尚硅谷大数据技术之Flume(新)第3章 企业开发案例

发布时间:2018年11月01日作者:yafei浏览次数:969

3.6 多数据源汇总案例

多Source汇总数据到单Flume如图7-4所示。

  • 案例需求:

hadoop103上的Flume-1监控文件/opt/module/group.log,

hadoop102上的Flume-2监控某一个端口的数据流,

Flume-1与Flume-2将数据发送给hadoop104上的Flume-3,Flume-3将最终数据打印到控制台。

2)需求分析:

 

3)实现步骤:

0.准备工作

分发Flume

[atguigu@hadoop102 module]$ xsync flume

在hadoop102、hadoop103以及hadoop104的/opt/module/flume/job目录下创建一个group3文件夹。

[atguigu@hadoop102 job]$ mkdir group3

[atguigu@hadoop103 job]$ mkdir group3

[atguigu@hadoop104 job]$ mkdir group3

1.创建flume1-logger-flume.conf

配置Source用于监控hive.log文件,配置Sink输出数据到下一级Flume。

在hadoop103上创建配置文件并打开

[atguigu@hadoop103 group3]$ touch flume1-logger-flume.conf

[atguigu@hadoop103 group3]$ vim flume1-logger-flume.conf

添加如下内容

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

 

# Describe/configure the source

a1.sources.r1.type = exec

a1.sources.r1.command = tail -F /opt/module/group.log

a1.sources.r1.shell = /bin/bash -c

 

# Describe the sink

a1.sinks.k1.type = avro

a1.sinks.k1.hostname = hadoop104

a1.sinks.k1.port = 4141

 

# Describe the channel

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.创建flume2-netcat-flume.conf

配置Source监控端口44444数据流,配置Sink数据到下一级Flume:

在hadoop102上创建配置文件并打开

[atguigu@hadoop102 group3]$ touch flume2-netcat-flume.conf

[atguigu@hadoop102 group3]$ vim flume2-netcat-flume.conf

添加如下内容

# Name the components on this agent

a2.sources = r1

a2.sinks = k1

a2.channels = c1

 

# Describe/configure the source

a2.sources.r1.type = netcat

a2.sources.r1.bind = hadoop102

a2.sources.r1.port = 44444

 

# Describe the sink

a2.sinks.k1.type = avro

a2.sinks.k1.hostname = hadoop104

a2.sinks.k1.port = 4141

 

# Use a channel which buffers events in memory

a2.channels.c1.type = memory

a2.channels.c1.capacity = 1000

a2.channels.c1.transactionCapacity = 100

 

# Bind the source and sink to the channel

a2.sources.r1.channels = c1

a2.sinks.k1.channel = c1

3.创建flume3-flume-logger.conf

配置source用于接收flume1与flume2发送过来的数据流,最终合并后sink到控制台。

在hadoop104上创建配置文件并打开

[atguigu@hadoop104 group3]$ touch flume3-flume-logger.conf

[atguigu@hadoop104 group3]$ vim flume3-flume-logger.conf

添加如下内容

# Name the components on this agent

a3.sources = r1

a3.sinks = k1

a3.channels = c1

 

# Describe/configure the source

a3.sources.r1.type = avro

a3.sources.r1.bind = hadoop104

a3.sources.r1.port = 4141

 

# Describe the sink

# Describe the sink

a3.sinks.k1.type = logger

 

# Describe the channel

a3.channels.c1.type = memory

a3.channels.c1.capacity = 1000

a3.channels.c1.transactionCapacity = 100

 

# Bind the source and sink to the channel

a3.sources.r1.channels = c1

a3.sinks.k1.channel = c1

4.执行配置文件

分别开启对应配置文件:flume3-flume-logger.conf,flume2-netcat-flume.conf,flume1-logger-flume.conf。

[atguigu@hadoop104 flume]$ bin/flume-ng agent –conf conf/ –name a3 –conf-file job/group3/flume3-flume-logger.conf -Dflume.root.logger=INFO,console

 

[atguigu@hadoop102 flume]$ bin/flume-ng agent –conf conf/ –name a2 –conf-file job/group3/flume2-netcat-flume.conf

 

[atguigu@hadoop103 flume]$ bin/flume-ng agent –conf conf/ –name a1 –conf-file job/group3/flume1-logger-flume.conf

5.在hadoop103上向/opt/module目录下的group.log追加内容

[atguigu@hadoop103 module]$ echo ‘hello’ > group.log

6.在hadoop102上向44444端口发送数据

[atguigu@hadoop102 flume]$ telnet hadoop102 44444

7.检查hadoop104上数据

 

 


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