例子参考资料:http://www.aboutyun.com/thread-8917-1-1.html

自定义sink实现和属性注入:http://www.coderli.com/flume-ng-sink-properties/

自定义拦截器:http://blog.csdn.net/xiao_jun_0820/article/details/38333171

自定义kafkasink:www.itnose.net/detail/6187977.html

1. 使用avro发送指定文件

(1)在conf文件夹下创建avro.conf文件,写入如下配置
vim /usr/local/hadoop/apache-flume-1.6.0-bin/conf/avro.conf

a1.sources = r1
a1.sinks = k1
a1.channels = c1 # Describe/configure the source
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = 0.0.0.0
a1.sources.r1.port = 4141 # Describe the sink
a1.sinks.k1.type = logger # Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100 # Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

(2)启动flume agent a1

进入bin执行命令

 ./flume-ng agent -c . -f /usr/local/hadoop/apache-flume-1.6.-bin/conf/avro.conf -n a1 -Dflume.root.logger=INFO,console

(3)创建用于传送的日志文件并写入文字
在/usr/local/hadoop/apache-flume-1.6.0-bin文件夹下创建 log.00 文件,写入"hahahahah"

(4)使用avro-client发送文件
再启动一个控制台,进入bin执行命令

 ./flume-ng avro-client -c . -H localhost -p  -F /usr/local/hadoop/apache-flume-1.6.-bin/log. 

可在控制台1见如下日志,说明已经成功传送

// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: => /127.0.0.1:] OPEN
// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: => /127.0.0.1:] BOUND: /127.0.0.1:
// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: => /127.0.0.1:] CONNECTED: /127.0.0.1:
// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: :> /127.0.0.1:] DISCONNECTED
// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: :> /127.0.0.1:] UNBOUND
// :: INFO ipc.NettyServer: [id: 0xa681f3fa, /127.0.0.1: :> /127.0.0.1:] CLOSED
// :: INFO ipc.NettyServer: Connection to /127.0.0.1: disconnected.
// :: INFO sink.LoggerSink: Event: { headers:{} body: 2E 2F 6C 6D hahahahah ./flum }

2.使用EXEC(监控单个日志文件)

EXEC执行一个给定的命令获得输出的源,如果要使用tail命令,必选使得file足够大才能看到输出内容输出内容

(1)创建agent配置文件,在 /conf 下新建 exec_tail.conf

a1.sources = r1
a1.sinks = k1
a1.channels = c1 # Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.channels = c1
a1.sources.r1.command = tail -F /usr/local/hadoop/apache-flume-1.6.-bin/log_exec_tail
#注意,上面这一行就是要监控的日志文件的位置 # Describe the sink
a1.sinks.k1.type = logger # Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity =
a1.channels.c1.transactionCapacity = # Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

(2)启动flume agent a1
进入bin执行命令

./flume-ng agent -c . -f /usr/local/hadoop/apache-flume-1.6.-bin/conf/exec_tail.conf -n a1 -Dflume.root.logger=INFO,console

(3)创建用于传送的日志文件并写入文字
在/usr/local/hadoop/apache-flume-1.6.0-bin文件夹下创建log_exec_tail文件,并在其中生成足够多的日志

>  for i in {..}; do echo "test line $i" >> /usr/local/hadoop/apache-flume-1.6.-bin/log_exec_tail;  done;

可在控制台1看见如下日志

//前面的省略

// :: INFO sink.LoggerSink: Event: { headers:{} body:      6C  6E                 test line  }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }
// :: INFO sink.LoggerSink: Event: { headers:{} body: 6C 6E test line }

3.使用Spool(监控整个目录)
Spool监测配置的目录下新增的文件,并将文件中的数据读取出来。需要注意两点:
  1) 拷贝到spool目录下的文件不可以再打开编辑。
  2) spool目录下不可包含相应的子目录

(1)在conf文件夹下创建spool.conf文件,写入如下配置
vim /usr/local/hadoop/apache-flume-1.6.0-bin/conf/spool.conf

a1.sources = r1
a1.sinks = k1
a1.channels = c1 # Describe/configure the source
a1.sources.r1.type = spooldir
a1.sources.r1.channels = c1
#要监控的目录(注意 一旦写入这个目录,文件就不能更改)
a1.sources.r1.spoolDir = /usr/local/hadoop/apache-flume-1.6.-bin/logs
a1.sources.r1.fileHeader = true # Describe the sink
a1.sinks.k1.type = logger # Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity =
a1.channels.c1.transactionCapacity = # Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

(2)启动flume agent a1
进入bin执行命令

> ./flume-ng agent -c . -f /usr/local/hadoop/apache-flume-1.6.-bin/conf/spool.conf -n a1 -Dflume.root.logger=INFO,console

(3)向被监控的文件夹下传入日志文件
生成10个文件

> for i in {..}; do echo "test line $i" >> /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text$i.log;  done;

查看控制台,可见如下日志

// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text1.log} body:      6C  6E                   test line  }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text1.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text1.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text10.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text10.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text10.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text2.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text2.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text2.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text3.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text3.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text3.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text4.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text4.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text4.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text5.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text5.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text5.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text6.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text6.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text6.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text7.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text7.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text7.log.COMPLETED
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text8.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text8.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text8.log.COMPLETED
// :: INFO avro.ReliableSpoolingFileEventReader: Last read took us just up to a file boundary. Rolling to the next file, if there is one.
// :: INFO sink.LoggerSink: Event: { headers:{file=/usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text9.log} body: 6C 6E test line }
// :: INFO avro.ReliableSpoolingFileEventReader: Preparing to move file /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text9.log to /usr/local/hadoop/apache-flume-1.6.-bin/logs/spool_text9.log.COMPLETED

注意:发送完毕的日志文件会后缀名会添加“.COMPLETED”

Flume笔记--示例(使用配置文件)的更多相关文章

  1. SpringBoot学习笔记:读取配置文件

    SpringBoot学习笔记:读取配置文件 配置文件 在以往的项目中,我们主要通过XML文件进行框架配置,业务的相关配置会放在属性文件中,然后通过一个属性读取的工具类来读取配置信息.在SpringBo ...

  2. flume使用示例

    flume的特点: flume是一个分布式.可靠.和高可用的海量日志采集.聚合和传输的系统.支持在日志系统中定制各类数据发送方,用于收集数据;同时,Flume提供对数据进行简单处理,并写到各种数据接受 ...

  3. Shell学习笔记 - 环境变量配置文件(转)

    一.source命令 功能:在当前bash环境下读取并执行配置文件中的命令 1. 命令格式 source 配置文件  或  . 配置文件 2. 命令示例 [root@localhost ~]# sou ...

  4. Shell学习笔记 - 环境变量配置文件

    一.source命令 功能:在当前bash环境下读取并执行配置文件中的命令 1. 命令格式 source 配置文件  或  . 配置文件 2. 命令示例 [root@localhost ~]# sou ...

  5. Flume笔记--source端监听目录,sink端上传到HDFS

    官方文档参数解释:http://flume.apache.org/FlumeUserGuide.html#hdfs-sink 需要注意:文件格式,fileType=DataStream 默认为Sequ ...

  6. Spring Boot笔记三:配置文件

    配置文件这里需要讲的东西很多,所以我写在了这里,但是这个是和上篇文章衔接的,所以看这篇文章,先看上篇文章笔记二 一.单独的配置文件 配置文件里面不能都写我们的类的配置吧,这样那么多类太杂了,所以我们写 ...

  7. python学习笔记之读取配置文件【转自https://my.oschina.net/u/3041656/blog/793467】

    [转自https://my.oschina.net/u/3041656/blog/793467] 最近在接触利用python来写测试框架,本人也是个刚接触python,所以是个小菜鸟,今天开始,一点点 ...

  8. Dubbo -- 系统学习 笔记 -- 示例 -- 泛化引用

    Dubbo -- 系统学习 笔记 -- 目录 示例 想完整的运行起来,请参见:快速启动,这里只列出各种场景的配置方式 泛化引用 泛接口调用方式主要用于客户端没有API接口及模型类元的情况,参数及返回值 ...

  9. Dubbo -- 系统学习 笔记 -- 示例 -- 结果缓存

    Dubbo -- 系统学习 笔记 -- 目录 示例 想完整的运行起来,请参见:快速启动,这里只列出各种场景的配置方式 结果缓存 结果缓存,用于加速热门数据的访问速度,Dubbo提供声明式缓存,以减少用 ...

随机推荐

  1. 【转】Android 二维码 生成和识别(附Demo源码)--不错

    原文网址:http://www.cnblogs.com/mythou/p/3280023.html 今天讲一下目前移动领域很常用的技术——二维码.现在大街小巷.各大网站都有二维码的踪迹,不管是IOS. ...

  2. (转载)python多行注释

    (转载)http://www.cnblogs.com/pylemon/archive/2011/05/23/2054090.html python本身不带多行注释,编辑时每行敲一个“#”相当的不方便, ...

  3. 【性能测试】【Jmeter】学习(2)——录制一段脚本

    打开JMeter工具,录制一段脚本(我做的是录制登陆网站后点击设备的开关设定,然后再退出) 1).创建一个线程组(右键点击“测试计划”--->“添加”---->“线程组”) 2).添加录制 ...

  4. 用SQL求1到N的质数和

    今天在百度知道中,遇到了一位朋友求助:利用sql求1到1000的质数和.再说今天周五下午比较悠闲,我就在MSSQL 2008中写了出来,现在分享在博客中,下面直接贴代码: declare @num i ...

  5. 《Linear Algebra and Its Applications》-chaper1-线性方程组-线性相关性

    这篇文章主要简单的记录所谓的“线性相关性”. 线性相关性的对象是向量R^n,对于向量方程,如果说x1v1 + x2v2 + …+xmvm = 0(其中xi是常数,vi是向量)有且仅有一个平凡解,那么我 ...

  6. Swift基础语法学习总结二

    1.函数 1.1 func funcNmae()->(){} 这样就定义了一个函数,它的参数为空,返回值为空,如果有参数和返回值直接写在两个括号里就可以了 1.2 参数需要指明类型,而如果没有返 ...

  7. Jenkins 初见

    在网上貌似没有找到Jenkins的中文的太多的文档,有的都是关于Hudson的一些 零零散散的,所以自己边学习边实践总结了以下系列文章,希望有助于大家对于Jenkins的使用. 本系列文章是基于我3年 ...

  8. JAVA设计模式(09):结构型-代理模式(Proxy)

    代理模式是经常使用的结构型设计模式之中的一个,当无法直接訪问某个对象或訪问某个对象存在困难时能够通过一个代理对象来间接訪问,为了保证client使用的透明性,所訪问的真实对象与代理对象须要实现同样的接 ...

  9. UITableView的编辑(插入、删除、移动)

    先说两个方法beginUpdates和endUpdates,几点注意事项: 一般我们把行.块的插入.删除.移动写在由这两个方法组成的函数块中.如果你不是在这两个函数组成的块中调用插入.删除.移动方法, ...

  10. [转] 智能指针(三):unique_ptr使用简介

    PS: 1. auto_ptr太不安全,可能多个auto_ptr指向一个对象,出现重复释放的问题 2. unique_ptr解决了这个问题,不允许拷贝构造函数和赋值操作符,但是!它支持移动构造函数,通 ...