableApi
public final class ExponentialWeightedAverageTimeToFirstByteEstimator
implements TimeToFirstByteEstimator {
/** The default smoothing factor. */
public static final double DEFAULT_SMOOTHING_FACTOR = 0.85;
private static final int MAX_DATA_SPECS = 10;
private final LinkedHashMap<DataSpec, Long> initializedDataSpecs;
private final double smoothingFactor;
private final Clock clock;
private long estimateUs;
/** Creates an instance using the {@link #DEFAULT_SMOOTHING_FACTOR}. */
public ExponentialWeightedAverageTimeToFirstByteEstimator() {
this(DEFAULT_SMOOTHING_FACTOR, Clock.DEFAULT);
}
/**
* Creates an instance.
*
* @param smoothingFactor The exponential weighted average smoothing factor.
*/
public ExponentialWeightedAverageTimeToFirstByteEstimator(double smoothingFactor) {
this(smoothingFactor, Clock.DEFAULT);
}
/**
* Creates an instance.
*
* @param smoothingFactor The exponential weighted average smoothing factor.
* @param clock The {@link Clock} used for calculating time samples.
*/
@VisibleForTesting
/* package */ ExponentialWeightedAverageTimeToFirstByteEstimator(
double smoothingFactor, Clock clock) {
this.smoothingFactor = smoothingFactor;
this.clock = clock;
initializedDataSpecs = new FixedSizeLinkedHashMap<>(/* maxSize= */ MAX_DATA_SPECS);
estimateUs = C.TIME_UNSET;
}
@Override
public long getTimeToFirstByteEstimateUs() {
return estimateUs;
}
@Override
public void reset() {
estimateUs = C.TIME_UNSET;
}
@Override
public void onTransferInitializing(DataSpec dataSpec) {
// Remove to make sure insertion order is updated in case the key already exists.
initializedDataSpecs.remove(dataSpec);
initializedDataSpecs.put(dataSpec, Util.msToUs(clock.elapsedRealtime()));
}
@Override
public void onTransferStart(DataSpec dataSpec) {
@Nullable Long initializationStartUs = initializedDataSpecs.remove(dataSpec);
if (initializationStartUs == null) {
return;
}
long timeToStartSampleUs = Util.msToUs(clock.elapsedRealtime()) - initializationStartUs;
if (estimateUs == C.TIME_UNSET) {
estimateUs = timeToStartSampleUs;
} else {
estimateUs =
(long) (smoothingFactor * estimateUs + (1d - smoothingFactor) * timeToStartSampleUs);
}
}
private static class FixedSizeLinkedHashMap<K, V> extends LinkedHashMap<K, V> {
private final int maxSize;
public FixedSizeLinkedHashMap(int maxSize) {
this.maxSize = maxSize;
}
@Override
protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
return size() > maxSize;
}
}
}