让你快速认识flume及安装和使用flume1.5传输数据(日志)到hadoop2.2

转自:http://www.aboutyun.com/thread-7949-1-1.html

问题导读:
1.什么是flume?

2.如何安装flume?
3.flume的配置文件与其它软件有什么不同?






一、认识flume

1.flume是什么?
这里简单介绍一下,它是Cloudera的一个产品
2.flume是干什么的?
收集日志的
3.flume如何搜集日志?
我们把flume比作情报人员
(1)搜集信息
(2)获取记忆信息
(3)传递报告间谍信息
flume是怎么完成上面三件事情的,三个组件:
source: 搜集信息
channel:传递信息
sink:存储信息
上面有点简练,详细可以参考Flume内置channel,source,sink三组件介绍
上面我们认识了,flume。
下面我们来安装flume1.5



二、安装flume1.5


1.下载安装包
(1)官网下载
apache-flume-1.5.0-bin.tar.gz
apache-flume-1.5.0-src.tar.gz
(2)百度网盘下载
链接: http://pan.baidu.com/s/1dDip8RZ 密码: 268r

我们走到这一步,我们会想到一个问题,我的电脑是32位的,不知道能否安装?如果我的电脑是64位的,能否安装。之前我们装的hadoop就分为32位和64位,想到这个问题是正常的,但是这里不用担心,因为我们下载的是二进制包,也就是说你32位和64位都可以安装。

2.分别解压:
下载之后,我们看到下面两个包:
(1)上传Linux
 
上面两个包,可以下载window,然后通过WinSCP,如果不会  新手指导:使用 WinSCP(下载) 上文件到 Linux图文教程
(2)解压包

解压apache-flume-1.5.0-bin.tar.gz, 解压到usr文件夹下面
  1. sudo tar zxvf apache-flume-1.5.0-bin.tar.gz
复制代码
 


解压apache-flume-1.5.0-src.tar.gz, 解压到usr文件夹下面
  1. sudo tar zxvf apache-flume-1.5.0-src.tar.gz
复制代码
 

(3) src里面文件内容,覆盖解压后bin文件里面的内容
  1. sudo cp -ri apache-flume-1.5.0-src/* apache-flume-1.5.0-bin
复制代码
 

(4)重命名
  1. mv apache-flume-1.5.0-bin/ flume
复制代码
 

3.配置环境变量:
 

配置环境变量生效
  1. source /etc/environment
复制代码

3.建立配置文件
这里面的配置文件还是比较特别的,不同于以往我们安装的软件,我们这里可以自己建立配置文件。
首先我们建立一个 example文件
  1. vi example
复制代码

,然后把下面内容,粘帖到里面就可以了,注意不要有乱码,有乱码的话,可以直接创建一个文件,然后上传。方法也有很多,能解决就好。

对于下面红字部分,记得创建文件夹,并且注意他们的权限一致,这个比较简单的,就不在书写了。对于下面的配置项,可以参考 flume参考文档 ,这里面的参数很详细。

agent1表示代理名称
agent1.sources=source1
agent1.sinks=sink1
agent1.channels=channel1


#配置source1
agent1.sources.source1.type=spooldir
agent1.sources.source1.spoolDir= /usr/aboutyunlog
agent1.sources.source1.channels=channel1
agent1.sources.source1.fileHeader = false

#配置sink1
agent1.sinks.sink1.type=hdfs
agent1.sinks.sink1.hdfs.path= hdfs://master:8020/aboutyunlog
agent1.sinks.sink1.hdfs.fileType=DataStream
agent1.sinks.sink1.hdfs.writeFormat=TEXT
agent1.sinks.sink1.hdfs.rollInterval=4
agent1.sinks.sink1.channel=channel1


#配置channel1
agent1.channels.channel1.type=file
agent1.channels.channel1.checkpointDir= /usr/aboutyun_tmp123
agent1.channels.channel1.dataDirs= /usr/aboutyun_tmp

让你快速认识flume及安装和使用flume1.5传输数据(日志)到hadoop2.2_第1张图片 


4.启动flume
flume-ng agent -n agent1 -c conf -f  usr/flume/conf/example  -Dflume.root.logger=DEBUG,console

上面注意红字部分,是我们自己建立的文件,而对于绿色部分,则是输出调试信息,也可以在配置文件中配置。


5.我们启动flume之后
会看到下面信息,并且信息不停的重复。这个其实是在 空文件的时候, 监控的信息输出。
让你快速认识flume及安装和使用flume1.5传输数据(日志)到hadoop2.2_第2张图片 


一旦有文件输入,我们会看到下面信息。
注意:这个不要关闭,我们另外开启一个shell,在监控文件夹中放入要上传的文件

比如我们在监控文件夹下,创建一个test1文件,内容如下
让你快速认识flume及安装和使用flume1.5传输数据(日志)到hadoop2.2_第3张图片 


这时候flume监控shell,会有相应的如下下面变化
2014-06-02 12:01:04,066 (pool-6-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.rollCurrentFile(ReliableSpoolingFileEventReader.java:332)] Preparing to move file /usr/aboutyunlog/test1 to /usr/aboutyunlog/test1.COMPLETED
2014-06-02 12:01:04,070 (pool-6-thread-1) [ERROR - org.apache.flume.source.SpoolDirectorySource$SpoolDirectoryRunnable.run(SpoolDirectorySource.java:256)] FATAL: Spool Directory source source1: { spoolDir: /usr/aboutyunlog }: Uncaught exception in SpoolDirectorySource thread. Restart or reconfigure Flume to continue processing.
java.lang.IllegalStateException: File name has been re-used with different files. Spooling assumptions violated for /usr/aboutyunlog/test1.COMPLETED
at org.apache.flume.client.avro.ReliableSpoolingFileEventReader.rollCurrentFile(ReliableSpoolingFileEventReader.java:362)
at org.apache.flume.client.avro.ReliableSpoolingFileEventReader.retireCurrentFile(ReliableSpoolingFileEventReader.java:314)
at org.apache.flume.client.avro.ReliableSpoolingFileEventReader.readEvents(ReliableSpoolingFileEventReader.java:243)
at org.apache.flume.source.SpoolDirectorySource$SpoolDirectoryRunnable.run(SpoolDirectorySource.java:227)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
2014-06-02 12:01:07,749 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.HDFSDataStream.configure(HDFSDataStream.java:58)] Serializer = TEXT, UseRawLocalFileSystem = false
2014-06-02 12:01:07,803 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:261)] Creating hdfs://master:8020/aboutyunlog/FlumeData.1401681667750.tmp
2014-06-02 12:01:07,871 (hdfs-sink1-call-runner-2) [DEBUG - org.apache.flume.sink.hdfs.AbstractHDFSWriter.reflectGetNumCurrentReplicas(AbstractHDFSWriter.java:195)] Using getNumCurrentReplicas--HDFS-826
2014-06-02 12:01:07,871 (hdfs-sink1-call-runner-2) [DEBUG - org.apache.flume.sink.hdfs.AbstractHDFSWriter.reflectGetDefaultReplication(AbstractHDFSWriter.java:223)] Using FileSystem.getDefaultReplication(Path) from HADOOP-8014
2014-06-02 12:01:10,945 (Log-BackgroundWorker-channel1) [INFO - org.apache.flume.channel.file.EventQueueBackingStoreFile.beginCheckpoint(EventQueueBackingStoreFile.java:214)] Start checkpoint for /usr/aboutyun_tmp123/checkpoint, elements to sync = 3
2014-06-02 12:01:10,949 (Log-BackgroundWorker-channel1) [INFO - org.apache.flume.channel.file.EventQueueBackingStoreFile.checkpoint(EventQueueBackingStoreFile.java:239)] Updating checkpoint metadata: logWriteOrderID: 1401681430998, queueSize: 0, queueHead: 11
2014-06-02 12:01:10,952 (Log-BackgroundWorker-channel1) [INFO - org.apache.flume.channel.file.Log.writeCheckpoint(Log.java:1005)] Updated checkpoint for file: /usr/aboutyun_tmp/log-8 position: 2482 logWriteOrderID: 1401681430998
2014-06-02 12:01:10,953 (Log-BackgroundWorker-channel1) [DEBUG - org.apache.flume.channel.file.Log.removeOldLogs(Log.java:1067)] Files currently in use: [8]
2014-06-02 12:01:11,872 (hdfs-sink1-roll-timer-0) [DEBUG - org.apache.flume.sink.hdfs.BucketWriter$2.call(BucketWriter.java:303)] Rolling file (hdfs://master:8020/aboutyunlog/FlumeData.1401681667750.tmp): Roll scheduled after 4 sec elapsed.
2014-06-02 12:01:11,873 (hdfs-sink1-roll-timer-0) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:409)] Closing hdfs://master:8020/aboutyunlog/FlumeData.1401681667750.tmp
2014-06-02 12:01:11,873 (hdfs-sink1-call-runner-7) [INFO - org.apache.flume.sink.hdfs.BucketWriter$3.call(BucketWriter.java:339)] Close tries incremented
2014-06-02 12:01:11,895 (hdfs-sink1-call-runner-8) [INFO - org.apache.flume.sink.hdfs.BucketWriter$8.call(BucketWriter.java:669)] Renaming hdfs://master:8020/aboutyunlog/FlumeData.1401681667750.tmp to hdfs://master:8020/aboutyunlog/FlumeData.1401681667750
2014-06-02 12:01:11,897 (hdfs-sink1-roll-timer-0) [INFO - org.apache.flume.sink.hdfs.HDFSEventSink$1.run(HDFSEventSink.java:402)] Writer callback called.
2014-06-02 12:01:12,423 (conf-file-poller-0) [DEBUG - org.apache.flume.node.PollingPropertiesFileConfigurationProvider$FileWatcherRunnable.run(PollingPropertiesFileConfigurationProvider.java:126)] Checking file:conf/example for changes
2014-06-02 12:01:40,953 (Log-BackgroundWorker-channel1) [DEBUG - org.apache.flume.channel.file.FlumeEventQueue.checkpoint(FlumeEventQueue.java:137)] Checkpoint not required

上传成功之后,我们去hdfs上,查看上传文件:
 


这样我们做到了flume上传到hadoop2.2。

完毕

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