/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you 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 org.apache.beam.sdk.util; import static com.google.common.base.Preconditions.checkState; import java.util.HashMap; import java.util.Map; import org.apache.beam.sdk.transforms.Combine; /** * Keep track of the minimum/maximum/sum of a set of timestamped long values. * For efficiency, bucket values by their timestamp. */ public class BucketingFunction { private static class Bucket { private int numSamples; private long combinedValue; public Bucket(BucketingFunction outer) { numSamples = 0; combinedValue = outer.function.identity(); } public void add(BucketingFunction outer, long value) { combinedValue = outer.function.apply(combinedValue, value); numSamples++; } public boolean remove() { numSamples--; checkState(numSamples >= 0, "Lost count of samples"); return numSamples == 0; } public long get() { return combinedValue; } } /** * How large a time interval to fit within each bucket. */ private final long bucketWidthMs; /** * How many buckets are considered 'significant'? */ private final int numSignificantBuckets; /** * How many samples are considered 'significant'? */ private final int numSignificantSamples; /** * Function for combining sample values. */ private final Combine.BinaryCombineLongFn function; /** * Active buckets. */ private final Map<Long, Bucket> buckets; public BucketingFunction( long bucketWidthMs, int numSignificantBuckets, int numSignificantSamples, Combine.BinaryCombineLongFn function) { this.bucketWidthMs = bucketWidthMs; this.numSignificantBuckets = numSignificantBuckets; this.numSignificantSamples = numSignificantSamples; this.function = function; this.buckets = new HashMap<>(); } /** * Which bucket key corresponds to {@code timeMsSinceEpoch}. */ private long key(long timeMsSinceEpoch) { return timeMsSinceEpoch - (timeMsSinceEpoch % bucketWidthMs); } /** * Add one sample of {@code value} (to bucket) at {@code timeMsSinceEpoch}. */ public void add(long timeMsSinceEpoch, long value) { long key = key(timeMsSinceEpoch); Bucket bucket = buckets.get(key); if (bucket == null) { bucket = new Bucket(this); buckets.put(key, bucket); } bucket.add(this, value); } /** * Remove one sample (from bucket) at {@code timeMsSinceEpoch}. */ public void remove(long timeMsSinceEpoch) { long key = key(timeMsSinceEpoch); Bucket bucket = buckets.get(key); if (bucket == null) { return; } if (bucket.remove()) { buckets.remove(key); } } /** * Return the (bucketized) combined value of all samples. */ public long get() { long result = function.identity(); for (Bucket bucket : buckets.values()) { result = function.apply(result, bucket.get()); } return result; } /** * Is the current result 'significant'? Ie is it drawn from enough buckets * or from enough samples? */ public boolean isSignificant() { if (buckets.size() >= numSignificantBuckets) { return true; } int totalSamples = 0; for (Bucket bucket : buckets.values()) { totalSamples += bucket.numSamples; } return totalSamples >= numSignificantSamples; } }