我的火花作业是由Oozie在Hue中提交的。火花以纱线群集模式运行。我正在尝试通过所谓的驱动程序的4040端口监视运行的应用程序状态，但是我找不到4040端口，我检查了该过程：
appuser 137872 137870 0 18:55 ? 00:00:00 /bin/bash -c /home/jdk/bin/java -server -Xmx4096m -Djava.io.tmpdir=/data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0547/container_1493800575189_0547_01_000004/tmp '-Dspark.driver.port=36503' '-Dspark.ui.port=0' -Dspark.yarn.app.container.log.dir=/home/log/hadoop/logs/userlogs/application_1493800575189_0547/container_1493800575189_0547_01_000004 -XX:OnOutOfMemoryError='kill %p' org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@10.120.117.107:36503 --executor-id 3 --hostname 10.120.117.100 --cores 1 --app-id application_1493800575189_0547 --user-class-path file:/data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0547/container_1493800575189_0547_01_000004/__app__.jar 1> /home/log/hadoop/logs/userlogs/application_1493800575189_0547/container_1493800575189_0547_01_000004/stdout 2> /home/log/hadoop/logs/userlogs/application_1493800575189_0547/container_1493800575189_0547_01_000004/stderr
appuser 138337 137872 99 18:55 ? 00:05:11 /home/jdk/bin/java -server -Xmx4096m -Djava.io.tmpdir=/data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0547/container_1493800575189_0547_01_000004/tmp -Dspark.driver.port=36503 -Dspark.ui.port=0 -Dspark.yarn.app.container.log.dir=/home/log/hadoop/logs/userlogs/application_1493800575189_0547/container_1493800575189_0547_01_000004 -XX:OnOutOfMemoryError=kill %p org.apache.spark.executor.CoarseGrainedExecutorBackend --driver-url spark://CoarseGrainedScheduler@10.120.117.107:36503 --executor-id 3 --hostname 10.120.117.100 --cores 1 --app-id application_1493800575189_0547 --user-class-path file:/data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0547/container_1493800575189_0547_01_000004/__app__.jar
我不知道为什么spark.ui.port是0而不是4040。当然，我的linux系统不允许端口0。>
有人可以给我一些建议吗？
非常感谢Mariusz的答案，下面是Spark Applicationmaster流程吗？
[appuser@hz-10-120-117-100 bin]$ ps -ef|grep ApplicationMaster
appuser 125805 125803 0 May03 ? 00:00:00 /bin/bash -c /home/jdk/bin/java -server -Xmx1024m -Djava.io.tmpdir=/data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0014/container_1493800575189_0014_01_000001/tmp -Dspark.yarn.app.container.log.dir=/home/log/hadoop/logs/userlogs/application_1493800575189_0014/container_1493800575189_0014_01_000001 org.apache.spark.deploy.yarn.ApplicationMaster --class 'com.netease.ecom.data.gjs.statis.online.app.day.AppDayRealtimeStatis' --jar hdfs://datahdfsmaster/user/appuser/bjmazhengbing/jar/spark_streaming/spark-streaming-etl-2.0.jar --arg 'analysis_gjs_online.properties' --arg 'rrr' --properties-file /data6/data/hadoop/tmp/usercache/appuser/appcache/application_1493800575189_0014/container_1493800575189_0014_01_000001/__spark_conf__/__spark_conf__.properties 1> /home/log/hadoop/logs/userlogs/application_1493800575189_0014/container_1493800575189_0014_01_000001/stdout 2> /home/log/hadoop/logs/userlogs/application_1493800575189_0014/container_1493800575189_0014_01_000001/stderr
根据Spark的官方文件，驱动程序程序应具有4040端口，用于监视，但我的驱动程序程序似乎没有打开任何端口：
[appuser@hz-10-120-117-100 bin]$ netstat -ntlp|grep 125805
(Not all processes could be identified, non-owned process info
will not be shown, you would have to be root to see it all.)
我最终发现驱动程序端口的目的是监视应用程序状态。有任何建议吗？
您列出的过程是执行者，而不是驱动程序。
在yarn-cluster模式下运行应用程序时，Spark Driver和Yarn应用程序Master Master在同一JVM中运行。因此，确定Spark UI地址的最简单方法是转到Recource Manager的UI，查找您的应用程序，然后单击"应用程序主体"链接。这将是代理地址，指向驾驶员的UI端口。