一百八十五、外部工具

外部工具

tail

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tail是命令行工具,可以让您查看文件的末尾。添加-f选项,当新数据可用时,它将刷新。当你想知道发生了什么时,这很有用,例如,当一个集群需要很长时间才能关闭或启动时,因为你可以触发一个新的终端并跟踪主日志(可能还有一些RegionServers)。

top

在第一次尝试查看计算机上运行的内容以及如何使用资源时,top可能是最重要的工具之一。这是生产系统的一个例子:

top - 14:46:59 up 39 days, 11:55,  1 user,  load average: 3.75, 3.57, 3.84
Tasks: 309 total,   1 running, 308 sleeping,   0 stopped,   0 zombie
Cpu(s):  4.5%us,  1.6%sy,  0.0%ni, 91.7%id,  1.4%wa,  0.1%hi,  0.6%si,  0.0%st
Mem:  24414432k total, 24296956k used,   117476k free,     7196k buffers
Swap: 16008732k total,        14348k used, 15994384k free, 11106908k cached
  PID USER          PR  NI  VIRT  RES  SHR S %CPU %MEM        TIME+  COMMAND
15558 hadoop        18  -2 3292m 2.4g 3556 S   79 10.4   6523:52 java
13268 hadoop        18  -2 8967m 8.2g 4104 S   21 35.1   5170:30 java
 8895 hadoop        18  -2 1581m 497m 3420 S   11  2.1   4002:32 java

在这里我们可以看到在过去五分钟内的系统平均负载是3.75,这非常粗略地意味着在这5分钟内平均有3.75个线程在等待CPU时间。通常,完美的利用率等于内核的数量,在该数量下机器未得到充分利用,并且超过此数量,机器被过度利用。这是一个重要的概念,请参阅此文章以了解更多信息:http://www.linuxjournal.com/article/9001。

除了负载之外,我们可以看到系统几乎使用了所有可用的RAM,但大部分用于OS缓存(这很好)。交换只有几KB,这是需要的,高数字表示交换活动,这是Java系统性能的克星。另一种检测交换的方法是当负载平均值通过roof时(尽管这也可能是由死磁盘等引起的)。

默认情况下,进程列表并不是非常有用,我们所知道的是3个java进程正在使用大约111%的CPU。要知道哪个是哪个,只需键入c,并扩展每一行。键入1将为您提供每个CPU的使用方式的详细信息,而不是所有CPU的平均值,如此处所示。

JPS

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jps随每个JDK一起提供,并为当前用户提供java进程ID(如果是root,则为所有用户提供id)。例:

hadoop@sv4borg12:~$ jps
1322 TaskTracker
17789 HRegionServer
27862 Child
1158 DataNode
25115 HQuorumPeer
2950 Jps
19750 ThriftServer
18776 jmx

按顺序,我们看到:

  • Hadoop TaskTracker管理当地的Childs
  • HBase RegionServer服务于区域
  • Child,它的MapReduce任务,无法确切地分辨出哪种类型
  • Hadoop TaskTracker管理当地的Childs
  • Hadoop DataNode服务块
  • HQorumPeer,ZooKeeper组成成员
  • Jps,是当前的过程
  • ThriftServer,它是一个特殊的将只在启动thrift时运行
  • jmx,这是一个本地进程,它是我们监控平台的一部分,你可能没有。

然后,您可以执行诸如检出启动该过程的完整命令行之类的操作:

hadoop@sv4borg12:~$ ps aux | grep HRegionServer
hadoop   17789  155 35.2 9067824 8604364 ?     S<l  Mar04 9855:48 /usr/java/jdk1.6.0_14/bin/java -Xmx8000m -XX:+DoEscapeAnalysis -XX:+AggressiveOpts -XX:+UseConcMarkSweepGC -XX:NewSize=64m -XX:MaxNewSize=64m -XX:CMSInitiatingOccupancyFraction=88 -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -Xloggc:/export1/hadoop/logs/gc-hbase.log -Dcom.sun.management.jmxremote.port=10102 -Dcom.sun.management.jmxremote.authenticate=true -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.password.file=/home/hadoop/hbase/conf/jmxremote.password -Dcom.sun.management.jmxremote -Dhbase.log.dir=/export1/hadoop/logs -Dhbase.log.file=hbase-hadoop-regionserver-sv4borg12.log -Dhbase.home.dir=/home/hadoop/hbase -Dhbase.id.str=hadoop -Dhbase.root.logger=INFO,DRFA -Djava.library.path=/home/hadoop/hbase/lib/native/Linux-amd64-64 -classpath /home/hadoop/hbase/bin/../conf:[many jars]:/home/hadoop/hadoop/conf org.apache.hadoop.hbase.regionserver.HRegionServer start

jstack

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jstack在尝试找出除了查看日志之外,java进程正在做什么,它是最重要的工具之一。它必须与jps一起使用才能为其提供进程ID。它显示了一个线程列表,每个线程都有一个名称,它们按照创建的顺序出现(所以最顶层的线程是最新的线程)。以下是一些示例:

RegionServer的主线程等待主服务器执行的操作:

"regionserver60020" prio=10 tid=0x0000000040ab4000 nid=0x45cf waiting on condition [0x00007f16b6a96000..0x00007f16b6a96a70]
java.lang.Thread.State: TIMED_WAITING (parking)
    at sun.misc.Unsafe.park(Native Method)
    - parking to wait for  <0x00007f16cd5c2f30> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
    at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:198)
    at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:1963)
    at java.util.concurrent.LinkedBlockingQueue.poll(LinkedBlockingQueue.java:395)
    at org.apache.hadoop.hbase.regionserver.HRegionServer.run(HRegionServer.java:647)
    at java.lang.Thread.run(Thread.java:619)

当前正在刷新到文件的MemStore刷新线程:

"regionserver60020.cacheFlusher" daemon prio=10 tid=0x0000000040f4e000 nid=0x45eb in Object.wait() [0x00007f16b5b86000..0x00007f16b5b87af0]
java.lang.Thread.State: WAITING (on object monitor)
    at java.lang.Object.wait(Native Method)
    at java.lang.Object.wait(Object.java:485)
    at org.apache.hadoop.ipc.Client.call(Client.java:803)
    - locked <0x00007f16cb14b3a8> (a org.apache.hadoop.ipc.Client$Call)
    at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:221)
    at $Proxy1.complete(Unknown Source)
    at sun.reflect.GeneratedMethodAccessor38.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
    at java.lang.reflect.Method.invoke(Method.java:597)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:82)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:59)
    at $Proxy1.complete(Unknown Source)
    at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.closeInternal(DFSClient.java:3390)
    - locked <0x00007f16cb14b470> (a org.apache.hadoop.hdfs.DFSClient$DFSOutputStream)
    at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.close(DFSClient.java:3304)
    at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:61)
    at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:86)
    at org.apache.hadoop.hbase.io.hfile.HFile$Writer.close(HFile.java:650)
    at org.apache.hadoop.hbase.regionserver.StoreFile$Writer.close(StoreFile.java:853)
    at org.apache.hadoop.hbase.regionserver.Store.internalFlushCache(Store.java:467)
    - locked <0x00007f16d00e6f08> (a java.lang.Object)
    at org.apache.hadoop.hbase.regionserver.Store.flushCache(Store.java:427)
    at org.apache.hadoop.hbase.regionserver.Store.access$100(Store.java:80)
    at org.apache.hadoop.hbase.regionserver.Store$StoreFlusherImpl.flushCache(Store.java:1359)
    at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:907)
    at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:834)
    at org.apache.hadoop.hbase.regionserver.HRegion.flushcache(HRegion.java:786)
    at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:250)
    at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:224)
    at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.run(MemStoreFlusher.java:146)

一个处理程序线程正在等待要做的事情(如put,delete,scan等):

"IPC Server handler 16 on 60020" daemon prio=10 tid=0x00007f16b011d800 nid=0x4a5e waiting on condition [0x00007f16afefd000..0x00007f16afefd9f0]
   java.lang.Thread.State: WAITING (parking)
          at sun.misc.Unsafe.park(Native Method)
          - parking to wait for  <0x00007f16cd3f8dd8> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
          at java.util.concurrent.locks.LockSupport.park(LockSupport.java:158)
          at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:1925)
          at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:358)
          at org.apache.hadoop.hbase.ipc.HBaseServer$Handler.run(HBaseServer.java:1013)

还有一个正在忙着增加一个计数器(它正处于尝试创建扫描器以读取最后一个值的阶段):

"IPC Server handler 66 on 60020" daemon prio=10 tid=0x00007f16b006e800 nid=0x4a90 runnable [0x00007f16acb77000..0x00007f16acb77cf0]
   java.lang.Thread.State: RUNNABLE
          at org.apache.hadoop.hbase.regionserver.KeyValueHeap.<init>(KeyValueHeap.java:56)
          at org.apache.hadoop.hbase.regionserver.StoreScanner.<init>(StoreScanner.java:79)
          at org.apache.hadoop.hbase.regionserver.Store.getScanner(Store.java:1202)
          at org.apache.hadoop.hbase.regionserver.HRegion$RegionScanner.<init>(HRegion.java:2209)
          at org.apache.hadoop.hbase.regionserver.HRegion.instantiateInternalScanner(HRegion.java:1063)
          at org.apache.hadoop.hbase.regionserver.HRegion.getScanner(HRegion.java:1055)
          at org.apache.hadoop.hbase.regionserver.HRegion.getScanner(HRegion.java:1039)
          at org.apache.hadoop.hbase.regionserver.HRegion.getLastIncrement(HRegion.java:2875)
          at org.apache.hadoop.hbase.regionserver.HRegion.incrementColumnValue(HRegion.java:2978)
          at org.apache.hadoop.hbase.regionserver.HRegionServer.incrementColumnValue(HRegionServer.java:2433)
          at sun.reflect.GeneratedMethodAccessor20.invoke(Unknown Source)
          at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
          at java.lang.reflect.Method.invoke(Method.java:597)
          at org.apache.hadoop.hbase.ipc.HBaseRPC$Server.call(HBaseRPC.java:560)
          at org.apache.hadoop.hbase.ipc.HBaseServer$Handler.run(HBaseServer.java:1027)

从HDFS接收数据的线程:

"IPC Client (47) connection to sv4borg9/10.4.24.40:9000 from hadoop" daemon prio=10 tid=0x00007f16a02d0000 nid=0x4fa3 runnable [0x00007f16b517d000..0x00007f16b517dbf0]
   java.lang.Thread.State: RUNNABLE
          at sun.nio.ch.EPollArrayWrapper.epollWait(Native Method)
          at sun.nio.ch.EPollArrayWrapper.poll(EPollArrayWrapper.java:215)
          at sun.nio.ch.EPollSelectorImpl.doSelect(EPollSelectorImpl.java:65)
          at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:69)
          - locked <0x00007f17d5b68c00> (a sun.nio.ch.Util$1)
          - locked <0x00007f17d5b68be8> (a java.util.Collections$UnmodifiableSet)
          - locked <0x00007f1877959b50> (a sun.nio.ch.EPollSelectorImpl)
          at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:80)
          at org.apache.hadoop.net.SocketIOWithTimeout$SelectorPool.select(SocketIOWithTimeout.java:332)
          at org.apache.hadoop.net.SocketIOWithTimeout.doIO(SocketIOWithTimeout.java:157)
          at org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:155)
          at org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:128)
          at java.io.FilterInputStream.read(FilterInputStream.java:116)
          at org.apache.hadoop.ipc.Client$Connection$PingInputStream.read(Client.java:304)
          at java.io.BufferedInputStream.fill(BufferedInputStream.java:218)
          at java.io.BufferedInputStream.read(BufferedInputStream.java:237)
          - locked <0x00007f1808539178> (a java.io.BufferedInputStream)
          at java.io.DataInputStream.readInt(DataInputStream.java:370)
          at org.apache.hadoop.ipc.Client$Connection.receiveResponse(Client.java:569)
          at org.apache.hadoop.ipc.Client$Connection.run(Client.java:477)

这是一个master试图在RegionServer死后恢复lease:

"LeaseChecker" daemon prio=10 tid=0x00000000407ef800 nid=0x76cd waiting on condition [0x00007f6d0eae2000..0x00007f6d0eae2a70]
--
   java.lang.Thread.State: WAITING (on object monitor)
          at java.lang.Object.wait(Native Method)
          at java.lang.Object.wait(Object.java:485)
          at org.apache.hadoop.ipc.Client.call(Client.java:726)
          - locked <0x00007f6d1cd28f80> (a org.apache.hadoop.ipc.Client$Call)
          at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:220)
          at $Proxy1.recoverBlock(Unknown Source)
          at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.processDatanodeError(DFSClient.java:2636)
          at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.<init>(DFSClient.java:2832)
          at org.apache.hadoop.hdfs.DFSClient.append(DFSClient.java:529)
          at org.apache.hadoop.hdfs.DistributedFileSystem.append(DistributedFileSystem.java:186)
          at org.apache.hadoop.fs.FileSystem.append(FileSystem.java:530)
          at org.apache.hadoop.hbase.util.FSUtils.recoverFileLease(FSUtils.java:619)
          at org.apache.hadoop.hbase.regionserver.wal.HLog.splitLog(HLog.java:1322)
          at org.apache.hadoop.hbase.regionserver.wal.HLog.splitLog(HLog.java:1210)
          at org.apache.hadoop.hbase.master.HMaster.splitLogAfterStartup(HMaster.java:648)
          at org.apache.hadoop.hbase.master.HMaster.joinCluster(HMaster.java:572)
          at org.apache.hadoop.hbase.master.HMaster.run(HMaster.java:503)

OpenTSDB

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OpenTSDB是Ganglia的绝佳替代品,因为它使用Apache HBase存储所有时间序列,而不必向下采样。监控您的包含OpenTSDB的HBase集群是一个很好的练习。

这是一个集群的例子,它几乎同时发生了数百个压缩,这严重影响了IO性能:( TODO:插入图表绘制compactionQueueSize)

建立仪表板是一个很好的做法,每个机器和每个集群都包含所有重要的图表,因此只需一个快速查看就可以完成调试问题。例如,在StumbleUpon上,每个集群有一个仪表板,其中包含来自操作系统和Apache HBase的最重要指标。然后,您可以在机器级别下载并获得更详细的指标。

clusterssh +top

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clusterssh + top,它就像一个穷人的监控系统,当你只有几台机器时,它非常有用,因为它很容易设置。启动clusterssh将为每台机器提供一个终端,而在另一个终端中,您键入的任何内容都将在每个窗口中重新键入。这意味着您可以键入top一次,同时为所有计算机启动它,同时为您提供群集当前状态的完整视图。您还可以同时拖尾所有日志,编辑文件等。

文章永久链接:https://ddkk.com/?p=12340