Add cluster applier stats #77552
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| Original file line number | Diff line number | Diff line change | ||||
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| @@ -0,0 +1,149 @@ | ||||||
| /* | ||||||
| * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||||||
| * or more contributor license agreements. Licensed under the Elastic License | ||||||
| * 2.0 and the Server Side Public License, v 1; you may not use this file except | ||||||
| * in compliance with, at your election, the Elastic License 2.0 or the Server | ||||||
| * Side Public License, v 1. | ||||||
| */ | ||||||
| package org.elasticsearch.cluster.service; | ||||||
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| import org.elasticsearch.cluster.service.ClusterApplierRecordingService.Stats.Recording; | ||||||
| import org.elasticsearch.common.io.stream.StreamInput; | ||||||
| import org.elasticsearch.common.io.stream.StreamOutput; | ||||||
| import org.elasticsearch.common.io.stream.Writeable; | ||||||
| import org.elasticsearch.common.metrics.MeanMetric; | ||||||
| import org.elasticsearch.common.xcontent.ToXContentFragment; | ||||||
| import org.elasticsearch.common.xcontent.XContentBuilder; | ||||||
| import org.elasticsearch.core.Releasable; | ||||||
| import org.elasticsearch.core.TimeValue; | ||||||
| import org.elasticsearch.core.Tuple; | ||||||
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| import java.io.IOException; | ||||||
| import java.io.UncheckedIOException; | ||||||
| import java.util.HashSet; | ||||||
| import java.util.LinkedList; | ||||||
| import java.util.List; | ||||||
| import java.util.Map; | ||||||
| import java.util.Set; | ||||||
| import java.util.concurrent.ConcurrentHashMap; | ||||||
| import java.util.stream.Collectors; | ||||||
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| public final class ClusterApplierRecordingService { | ||||||
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| private final Map<String, MeanMetric> recordedActions = new ConcurrentHashMap<>(); | ||||||
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| synchronized Stats getStats() { | ||||||
|
There was a problem hiding this comment. This seems mildly scary, though I'm having a hard time guessing the impact. But technically, a barrage of stats requests would cause the CS applier thread to slow down (potentially considerably?) There was a problem hiding this comment. My thinking is that this should complete in microseconds => we'd need implausibly many concurrent stats requests to cause meaningful starvation here. There was a problem hiding this comment. True, I guess it also runs on the management pool with somewhat limited concurrency 🤞 :) |
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| return new Stats( | ||||||
| recordedActions.entrySet().stream() | ||||||
| .collect(Collectors.toUnmodifiableMap(Map.Entry::getKey, e -> new Recording(e.getValue().count(), e.getValue().sum()))) | ||||||
| ); | ||||||
| } | ||||||
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| synchronized void updateStats(Recorder recorder) { | ||||||
| Set<String> seenActions = new HashSet<>(); | ||||||
| for (Tuple<String, Long> entry : recorder.recordings) { | ||||||
| String action = entry.v1(); | ||||||
| long timeSpentMS = entry.v2(); | ||||||
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| MeanMetric metric = recordedActions.computeIfAbsent(action, key -> new MeanMetric()); | ||||||
| metric.inc(timeSpentMS); | ||||||
| seenActions.add(action); | ||||||
| } | ||||||
| recordedActions.entrySet().removeIf(entry -> seenActions.contains(entry.getKey()) == false); | ||||||
| } | ||||||
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| static final class Recorder { | ||||||
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| private String currentAction; | ||||||
| private long startTimeNS; | ||||||
| private boolean recording; | ||||||
| private final List<Tuple<String, Long>> recordings = new LinkedList<>(); | ||||||
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| Releasable record(String action) { | ||||||
| if (recording) { | ||||||
| throw new IllegalStateException("already recording"); | ||||||
| } | ||||||
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| this.recording = true; | ||||||
| this.currentAction = action; | ||||||
| this.startTimeNS = System.nanoTime(); | ||||||
|
There was a problem hiding this comment. I think we're ok with milliseconds so we can use |
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| return this::stop; | ||||||
| } | ||||||
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| void stop() { | ||||||
| recording = false; | ||||||
| long timeSpentMS = TimeValue.nsecToMSec(System.nanoTime() - this.startTimeNS); | ||||||
| recordings.add(new Tuple<>(currentAction, timeSpentMS)); | ||||||
| } | ||||||
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| List<Tuple<String, Long>> getRecordings() { | ||||||
| return recordings; | ||||||
| } | ||||||
| } | ||||||
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| public static class Stats implements Writeable, ToXContentFragment { | ||||||
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| private final Map<String, Recording> recordings; | ||||||
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| public Stats(Map<String, Recording> recordings) { | ||||||
| this.recordings = recordings; | ||||||
| } | ||||||
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| public Stats(StreamInput in) throws IOException { | ||||||
| this(in.readMap(StreamInput::readString, Recording::new)); | ||||||
| } | ||||||
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| @Override | ||||||
| public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException { | ||||||
| builder.startObject("cluster_applier_stats"); | ||||||
| builder.startArray("recordings"); | ||||||
| toXContentTimeSpent(builder, recordings); | ||||||
| builder.endObject(); | ||||||
| return builder; | ||||||
| } | ||||||
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| private static void toXContentTimeSpent(XContentBuilder builder, Map<String, Recording> timeSpentPerListener) throws IOException { | ||||||
| timeSpentPerListener.entrySet().stream() | ||||||
| .sorted((o1, o2) -> -Long.compare(o1.getValue().sum, o2.getValue().sum)) | ||||||
|
There was a problem hiding this comment. I can never remember which way round this'll sort, but then I couldn't get the explicit alternative to work with type inference for some reason so it looks like this. Yuck either way.
Suggested change
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| .forEach(entry -> { | ||||||
| try { | ||||||
| builder.startObject(); | ||||||
| builder.field("name", entry.getKey()); | ||||||
| String name = "cumulative_execution"; | ||||||
| builder.field(name + "_count", entry.getValue().count); | ||||||
| builder.humanReadableField(name + "_time_millis", name + "_time", TimeValue.timeValueMillis(entry.getValue().sum)); | ||||||
| builder.endObject(); | ||||||
| } catch (IOException e) { | ||||||
| throw new UncheckedIOException(e); | ||||||
|
There was a problem hiding this comment. Don't think I like this, we don't generally check for |
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| } | ||||||
| }); | ||||||
| builder.endArray(); | ||||||
| } | ||||||
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| @Override | ||||||
| public void writeTo(StreamOutput out) throws IOException { | ||||||
| out.writeMap(recordings, StreamOutput::writeString, (out1, value) -> value.writeTo(out1)); | ||||||
| } | ||||||
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| public static class Recording implements Writeable { | ||||||
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| private final long count; | ||||||
| private final long sum; | ||||||
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| public Recording(long count, long sum) { | ||||||
| this.count = count; | ||||||
| this.sum = sum; | ||||||
| } | ||||||
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| public Recording(StreamInput in) throws IOException { | ||||||
| this(in.readVLong(), in.readVLong()); | ||||||
| } | ||||||
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| @Override | ||||||
| public void writeTo(StreamOutput out) throws IOException { | ||||||
| out.writeVLong(count); | ||||||
| out.writeVLong(sum); | ||||||
| } | ||||||
| } | ||||||
| } | ||||||
| } | ||||||
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All the access to this is
synchronizedso I think we can just use a regularHashMap