大数据新手之路四：联合使用Flume和Kafka

Ubuntu16.04+Kafka1.0.0+Flume1.8.0

 

1.目标

①使用Flume作为Kafka的Producer；

②使用Kafka作为Flume的Sink；

其实以上两点是同一个事情在Flume和Kafka两个立场上的不同描述而已，其实就是同一个事情。

 

2.启动zookeeper（这里使用kafka自带的zookeeper，也可以独立部署zookeeper使用）

使用默认的zookeeper.properties配置文件

zookeeper-server-start.sh /usr/local/kafka/config/zookeeper.properties

 

3.启动kafka

使用默认的server.properties配置文件

kafka-server-start.sh /usr/local/kafka/config/server.properties

 

4.增加一个名字为flume的topic

kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic flume

 

5.创建一个consumer接受flume的消息（后面在这个进程中将接收到消息）

kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic flume

 

6.在/usr/local/flume/conf中增加一个kafka_sink.conf文件

#example.conf: A single-node Flume configuration

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

# Describe/configure the source
a1.sources.r1.type = netcat
a1.sources.r1.bind = localhost
a1.sources.r1.port = 44444

# Describe the sink
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = flume
a1.sinks.k1.kafka.bootstrap.servers = localhost:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.k1.kafka.producer.compression.type = snappy

# 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

 

7.启动flume

flume-ng agent --conf /usr/local/flume/conf --conf-file /usr/local/flume/conf/kafka_sink.conf --name a1 -Dflume.root.logger=INFO,console

 

8.使用telnet连接到flume并发送数据

$ telnet localhost 44444
Trying 127.0.0.1...
Connected to localhost.localdomain (127.0.0.1).
Escape character is '^]'.
Test flume kafka! <ENTER>
OK

 

9.在consumer的进程中可以看到如下信息

Test flume kafka!

 

以上。