Flume的安装及使用

Flume的安装

1、上传至虚拟机，并解压
tar -zxvf apache-flume-1.6.0-bin.tar.gz -C /usr/local/soft/

在环境变量中增加如下命令，可以使用 soft 快速切换到 /usr/local/soft

alias soft=‘cd /usr/local/soft/’

2、重命名目录，并配置环境变量
mv apache-flume-1.6.0-bin/ flume-1.6.0
vim /etc/profile
source /etc/profile
3、查看flume版本
flume-ng version
[root@master soft]# flume-ng version
Flume 1.6.0
Source code repository: https://git-wip-us.apache.org/repos/asf/flume.git
Revision: 2561a23240a71ba20bf288c7c2cda88f443c2080
Compiled by hshreedharan on Mon May 11 11:15:44 PDT 2015
From source with checksum b29e416802ce9ece3269d34233baf43f
[root@master soft]#
4、测试flume
  • 监控一个目录，将数据打印出来
  • 配置文件
# a表示给agent命名为a
  # 给source组件命名为r1
  a.sources = r1
  # 给sink组件命名为k1
  a.sinks = k1 
  # 给channel组件命名为c1
  a.channels = c1
  #指定spooldir的属性
  a.sources.r1.type = spooldir 
  a.sources.r1.spoolDir = /root/data 
  a.sources.r1.fileHeader = true 
  a.sources.r1.interceptors = i1 
  a.sources.r1.interceptors.i1.type = timestamp
  #指定sink的类型
  a.sinks.k1.type = logger
  #指定channel
  a.channels.c1.type = memory 
  a.channels.c1.capacity = 1000
  # 表示sink每次会从channel里取多少数据
  a.channels.c1.transactionCapacity = 100
  # 组装
  a.sources.r1.channels = c1 
  a.sinks.k1.channel = c1
  • 启动agent
flume-ng agent -n a -f ./spoolingtest.conf -Dflume.root.logger=DEBUG,console
  • 新建/root/data目录
mkdir /root/data
  • 在/root/data/目录下新建文件，输入内容，观察flume进程打印的日志
# 随意在a.txt中加入一些内容
vim /root/data/a.txt
5、flume的使用
  • spoolingToHDFS.conf
  • 配置文件
# a表示给agent命名为a
# 给source组件命名为r1
a.sources = r1
# 给sink组件命名为k1
a.sinks = k1 
# 给channel组件命名为c1
a.channels = c1
#指定spooldir的属性
a.sources.r1.type = spooldir 
a.sources.r1.spoolDir = /root/data 
a.sources.r1.fileHeader = true 
a.sources.r1.interceptors = i1 
a.sources.r1.interceptors.i1.type = timestamp
#指定sink的类型
a.sinks.k1.type = hdfs
a.sinks.k1.hdfs.path = /flume/data/dir1
# 指定文件名前缀
a.sinks.k1.hdfs.filePrefix = student
# 指定达到多少数据量写一次文件 单位：bytes
a.sinks.k1.hdfs.rollSize = 102400
# 指定多少条写一次文件
a.sinks.k1.hdfs.rollCount = 1000
# 指定文件类型为 流 来什么输出什么
a.sinks.k1.hdfs.fileType = DataStream
# 指定文件输出格式 为text
a.sinks.k1.hdfs.writeFormat = text
# 指定文件名后缀
a.sinks.k1.hdfs.fileSuffix = .txt

#指定channel
a.channels.c1.type = memory 
a.channels.c1.capacity = 1000
# 表示sink每次会从channel里取多少数据
a.channels.c1.transactionCapacity = 100
# 组装
a.sources.r1.channels = c1 
a.sinks.k1.channel = c1
  • 在 /root/data/目录下准备数据
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
  • 启动agent
flume-ng agent -n a -f ./spoolingToHDFS.conf -Dflume.root.logger=DEBUG,console
  • hbaseLogToHDFS
  • 配置文件
# a表示给agent命名为a
# 给source组件命名为r1
a.sources = r1
# 给sink组件命名为k1
a.sinks = k1 
# 给channel组件命名为c1
a.channels = c1
#指定spooldir的属性
a.sources.r1.type = exec 
a.sources.r1.command = tail -f /usr/local/soft/hbase-1.4.6/logs/hbase-root-master-master.log
#指定sink的类型
a.sinks.k1.type = hdfs
a.sinks.k1.hdfs.path = /flume/data/dir2
# 指定文件名前缀
a.sinks.k1.hdfs.filePrefix = hbaselog
# 指定达到多少数据量写一次文件 单位：bytes
a.sinks.k1.hdfs.rollSize = 102400
# 指定多少条写一次文件
a.sinks.k1.hdfs.rollCount = 1000
# 指定文件类型为 流 来什么输出什么
a.sinks.k1.hdfs.fileType = DataStream
# 指定文件输出格式 为text
a.sinks.k1.hdfs.writeFormat = text
# 指定文件名后缀
a.sinks.k1.hdfs.fileSuffix = .txt

#指定channel
a.channels.c1.type = memory 
a.channels.c1.capacity = 1000
# 表示sink每次会从channel里取多少数据
a.channels.c1.transactionCapacity = 100
# 组装
a.sources.r1.channels = c1 
a.sinks.k1.channel = c1
  • hbaselogToHBase
  • 在hbase中创建log表
create 'log','cf1'
  • 配置文件
# a表示给agent命名为a
# 给source组件命名为r1
a.sources = r1
# 给sink组件命名为k1
a.sinks = k1 
# 给channel组件命名为c1
a.channels = c1
#指定spooldir的属性
a.sources.r1.type = exec 
a.sources.r1.command = cat /usr/local/soft/hbase-1.4.6/logs/hbase-root-master-master.log
#指定sink的类型
a.sinks.k1.type = hbase
a.sinks.k1.table = log
a.sinks.k1.columnFamily = cf1

#指定channel
a.channels.c1.type = memory 
a.channels.c1.capacity = 100000
# 表示sink每次会从channel里取多少数据
a.channels.c1.transactionCapacity = 100
# 组装
a.sources.r1.channels = c1 
a.sinks.k1.channel = c1
  • netcatLogger

监听telnet端口

  • 安装telnet
yum install yum install telnet
  • 配置文件
# a表示给agent命名为a
# 给source组件命名为r1
a.sources = r1
# 给sink组件命名为k1
a.sinks = k1 
# 给channel组件命名为c1
a.channels = c1
#指定spooldir的属性
a.sources.r1.type = netcat 
a.sources.r1.bind = 0.0.0.0 
a.sources.r1.port = 8888 

#指定sink的类型
a.sinks.k1.type = logger
#指定channel
a.channels.c1.type = memory 
a.channels.c1.capacity = 1000
# 表示sink每次会从channel里取多少数据
a.channels.c1.transactionCapacity = 100
# 组装
a.sources.r1.channels = c1 
a.sinks.k1.channel = c1
  • 启动
  • 先启动agent
flume-ng agent -n a -f ./netcatToLogger.conf -Dflume.root.logger=DEBUG,console
  • 在启动telnet
telnet master 8888
  • httpToLogger
  • 配置文件
# a表示给agent命名为a
# 给source组件命名为r1
a.sources = r1
# 给sink组件命名为k1
a.sinks = k1 
# 给channel组件命名为c1
a.channels = c1
#指定spooldir的属性
a.sources.r1.type = http 
a.sources.r1.port = 8888 

#指定sink的类型
a.sinks.k1.type = logger
#指定channel
a.channels.c1.type = memory 
a.channels.c1.capacity = 1000
# 表示sink每次会从channel里取多少数据
a.channels.c1.transactionCapacity = 100
# 组装
a.sources.r1.channels = c1 
a.sinks.k1.channel = c1
  • 启动
  • 先启动agent
flume-ng agent -n a -f ./httpToLogger.conf -Dflume.root.logger=DEBUG,console
  • 再使用curl发起一个http请求
curl -X POST -d '[{ "headers" :{"a" : "a1","b" : "b1"},"body" : "hello~http~flume~"}]' http://master:8888