尚硅谷大数据技术之Flume(新)第3章 企业开发案例
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