flume+flume+kafka消息传递

通过flume收集其他机器上flume的监测数据，发送到本机的kafka进行消费。

环境：slave中安装flume，master中安装flume+kafka（这里用两台虚拟机，也可以用三台以上）

masterIP 192.168.83.128    slaveIP 192.168.83.129

通过监控test.log文件的变化，收集变化信息发送到主机的flume中，再发送到kafka中进行消费

1、配置slave1在flume中配置conf目录中的example.conf文件，没有就创建一个

#Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = exec
#监控文件夹下的test.log文件
a1.sources.r1.command = tail -F /home/qq/pp/data/test.log
a1.sources.r1.channels = c1

# Describe the sink
##sink端的avro是一个数据发送者
a1.sinks = k1
##type设置成avro来设置发消息
a1.sinks.k1.type = avro
a1.sinks.k1.channel = c1
##下沉到master这台机器
a1.sinks.k1.hostname = 192.168.83.133
##下沉到mini2中的44444
a1.sinks.k1.port = 44444
a1.sinks.k1.batch-size = 2

# 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、master上配置flume/conf里面的example.conf(标红的注意下)

#me the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
##source中的avro组件是一个接收者服务
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = 0.0.0.0
a1.sources.r1.port = 44444

# Describe the sink
#a1.sinks.k1.type = logger
#对于sink的配置描述 使用kafka做数据的消费
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.topic = flume_kafka
a1.sinks.k1.brokerList = 192.168.83.128:9092,192.168.83.129:9092
a1.sinks.k1.requiredAcks = 1
a1.sinks.k1.batchSize = 20

# 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

3、向监听文件写入字符串(程序循环写入，不用手动修改test.log文件了)

[root@s1 # cd /home/qq/pp/data
[root@s1 home/qq/pp/data# while true
> do
> echo "toms" >> test.log
> sleep 1
> done

4、查看上面的程序是否执行

#cd /home/qq/pp/data
#tail -f test.log

5、打开消息接收者master的flume

进入flume安装目录，执行如下语句

bin/flume-ng agent -c conf -f conf/example.conf -n a1 -Dflume.root.logger=INFO,console

现在回打印出一些信息

6、启动slave的flume

进入flume安装目录，执行如下语句

bin/flume-ng agent -c conf -f conf/example.conf -n a1 -Dflume.root.logger=INFO,console

7、 进入master ---kafka安装目录

　　　　1）启动zookeeper

　　　　　　bin/zookeeper-server-start.sh -daemon config/zookeeper.properties

　　　　2）启动kafka服务

　　　　　　bin/kafka-server-start.sh -daemon config/server.properties

　　　　3）创建topic

kafka-topics.sh --create --topic flume_kafka  --zookeeper 192.168.83.129:2181,192.168.83.128:2181 --partitions 2 --replication-factor 1

　　　　4）创建消费者

bin/kafka-console-consumer.sh --bootstrap-server 192.168.83.128:9092,192.168.83.129:9092 --topic flume_kafka --from-beginning

　　　　5）然后就会看到消费之窗口打印写入的信息，

后面将会结合storm进行数据的真正消费敬请期待。

参考：

https://blog.csdn.net/luozhonghua2014/article/details/80369469?utm_source=blogxgwz5

https://blog.csdn.net/wxgxgp/article/details/85701844

https://blog.csdn.net/tototuzuoquan/article/details/73203241

flume+flume+kafka消息传递

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