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[SPARK-18364][YARN] Expose metrics for YarnShuffleService #17401

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Original file line number Diff line number Diff line change
Expand Up @@ -176,7 +176,8 @@ private void checkAuth(TransportClient client, String appId) {
/**
* A simple class to wrap all shuffle service wrapper metrics
*/
private class ShuffleMetrics implements MetricSet {
@VisibleForTesting
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@VisibleForTesting causes classpath issues. Please note this in the java doc instead (SPARK-11615).

This is a scalastyle output, would be better to remove this annotation.

public class ShuffleMetrics implements MetricSet {
private final Map<String, Metric> allMetrics;
// Time latency for open block request in ms
private final Timer openBlockRequestLatencyMillis = new Timer();
Expand All @@ -185,7 +186,7 @@ private class ShuffleMetrics implements MetricSet {
// Block transfer rate in byte per second
private final Meter blockTransferRateBytes = new Meter();

private ShuffleMetrics() {
public ShuffleMetrics() {
allMetrics = new HashMap<>();
allMetrics.put("openBlockRequestLatencyMillis", openBlockRequestLatencyMillis);
allMetrics.put("registerExecutorRequestLatencyMillis", registerExecutorRequestLatencyMillis);
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -19,8 +19,9 @@

import java.io.File;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.lang.reflect.Method;
import java.nio.ByteBuffer;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.util.List;
import java.util.Map;
Expand All @@ -35,9 +36,11 @@
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.permission.FsPermission;
import org.apache.hadoop.metrics2.MetricsSource;
import org.apache.hadoop.metrics2.impl.MetricsSystemImpl;
import org.apache.hadoop.metrics2.lib.DefaultMetricsSystem;
import org.apache.hadoop.yarn.api.records.ContainerId;
import org.apache.hadoop.yarn.server.api.*;
import org.apache.spark.network.util.LevelDBProvider;
import org.iq80.leveldb.DB;
import org.iq80.leveldb.DBIterator;

Expand All @@ -50,6 +53,7 @@
import org.apache.spark.network.server.TransportServer;
import org.apache.spark.network.server.TransportServerBootstrap;
import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler;
import org.apache.spark.network.util.LevelDBProvider;
import org.apache.spark.network.util.TransportConf;
import org.apache.spark.network.yarn.util.HadoopConfigProvider;

Expand Down Expand Up @@ -166,6 +170,23 @@ protected void serviceInit(Configuration conf) throws Exception {
TransportConf transportConf = new TransportConf("shuffle", new HadoopConfigProvider(conf));
blockHandler = new ExternalShuffleBlockHandler(transportConf, registeredExecutorFile);

// register metrics on the block handler into the Node Manager's metrics system.
try {
YarnShuffleServiceMetrics serviceMetrics = new YarnShuffleServiceMetrics(
blockHandler.getAllMetrics());
MetricsSystemImpl metricsSystem = (MetricsSystemImpl) DefaultMetricsSystem.instance();

Method registerSourceMethod = metricsSystem.getClass().getDeclaredMethod("registerSource",
String.class, String.class, MetricsSource.class);
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@jerryshao jerryshao Mar 27, 2017

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Nit, here I think should be 2 space indent follow the above line.

registerSourceMethod.setAccessible(true);
registerSourceMethod.invoke(metricsSystem, "shuffleService", "Metrics on the Spark " +
"Shuffle Service", serviceMetrics);
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Also here.

logger.info("Registered metrics with Hadoop's DefaultMetricsSystem");
} catch (Exception e) {
logger.warn("Unable to register Spark Shuffle Service metrics with Node Manager; " +
"proceeding without metrics", e);
}

// If authentication is enabled, set up the shuffle server to use a
// special RPC handler that filters out unauthenticated fetch requests
List<TransportServerBootstrap> bootstraps = Lists.newArrayList();
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,123 @@
/*
* 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.spark.network.yarn;

import com.codahale.metrics.*;
import com.google.common.annotations.VisibleForTesting;
import org.apache.hadoop.metrics2.MetricsCollector;
import org.apache.hadoop.metrics2.MetricsInfo;
import org.apache.hadoop.metrics2.MetricsRecordBuilder;
import org.apache.hadoop.metrics2.MetricsSource;

import java.util.Map;

/**
* Modeled off of YARN's NodeManagerMetrics.
*/
public class YarnShuffleServiceMetrics implements MetricsSource {

private final MetricSet metricSet;

public YarnShuffleServiceMetrics(MetricSet metricSet) {
this.metricSet = metricSet;
}

/**
* Get metrics from the source
*
* @param collector to contain the resulting metrics snapshot
* @param all if true, return all metrics even if unchanged.
*/
@Override
public void getMetrics(MetricsCollector collector, boolean all) {
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Is it possible to add a unit test to verify the correctness of converting codahale metrics to Hadoop metrics?

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should be able to, I'm working on creating one now. By correctness, I think you mostly mean that the values passed through are the same, even though the naming schemes are different?

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Yes, you're right. From my understanding the correctness means Gauge still coverts to Gauge, Meter still to Meter, not sure can it be guaranteed?

MetricsRecordBuilder metricsRecordBuilder = collector.addRecord("shuffleService");

for (Map.Entry<String, Metric> entry : metricSet.getMetrics().entrySet()) {
collectMetric(metricsRecordBuilder, entry.getKey(), entry.getValue());
}
}

@VisibleForTesting
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Also here.

public static void collectMetric(MetricsRecordBuilder metricsRecordBuilder, String name, Metric metric) {
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Is it necessary to use static here? Looks like here it is it is only for the test convenience.

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I use static here to make it clear that the method does not need to be run in the context of an instance. This prevents it from accidentally accessing instance variables when I don't intend it to


// The metric types used in ExternalShuffleBlockHandler.ShuffleMetrics
if (metric instanceof Timer) {
Timer t = (Timer) metric;
metricsRecordBuilder
.addCounter(new ShuffleServiceMetricsInfo(name + "_count", "Count of timer " + name),
t.getCount())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate15", "15 minute rate of timer " + name),
t.getFifteenMinuteRate())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate5", "5 minute rate of timer " + name),
t.getFiveMinuteRate())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate1", "1 minute rate of timer " + name),
t.getOneMinuteRate())
.addGauge(new ShuffleServiceMetricsInfo(name + "_rateMean", "Mean rate of timer " + name),
t.getMeanRate());
} else if (metric instanceof Meter) {
Meter m = (Meter) metric;
metricsRecordBuilder
.addCounter(new ShuffleServiceMetricsInfo(name + "_count", "Count of meter " + name),
m.getCount())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate15", "15 minute rate of meter " + name),
m.getFifteenMinuteRate())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate5", "5 minute rate of meter " + name),
m.getFiveMinuteRate())
.addGauge(
new ShuffleServiceMetricsInfo(name + "_rate1", "1 minute rate of meter " + name),
m.getOneMinuteRate())
.addGauge(new ShuffleServiceMetricsInfo(name + "_rateMean", "Mean rate of meter " + name),
m.getMeanRate());
} else if (metric instanceof Gauge) {
Gauge m = (Gauge) metric;
Object gaugeValue = m.getValue();
if (gaugeValue instanceof Integer) {
Integer intValue = (Integer) gaugeValue;
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Does it mean that we could only handle integer Gauge, what if later on we add different metric in ExternalShuffleBlockHandler? Looks like we should also manually handle the case one by one here. At least we should an else branch for the fallback check.

metricsRecordBuilder
.addGauge(new ShuffleServiceMetricsInfo(name, "Integer value of " +
"gauge " + name), intValue.intValue());
}
}
}

private static class ShuffleServiceMetricsInfo implements MetricsInfo {

private final String name;
private final String description;

ShuffleServiceMetricsInfo(String name, String description) {
this.name = name;
this.description = description;
}

@Override
public String name() {
return name;
}

@Override
public String description() {
return description;
}
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,74 @@
/*
* 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.spark.network.yarn

import org.apache.hadoop.metrics2.MetricsRecordBuilder
import org.mockito.Matchers._
import org.mockito.Mockito.{mock, times, verify, when}
import org.scalatest.Matchers
import scala.collection.JavaConverters._
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The import ordering is not correct, Scala package should be before the third party packages.


import org.apache.spark.network.server.OneForOneStreamManager
import org.apache.spark.network.shuffle.{ExternalShuffleBlockHandler, ExternalShuffleBlockResolver}
import org.apache.spark.SparkFunSuite

class YarnShuffleServiceMetricsSuite extends SparkFunSuite with Matchers {

val streamManager = mock(classOf[OneForOneStreamManager])
val blockResolver = mock(classOf[ExternalShuffleBlockResolver])
when(blockResolver.getRegisteredExecutorsSize).thenReturn(42)

val metrics = new ExternalShuffleBlockHandler(streamManager, blockResolver).getAllMetrics

test("metrics named as expected") {
val allMetrics = Set(
"openBlockRequestLatencyMillis", "registerExecutorRequestLatencyMillis",
"blockTransferRateBytes", "registeredExecutorsSize")

metrics.getMetrics.keySet().asScala should be (allMetrics)
}

// these three metrics have the same effect on the collector
for (testname <- Seq("openBlockRequestLatencyMillis",
"registerExecutorRequestLatencyMillis",
"blockTransferRateBytes")) {
test(s"$testname - collector receives correct types") {
val builder = mock(classOf[MetricsRecordBuilder])
when(builder.addCounter(any(), anyLong())).thenReturn(builder)
when(builder.addGauge(any(), anyDouble())).thenReturn(builder)

YarnShuffleServiceMetrics.collectMetric(builder, testname,
metrics.getMetrics.get(testname))

verify(builder).addCounter(anyObject(), anyLong())
verify(builder, times(4)).addGauge(anyObject(), anyDouble())
}
}

// this metric writes only one gauge to the collector
test("registeredExecutorsSize - collector receives correct types") {
val builder = mock(classOf[MetricsRecordBuilder])
when(builder.addCounter(any(), anyLong())).thenReturn(builder)
when(builder.addGauge(any(), anyDouble())).thenReturn(builder)

YarnShuffleServiceMetrics.collectMetric(builder, "registeredExecutorsSize",
metrics.getMetrics.get("registeredExecutorsSize"))

// only one
verify(builder).addGauge(anyObject(), anyInt())
}
}