Log the sizes allocated through the SimpleMemoryPool for analysis. #380
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.kafka.common.memory; | ||
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| import java.util.HashMap; | ||
| import java.util.Map; | ||
| import java.util.concurrent.atomic.AtomicInteger; | ||
| import org.slf4j.Logger; | ||
| import org.slf4j.LoggerFactory; | ||
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| public class MemoryPoolStatsStore { | ||
| private static final Logger log = LoggerFactory.getLogger(MemoryPoolStatsStore.class); | ||
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| private final AtomicInteger[] histogram; | ||
| private final int maxSizeBytes; | ||
| private final int segmentSizeBytes; | ||
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| public static class Range { | ||
| public final int startInclusive; | ||
| public final int endInclusive; | ||
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| public Range(int startInclusive, int endInclusive) { | ||
| this.startInclusive = startInclusive; | ||
| this.endInclusive = endInclusive; | ||
| } | ||
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| @Override | ||
| public String toString() { | ||
| return "Range{" + "startInclusive=" + startInclusive + ", endInclusive=" + endInclusive + '}'; | ||
| } | ||
| } | ||
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| public MemoryPoolStatsStore(int segments, int maxSizeBytes) { | ||
| histogram = new AtomicInteger[segments]; | ||
| this.maxSizeBytes = maxSizeBytes; | ||
| segmentSizeBytes = (int) Math.ceil((double) maxSizeBytes / segments); | ||
| for (int segmentIndex = 0; segmentIndex < segments; segmentIndex++) { | ||
| histogram[segmentIndex] = new AtomicInteger(); | ||
| } | ||
| } | ||
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| private int getSegmentIndexForBytes(int bytes) { | ||
| if (bytes == 0) { | ||
| throw new IllegalArgumentException("Requested zero bytes for allocation."); | ||
| } | ||
| if (bytes > maxSizeBytes) { | ||
| log.debug("Requested bytes {} for allocation exceeds maximum recorded value {}", bytes, maxSizeBytes); | ||
| return -1; | ||
| } else { | ||
| return (bytes - 1) / segmentSizeBytes; | ||
|
There was a problem hiding this comment. Would it be better to record the bytes in log scale instead of linear scale? |
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| } | ||
| } | ||
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| public void recordAllocation(int bytes) { | ||
| try { | ||
| final int segmentIndex = getSegmentIndexForBytes(bytes); | ||
| if (segmentIndex != -1) { | ||
| histogram[segmentIndex].incrementAndGet(); | ||
| } | ||
| } catch (IllegalArgumentException e) { | ||
| log.error("Encountered error when trying to record memory allocation for request", e); | ||
| } | ||
| } | ||
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| public synchronized Map<Range, Integer> getFrequencies() { | ||
| Map<Range, Integer> frequenciesMap = new HashMap<>(); | ||
| for (int segmentIndex = 0; segmentIndex < histogram.length; segmentIndex++) { | ||
| frequenciesMap.put(new Range( | ||
| segmentIndex * segmentSizeBytes + 1, | ||
| segmentIndex * segmentSizeBytes + segmentSizeBytes | ||
| ), histogram[segmentIndex].intValue()); | ||
| } | ||
| return frequenciesMap; | ||
| } | ||
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| public synchronized void clear() { | ||
| for (AtomicInteger atomicInteger : histogram) { | ||
| atomicInteger.set(0); | ||
| } | ||
| } | ||
| } | ||
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Is there a reason to not use the metrics object but implement this by hand?
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Yes. Kafka metrics support publishing histograms only as percentiles. This will not be useful information for us to determine the range of most frequent memory allocations. For example, consider that around 60% of requests are of size 1 kb. Now, if we observe from metrics that the p90 request size is 400k and the p99 size is 1500k, we are unable to make any inference about the fact that most requests are within 1 kb range.
Hence, we are publishing the full histogram as logs.