Ganglia监控Spark

Ganglia是UC Berkeley发起的一个开源集群监视项目，主要是用来监控系统性能，如：cpu 、mem、硬盘利用率， I/O负载、网络流量情况等，通过曲线很容易见到每个节点的工作状态，对合理调整、分配系统资源，提高系统整体性能起到重要作用。

　　由于Licene的限制，没有放到默认的build里面，如果需要使用，需要自己编译。在使用Maven编译Spark的时候，我们可以加上-Pspark-ganglia-lgpl选项来将Ganglia相关的类打包进spark-assembly-x.x.x-hadoopx.x.x.jar中，命令如下：

[iteblog@iteblog spark]$ ./make-distribution.sh --tgz -Phadoop-2.4 -Pyarn -DskipTests 　　-Dhadoop.version=2.4.0 -Pspark-ganglia-lgpl

如果你使用的是SBT来编译，可以加上SPARK_GANGLIA_LGPL=true，完整命令如下：

[iteblog@iteblog spark]$ SPARK_HADOOP_VERSION=2.4.0 SPARK_YARN=true 　　SPARK_GANGLIA_LGPL=true sbt/sbt assembly

或者你在提交作业的时候，单独将Ganglia相关依赖加入到--jars选项中：

--jars lib/spark-ganglia-lgpl_2.10-x.x.x.jar  ...

依赖弄好之后，我们需要在$SPARK_HOME/conf/metrics.properties文件中加入一下配置：

*.sink.ganglia.class=org.apache.spark.metrics.sink.GangliaSink*.sink.ganglia.host=www.iteblog.com*.sink.ganglia.port=8080*.sink.ganglia.period=10*.sink.ganglia.unit=seconds*.sink.ganglia.ttl=1*.sink.ganglia.mode=multicast

host和port这个就是你Ganglia监控的地址，其中mode支持'unicast'(单播) 和 'multicast'(多播)两种模式。
如果你出现类似下面的异常信息：

15/06/11 23:35:14 ERROR MetricsSystem: Sink class org.apache.spark.metrics.sink.GangliaSink cannot be instantialized java.lang.ClassNotFoundException: org.apache.spark.metrics.sink.GangliaSink         at java.net.URLClassLoader$1.run(URLClassLoader.java:366)         at java.net.URLClassLoader$1.run(URLClassLoader.java:355)         at java.security.AccessController.doPrivileged(Native Method)         at java.net.URLClassLoader.findClass(URLClassLoader.java:354)         at java.lang.ClassLoader.loadClass(ClassLoader.java:425)         at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)         at java.lang.ClassLoader.loadClass(ClassLoader.java:358)         at java.lang.Class.forName0(Native Method)         at java.lang.Class.forName(Class.java:191)         at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:138)         at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:134)         at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)         at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)         at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:226)         at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:39)         at scala.collection.mutable.HashMap.foreach(HashMap.scala:98)         at org.apache.spark.metrics.MetricsSystem.registerSinks(MetricsSystem.scala:134)         at org.apache.spark.metrics.MetricsSystem.<init>(MetricsSystem.scala:84)         at org.apache.spark.metrics.MetricsSystem$.createMetricsSystem(MetricsSystem.scala:171)         at org.apache.spark.deploy.worker.Worker.<init>(Worker.scala:106)         at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)         at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)         at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)         at java.lang.reflect.Constructor.newInstance(Constructor.java:526)         at akka.util.Reflect$.instantiate(Reflect.scala:65)         at akka.actor.Props.newActor(Props.scala:337)         at akka.actor.ActorCell.newActor(ActorCell.scala:534)         at akka.actor.ActorCell.create(ActorCell.scala:560)         at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:425)         at akka.actor.ActorCell.systemInvoke(ActorCell.scala:447)         at akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:262)         at akka.dispatch.Mailbox.run(Mailbox.scala:218)         at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)         at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)         at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)         at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)         at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) 

请查看你的Spark包是否将org.apache.spark.metrics.sink.GangliaSink打包进去了；或者仔细看下你的配置文件，请尽量拷贝我这里提供的。
配置弄好之后，启动你的Spark集群，然后去http://IP地址/ganglia-web监控页面查看是否弄好了，类似下面的信息：

除了上图的master.apps 和master.workers 监控，Ganglia里面还显示如下的信息：

{    "version": "3.0.0",     "gauges": {        "jvm.PS-MarkSweep.count": {            "value": 0        },         "jvm.PS-MarkSweep.time": {            "value": 0        },         "jvm.PS-Scavenge.count": {            "value": 186        },         "jvm.PS-Scavenge.time": {            "value": 375        },         "jvm.heap.committed": {            "value": 536412160        },         "jvm.heap.init": {            "value": 536870912        },         "jvm.heap.max": {            "value": 536412160        },         "jvm.heap.usage": {            "value": 0.315636349481712        },         "jvm.heap.used": {            "value": 169311176        },         "jvm.non-heap.committed": {            "value": 37879808        },         "jvm.non-heap.init": {            "value": 24313856        },         "jvm.non-heap.max": {            "value": 184549376        },         "jvm.non-heap.usage": {            "value": 0.19970542734319513        },         "jvm.non-heap.used": {            "value": 36855512        },         "jvm.pools.Code-Cache.usage": {            "value": 0.031689961751302086        },         "jvm.pools.PS-Eden-Space.usage": {            "value": 0.9052384254331968        },         "jvm.pools.PS-Old-Gen.usage": {            "value": 0.02212668565200476        },         "jvm.pools.PS-Perm-Gen.usage": {            "value": 0.26271122694015503        },         "jvm.pools.PS-Survivor-Space.usage": {            "value": 0.5714285714285714        },         "jvm.total.committed": {            "value": 574291968        },         "jvm.total.init": {            "value": 561184768        },         "jvm.total.max": {            "value": 720961536        },         "jvm.total.used": {            "value": 206166688        },         "master.apps": {            "value": 0        },         "master.waitingApps": {            "value": 0        },         "master.workers": {            "value": 0        }    },     "counters": { },     "histograms": { },     "meters": { },     "timers": { }}