| /* |
| * 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 org.apache.beam.vendor.guava.v20_0.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.computeIfAbsent(key, k -> new Bucket(this)); |
| 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; |
| } |
| } |