Spark profiling on Arm64

Owned by Yuqi Gu (Deactivated)
Mar 26, 2018
2 min read


Statsd-jvm-profiler with Hibench

Statsd-jvm-profiler is a JVM agent profiler that sends profiling data to StatsD/InfluxDB. It was primarily built for profiling Hadoop/Spark with any JVM process.

1. Prerequisites

 1.1 Install influxDB

a. Install go-lan

apt-get install golang-1.9

b. get source

mkdir $HOME/gocodez
export GOPATH=$HOME/gocodez
go get github.com/influxdata/influxdb

c. Build

cd $GOPATH/src/github.com/influxdata/influxdb
gdm restore
go clean ./...
go install ./...

d. Start influxDB

$GOPATH/bin/influxd

# Create DataBase user / password ( profiler / profiler)
influx -precision rfc3339
CREATE DATABASE profiler
CREATE USER profiler WITH PASSWORD 'profiler' WITH ALL PRIVILEGES

1.2 Install Statsd-jvm-profiler Dependencies

sudo easy_install pip
pip install influxdb
pip install blist

2 Installation and Configuration 

 We need the statsd-jvm-profiler JAR on the machine where the JVM will be running. 

The JAR can be built with mvn package. We need a relatively recent Maven (at least Maven 3).

statsd-jvm-profiler is available in Maven Central:

<dependency>
  <groupId>com.etsy</groupId>
  <artifactId>statsd-jvm-profiler</artifactId>
  <version>2.0.0</version>
</dependency>

2.1 Get source and Build Statsd-jvm-profiler

git clone https://github.com/etsy/statsd-jvm-profiler


# Build and Skip its Unit Tests
mvn package -DskipTests

Deploy the jar to the machines which are running the executor processes. One way to do this is to using spark-submit’s –jars attribute, which will deploy it to the executor.

--jars /path/to/statsd-jvm-profiler-2.1.1-jar-with-dependencies.jar


2.2 Set Additional options:

spark.executor.extraJavaOptions=-javaagent:/root/statsd-jvm-profiler-2.1.1-SNAPSHOT-jar-with-dependencies.jar=server=wls-arm-cavium02.shanghai.arm.com,port=8086,reporter=InfluxDBReporter,database=profiler,username=profiler,password=profiler,prefix=yuqi.XXX,tagMapping=XXX.test"
  • statsd-jvm-profiler-2.1.1-SNAPSHOT-jar-with-dependencies.jar：Built from mvn package
  • server/port:  Cluster host name, port is default to 8086
  • reporter: sends profiling data to StatsD or InfluxDB
  • prefix: prefix offset in influxDB
  • tagMapping: Tag name in influxDB


Add additional options to Hibench script
For Hibench-sleep example:

diff --git a/bin/functions/workload_functions.sh b/bin/functions/workload_functions.sh
index 2127f3e..2c12a8a 100644
--- a/bin/functions/workload_functions.sh
+++ b/bin/functions/workload_functions.sh
@@ -198,6 +198,8 @@ function run_spark_job() {
 
     export_withlog SPARKBENCH_PROPERTIES_FILES
 
+    HI_PROP_OPTS="--conf spark.executor.extraJavaOptions=-javaagent:/root/statsd-jvm-profiler-2.1.1-SNAPSHOT-jar-with-dependencies.jar=server=wls-arm-cavium02.shanghai.arm.com,port=8086,reporter=InfluxDBReporter,database=profiler,username=profiler,password=profiler,prefix=yuqi.sleep,tagMapping=sleep.test"
+
     YARN_OPTS=""
     if [[ "$SPARK_MASTER" == yarn-* ]]; then
         export_withlog HADOOP_CONF_DIR
@@ -215,9 +217,9 @@ function run_spark_job() {
     fi
     if [[ "$CLS" == *.py ]]; then
         LIB_JARS="$LIB_JARS --jars ${SPARKBENCH_JAR}"
-        SUBMIT_CMD="${SPARK_HOME}/bin/spark-submit ${LIB_JARS} --properties-file ${SPARK_PROP_CONF} --master ${SPARK_MASTER} ${YARN_OPTS} ${CLS} $@"
+        SUBMIT_CMD="${SPARK_HOME}/bin/spark-submit ${LIB_JARS} --properties-file ${SPARK_PROP_CONF} --master ${SPARK_MASTER} ${YARN_OPTS} ${HI_PROP_OPTS}  ${CLS} $@"
     else
-        SUBMIT_CMD="${SPARK_HOME}/bin/spark-submit ${LIB_JARS} --properties-file ${SPARK_PROP_CONF} --class ${CLS} --master ${SPARK_MASTER} ${YARN_OPTS} ${SPARKBENCH_JAR} $@"
+        SUBMIT_CMD="${SPARK_HOME}/bin/spark-submit ${LIB_JARS} --properties-file ${SPARK_PROP_CONF} --class ${CLS} --master ${SPARK_MASTER} ${YARN_OPTS} ${HI_PROP_OPTS} ${SPARKBENCH_JAR} $@"
     fi


3. Profiling results

 3.1 Get Stack Dump from InfluxDB

Get dump tool:

https://github.com/etsy/statsd-jvm-profiler/blob/master/visualization/influxdb_dump.py

For Hibench-sleep example,sleep stack is the output file:

influxdb_dump.py -o "wls-arm-cavium02.shanghai.arm.com" -u profiler -p profiler -d profiler -t sleep.test -e yuqi.sleep> sleep.stack


3.2  Generate Flame graph 

Get tools:

https://github.com/brendangregg/FlameGraph/blob/master/flamegraph.pl

Generate flame graphs using the text files you dumped from InfluxDB dump file:

flamegraph.pl sleep.stack  > sleep.svg


4.   Profiling Analysis of Hibench Flame Graph 

  • Spark Sleep Graph

The original SVG file:  sleep.svg



The original SVG file: Sort.svg





  • Spark Terasort Graph 

The original SVG file: Terasort.svg



  • Spark WordCount Graph

The original SVG file:  wordCount.svg


  • High CPU utilization rank

From above 4 flame graphs:

Rank(%)SortTerasortwordCountSleep
1
sun.nio.ch.EPollArrayWrapper.epollWait
49.66%
sun.nio.ch.EPollArrayWrapper.epollWait
62.85%
sun.nio.ch.EPollArrayWrapper.epollWait
48.17%
io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run
---->sun.nio.ch.EPollArrayWrapper.epollWait
76.71%
2

io.netty.util.concurrent.SingleThreadEventExecutor$2.run

--→sun.nio.ch.EPollArrayWrapper.epollWait

14.8%

io.netty.util.concurrent.SingleThreadEventExecutor$2.run

--→sun.nio.ch.EPollArrayWrapper.epollWait

12.53%

io.netty.util.concurrent.SingleThreadEventExecutor$2.run

--→sun.nio.ch.EPollArrayWrapper.epollWait

19.78%

io.netty.util.concurrent.SingleThreadEventExecutor$2.run

---->sun.nio.ch.EPollArrayWrapper.epollWait

16.52%

3

org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write

13.34%

org.apache.spark.scheduler.ResultTask.runTask

13.67%

org.apache.spark.executor.CoarseGrainedExecutorBackend$.main
9.35%

java.util.concurrent.ThreadPoolExecutor.runWorker

0.1%

4

org.apache.hadoop.net.unix.DomainSocketWatcher.doPoll0

13.24%

org.apache.hadoop.ipc.ProtobufRpcEngine.getProxy
5.15%

org.apache.spark.deploy.SparkHadoopUtil$.liftedTree1$1
5.56%

com.squareup.okhttp.ConnectionPool.performCleanup

0.05%

5

org.apache.spark.rdd.RDD.iterator

5.26%


org.apache.spark.executor.CoarseGrainedExecutorBackend.main
4.48%

org.apache.spark.scheduler.ShuffleMapTask.runTask
5.55%

org.apache.spark.rpc.netty.Inbox.process

0.05%

6

org.apache.spark.serializer.KryoSerializer.newKryo

3.51%

org.apache.spark.SparkEnv$.createExecutorEnv
3.82

org.apache.hadoop.net.unix.DomainSocketWatcher.doPoll0
4.24%

org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp

0.05%

7

org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy

3.02%

org.apache.hadoop.net.unix.DomainSocketWatcher.doPoll0
3.58%

org.apache.spark.deploy.SparkHadoopUtil.<init>
3.35%

java.net.URLClassLoader.findClass

0.05%

8

com.twitter.chill.AllScalaRegistrar.apply

3.02%


sun.reflect.NativeConstructorAccessorImpl.newInstance0
2.59%

org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser
2.65%

sun.misc.URLClassPath$JarLoader.getResource

0.05%

9

org.apache.hadoop.hdfs.BlockReaderFactory.getRemoteBlockReaderFromTcp

2.14%

sun.misc.ProxyGenerator.generateClassFile
2.41%

org.apache.spark.util.collection.ExternalSorter.insertAll
1.66%

java.util.jar.JarFile.getJarEntry

0.05%

10

com.esotericsoftware.kryo.Kryo.<init>

2.04%

org.apache.spark.metrics.sink.MetricsServlet.<init>
1.49%

org.apache.spark.scheduler.ShuffleMapTask.runTask
1.16%

java.util.zip.ZipFile.getEntry

0.05%