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

用户1410343

发布于 2018-03-27 10:13:54

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发布于 2018-03-27 10:13:54

文章被收录于专栏：about云

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

sudo tar zxvf apache-flume-1.5.0-bin.tar.gz

解压apache-flume-1.5.0-src.tar.gz，解压到usr文件夹下面

sudo tar zxvf apache-flume-1.5.0-src.tar.gz

(3) src里面文件内容，覆盖解压后bin文件里面的内容

sudo cp -ri apache-flume-1.5.0-src/* apache-flume-1.5.0-bin

(4)重命名

mv apache-flume-1.5.0-bin/ flume

3.配置环境变量：

配置环境变量生效

source /etc/environment

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

vi example

，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

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。

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

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：