Groovy-JMX

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JMX 是事实上的标准，用于监视与 Java 虚拟环境有关的所有应用程序。鉴于 Groovy 直接位于 Java 之上，Groovy 可以利用 Java 中已经为 JMX 所做的大量工作。

监控 JVM

可以使用 java.lang.management 中提供的标准类来执行 JVM 的监视。以下代码示例展示了如何完成此操作。

import java.lang.management.*

def os = ManagementFactory.operatingSystemMXBean 
println """OPERATING SYSTEM: 
\tOS architecture = $os.arch 
\tOS name = $os.name 
\tOS version = $os.version 
\tOS processors = $os.availableProcessors 
""" 
 
def rt = ManagementFactory.runtimeMXBean 
println """RUNTIME: 
   \tRuntime name = $rt.name 
   \tRuntime spec name = $rt.specName 
   \tRuntime vendor = $rt.specVendor 
   \tRuntime spec version = $rt.specVersion 
   \tRuntime management spec version = $rt.managementSpecVersion 
   """ 

def mem = ManagementFactory.memoryMXBean 
def heapUsage = mem.heapMemoryUsage 
def nonHeapUsage = mem.nonHeapMemoryUsage 

println """MEMORY: 
   HEAP STORAGE: 
      \tMemory committed = $heapUsage.committed 
      \tMemory init = $heapUsage.init 
      \tMemory max = $heapUsage.max 
      \tMemory used = $heapUsage.used NON-HEAP STORAGE: 
      \tNon-heap memory committed = $nonHeapUsage.committed 
      \tNon-heap memory init = $nonHeapUsage.init 
      \tNon-heap memory max = $nonHeapUsage.max 
      \tNon-heap memory used = $nonHeapUsage.used 
   """
  
println "GARBAGE COLLECTION:" 
ManagementFactory.garbageCollectorMXBeans.each { gc ->
   println "\tname = $gc.name"
   println "\t\tcollection count = $gc.collectionCount"
   println "\t\tcollection time = $gc.collectionTime"
   String[] mpoolNames =   gc.memoryPoolNames
	
   mpoolNames.each { 
      mpoolName -> println "\t\tmpool name = $mpoolName"
   } 
}

执行代码时，输​​出将根据运行代码的系统而有所不同。下面给出了输出示例。

OPERATING SYSTEM: 
   OS architecture = x86 
   OS name = Windows 7 
   OS version = 6.1 
   OS processors = 4
   
RUNTIME: 
   Runtime name = 5144@Babuli-PC 
   Runtime spec name = Java Virtual Machine Specification 
   Runtime vendor = Oracle Corporation 
   Runtime spec version = 1.7 
   Runtime management spec version = 1.2
   
MEMORY: 
   HEAP STORAGE: 
      Memory committed = 16252928 
      Memory init = 16777216 
      Memory max = 259522560 
      Memory used = 7355840
   
NON-HEAP STORAGE: 
   Non-heap memory committed = 37715968 
   Non-heap memory init = 35815424 
   Non-heap memory max = 123731968 
   Non-heap memory used = 18532232 
   
GARBAGE COLLECTION: 
   name = Copy 
   collection count = 15 
   collection time = 47 
   mpool name = Eden Space 
   mpool name = Survivor Space
		
   name = MarkSweepCompact 
      collection count = 0 
      collection time = 0 
		
      mpool name = Eden Space 
      mpool name = Survivor Space 
      mpool name = Tenured Gen 
      mpool name = Perm Gen 
      mpool name = Perm Gen [shared-ro] 
      mpool name = Perm Gen [shared-rw]

监控Tomcat

为了监控 tomcat，启动 tomcat 时应设置以下参数 -

set JAVA_OPTS = -Dcom.sun.management.jmxremote 
Dcom.sun.management.jmxremote.port = 9004\
 
-Dcom.sun.management.jmxremote.authenticate=false 
Dcom.sun.management.jmxremote.ssl = false

以下代码使用 JMX 来发现正在运行的 Tomcat 中的可用 MBean，确定哪些是 Web 模块并提取每个 Web 模块的处理时间。

import groovy.swing.SwingBuilder
  
import javax.management.ObjectName 
import javax.management.remote.JMXConnectorFactory as JmxFactory 
import javax.management.remote.JMXServiceURL as JmxUrl 
import javax.swing.WindowConstants as WC 
 
import org.jfree.chart.ChartFactory 
import org.jfree.data.category.DefaultCategoryDataset as Dataset 
import org.jfree.chart.plot.PlotOrientation as Orientation 
 
def serverUrl = 'service:jmx:rmi:///jndi/rmi://localhost:9004/jmxrmi' 
def server = JmxFactory.connect(new JmxUrl(serverUrl)).MBeanServerConnection 
def serverInfo = new GroovyMBean(server, 'Catalina:type = Server').serverInfo 
println "Connected to: $serverInfo" 
 
def query = new ObjectName('Catalina:*') 
String[] allNames = server.queryNames(query, null) 

def modules = allNames.findAll { name -> 
   name.contains('j2eeType=WebModule') 
}.collect{ new GroovyMBean(server, it) }
  
println "Found ${modules.size()} web modules. Processing ..." 
def dataset = new Dataset() 
 
modules.each { m ->
   println m.name()
   dataset.addValue m.processingTime, 0, m.path 
}