Spark（五十）：使用JvisualVM监控Spark Executor JVM
引导
Windows环境下JvisulaVM一般存在于安装了JDK的目录${JAVA_HOME}/bin/JvisualVM.exe，它支持（本地和远程）jstatd和JMX两种方式连接远程JVM。
jstatd (Java Virtual Machine jstat Daemon)——监听远程服务器的CPU，内存，线程等信息
JMX（Java Management Extensions，即Java管理扩展）是一个为应用程序、设备、系统等植入管理功能的框架。JMX可以跨越一系列异构操作系统平台、系统体系结构和网络传输协议，灵活的开发无缝集成的系统、网络和服务管理应用。
备注：针对jstatd我尝试未成功，因此也不在这里误导别人。
JMX监控
正常配置：
-Dcom.sun.management.jmxremote
-Dcom.sun.management.jmxremote.ssl=false
-Dcom.sun.management.jmxremote.authenticate=false
-Djava.rmi.server.hostname=<ip>
-Dcom.sun.management.jmxremote.port=<port>
添加JMX配置：
在Spark中监控executor时，需要先配置jmx然后再启动spark应用程序，配置方式有三种：
1）在spark-defaults.conf中配置那三个参数
2）在spark-env.sh中配置：配置master,worker的JavaOptions
3）在spark-submit提交时配置
这里采用以下spark-submit提交时配置：
spark-submit \
--class myTest.KafkaWordCount \
--master yarn \
--deploy-mode cluster \
--conf "spark.executor.extraJavaOptions=-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=0 -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false" \
--verbose \
--executor-memory 1G \
--total-executor-cores \
/hadoop/spark/app/spark//testSpark.jar *.*.*.*:* test3 wordcount kafkawordcount3 checkpoint4
注意：
1）不能指定具体的 ip 和 port------因为spark中运行时，很可能一个节点上分配多个container进程，此时占用同一个端口，会导致spark应用程序通过spark-submit提交失败。
2）因为不指定具体的ip和port，所以在任务提交阶段会自动分配端口。
3）上边三种配置方式可能会导致监控级别不同（比如spark-submit只针对一个应用程序，spark-env.sh可能是全局一个节点所有executor监控【未验证】，请读者注意。）
查找JMX分配端口
通过yarn applicationattempt -list appicationId查找到applicationattemptid
[root@cdh- bin]# yarn applicationattempt -list application_1559203334026_0015
// :: INFO client.RMProxy: Connecting to ResourceManager at CDH-/10.dx.dx.143:
Total number of application attempts :
ApplicationAttempt-Id State AM-Container-Id Tracking-URL
appattempt_1559203334026_0015_000001 RUNNING container_1559203334026_0015_01_000001 http://CDH-143:8088/proxy/application_1559203334026_0015/
通过yarn container -list aaplicationattemptId查找container id list
[root@cdh- bin]# yarn container -list appattempt_1559203334026_0015_000001
// :: INFO client.RMProxy: Connecting to ResourceManager at CDH-/10.dx.dx.143:
Total number of containers :
Container-Id Start Time Finish Time State Host LOG-URL
container_1559203334026_0015_01_000012 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000012/dx
container_1559203334026_0015_01_000013 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000013/dx
container_1559203334026_0015_01_000010 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000010/dx
container_1559203334026_0015_01_000011 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000011/dx
container_1559203334026_0015_01_000016 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000016/dx
container_1559203334026_0015_01_000014 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000014/dx
container_1559203334026_0015_01_000015 Sat Jun :: + N/A RUNNING CDH-: http://CDH-146:8042/node/containerlogs/container_1559203334026_0015_01_000015/dx
container_1559203334026_0015_01_000004 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000004/dx
container_1559203334026_0015_01_000005 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000005/dx
container_1559203334026_0015_01_000002 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000002/dx
container_1559203334026_0015_01_000003 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000003/dx
container_1559203334026_0015_01_000008 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000008/dx
container_1559203334026_0015_01_000009 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000009/dx
container_1559203334026_0015_01_000006 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000006/dx
container_1559203334026_0015_01_000007 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000007/dx
container_1559203334026_0015_01_000001 Sat Jun :: + N/A RUNNING CDH-: http://CDH-142:8042/node/containerlogs/container_1559203334026_0015_01_000001/dx
到具体executor所在节点服务器上，使用如下命令找到运行的线程，和 pid
[root@cdh- ~]# ps -axu | grep container_1559203334026_0015_01_000013
yarn 0.0 0.0 ? S : : bash /data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/default_container_executor.sh
yarn 0.0 0.0 ? Ss : : /bin/bash -c /usr/java/jdk1..0_171-amd64/bin/java -server -Xmx6144m '-Dcom.sun.management.jmxremote' '-Dcom.sun.management.jmxremote.port=0' '-Dcom.sun.management.jmxremote.authenticate=false' '-Dcom.sun.management.jmxremote.ssl=false' -Djava.io.tmpdir=/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/tmp '-Dspark.network.timeout=10000000' '-Dspark.driver.port=47564' '-Dspark.port.maxRetries=32' -Dspark.yarn.app.container.log.dir=/data6/yarn/container-logs/application_1559203334026_0015/container_1559203334026_0015_01_000013 -XX:OnOutOfMemoryError='kill %p' org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@CDH-143:47564 --executor-id 12 --hostname CDH-146 --cores 2 --app-id application_1559203334026_0015 --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/__app__.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/streaming-dx-perf-3.0.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/dx-common-3.0.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/spark-sql-kafka-0-10_2.11-2.4.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/spark-avro_2.11-3.2.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/shc-core-1.1.2-2.2-s_2.11-SNAPSHOT.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/rocksdbjni-5.17.2.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/kafka-clients-0.10.0.1.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/elasticsearch-spark-20_2.11-6.4.1.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/dx_Spark_State_Store_Plugin-1.0-SNAPSHOT.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/bijection-core_2.11-0.9.5.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/bijection-avro_2.11-0.9.5.jar 1>/data6/yarn/container-logs/application_1559203334026_0015/container_1559203334026_0015_01_000013/stdout 2>/data6/yarn/container-logs/application_1559203334026_0015/container_1559203334026_0015_01_000013/stderr
yarn 3.3 ? Sl : : /usr/java/jdk1..0_171-amd64/bin/java -server -Xmx6144m -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port= -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false -Djava.io.tmpdir=/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/tmp -Dspark.network.timeout= -Dspark.driver.port= -Dspark.port.maxRetries= -Dspark.yarn.app.container.log.dir=/data6/yarn/container-logs/application_1559203334026_0015/container_1559203334026_0015_01_000013 -XX:OnOutOfMemoryError=kill %p org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@CDH-143:47564 --executor-id 12 --hostname CDH-146 --cores 2 --app-id application_1559203334026_0015 --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/__app__.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/dx-domain-perf-3.0.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/dx-common-3.0.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/spark-sql-kafka-0-10_2.11-2.4.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/spark-avro_2.11-3.2.0.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/shc-core-1.1.2-2.2-s_2.11-SNAPSHOT.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/rocksdbjni-5.17.2.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/kafka-clients-0.10.0.1.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/elasticsearch-spark-20_2.11-6.4.1.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/dx_Spark_State_Store_Plugin-1.0-SNAPSHOT.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/bijection-core_2.11-0.9.5.jar --user-class-path file:/data6/yarn/nm/usercache/dx/appcache/application_1559203334026_0015/container_1559203334026_0015_01_000013/bijection-avro_2.11-0.9.5.jar
root 0.0 0.0 pts/ S+ : : grep --color=auto container_1559203334026_0015_01_000013
然后通过 pid 找到对应JMX的端口
[root@cdh- ~]# sudo netstat -antp | grep
tcp 10.dx.dx.146: 0.0.0.0:* LISTEN /python2.
tcp6 ::: :::* LISTEN /java
tcp6 ::: :::* LISTEN /java
tcp6 10.dx.dx.146: :::* LISTEN /java
tcp6 10.dx.dx.146: 10.dx.dx.142: ESTABLISHED /java
tcp6 10.dx.dx.146: 10.206.186.35: ESTABLISHED /java
tcp6 10.dx.dx.146: 10.dx.dx.143: ESTABLISHED /java
结果中看，疑似为48169或37692，稍微尝试一下即可连上对应的 spark executor
使用JvisulaVM.exe工具添加监控
在本地windows服务器上找到JDK的目录，找到文件${JAVA_HOME}/bin/JvisualVM.exe，并运行它。启动后选择“远程”右键，添加JMX监控
填写监控executor所在节点ip
然后就可以启动监控：
Spark（五十）：使用JvisualVM监控Spark Executor JVM的更多相关文章
- Spark（五十二）：Spark Scheduler模块之DAGScheduler流程
导入 从一个Job运行过程中来看DAGScheduler是运行在Driver端的,其工作流程如下图: 图中涉及到的词汇概念: 1. RDD——Resillient Distributed Datase ...
- 使用 JvisualVM 监控 spark executor
使用 JvisualVM,需要先配置 java 的启动参数 jmx 正常情况下,如下配置 -Dcom.sun.management.jmxremote -Dcom.sun.management.jmx ...
- Spark2.x（五十五）：在spark structured streaming下sink file(parquet,csv等)，正常运行一段时间后：清理掉checkpoint，重新启动app，无法sink记录（file）到hdfs。
场景: 在spark structured streaming读取kafka上的topic,然后将统计结果写入到hdfs,hdfs保存目录按照month,day,hour进行分区: 1)程序放到spa ...
- Spark2.x（五十九）：yarn-cluster模式提交Spark任务，如何关闭client进程?
问题: 最近现场反馈采用yarn-cluster方式提交spark application后,在提交节点机上依然会存在一个yarn的client进程不关闭,又由于spark application都是 ...
- Spark（四十九）：Spark On YARN启动流程源码分析（一）
引导: 该篇章主要讲解执行spark-submit.sh提交到将任务提交给Yarn阶段代码分析. spark-submit的入口函数 一般提交一个spark作业的方式采用spark-submit来提交 ...
- 监控Spark应用方法简介
监控Spark应用有很多种方法. Web接口每一个SparkContext启动一个web UI用来展示应用相关的一些非常有用的信息,默认在4040端口.这些信息包括: 任务和调度状态的列表RDD大小和 ...
- Spark2.3（四十二）：Spark Streaming和Spark Structured Streaming更新broadcast总结（二）
本次此时是在SPARK2,3 structured streaming下测试,不过这种方案,在spark2.2 structured streaming下应该也可行(请自行测试).以下是我测试结果: ...
- Spark（十四）SparkStreaming的官方文档
一.SparkCore.SparkSQL和SparkStreaming的类似之处 二.SparkStreaming的运行流程 2.1 图解说明 2.2 文字解说 1.我们在集群中的其中一台机器上提交我 ...
- Spark应用监控解决方案--使用Prometheus和Grafana监控Spark应用
Spark任务启动后,我们通常都是通过跳板机去Spark UI界面查看对应任务的信息,一旦任务多了之后,这将会是让人头疼的问题.如果能将所有任务信息集中起来监控,那将会是很完美的事情. 通过Spark ...
随机推荐
- # python04---函数
python04---函数 一. 初识函数 """ def 函数名(参数): 函数体 返回值 """ # def: 定义函数关键字 # 函数 ...
- python（列表函数）
一.列表函数 1.sort()原址排序 参数默认reverse=False时为正序排序 list1 = [1,3,5,2,1,23,18] list1.sort() print (list1) 当参数 ...
- SQL SERVER-查询存储运行状态
SELECT p.name as SPName, qs.last_elapsed_time as [LastExecTime(ms)], (total_elapsed_time as [AvgExec ...
- python之文件的相关操作
一..文件操作的函数 open("文件名(路径)" ,mode = "模式" , encoding="字符集") 注:文件路径: (1)绝对 ...
- python中的exec和eval
exec 描述 exec 执行储存在字符串或文件中的 Python 语句,相比于 eval,exec可以执行更复杂的 Python 代码. 返回值 exec 返回值永远为 None. 需要说明的是在 ...
- 01 浅谈c++及面向对象编程
参考链接: 学习完c++但是对c++面向对象编程还是比较模糊,现在花时间总体来总结一下: c++中的对象是使用类来定义的,下面先重点讲一下类的概念. 说到类就要先说一下类的三种特性:封装,继承,多态. ...
- 2019-2020-1 20199301《Linux内核原理与分析》第五周作业
第四章·系统调用的三层机制(上) 本章的重点在于用户态程序如何触发系统调用? 一.用户.内核.中断 IntelX86有四种不同的执行级别.Linux操作系统中只采用了其中的0和3两个特权级别,分别对应 ...
- 神经网络(8)---如何求神经网络的参数：cost function的表达
两种分类问题: binary & multi-class 下面的是两种类型的分类问题(一种是binary classification,一种是multi-class classificatio ...
- 解决Antimalware Service Executable CPU占用高的问题
windows8/8.1,WIN10自带的安全软件Windows defender还不错,基本可以不用装其他杀毒软件了. 但是其进程Antimalware Service Executable 出现C ...
- Spark Streaming的原理
Spark Streaming应用也是Spark应用,Spark Streaming生成的DStream最终也是会转化成RDD,然后进行RDD的计算,所以Spark Streaming最终的计算是RD ...