Flume架构及使用例子

Flume架构及核心组件

（1）Source 收集 负责从什么地方采集数据（2）Channel 记录 （3）Sink 输出

官方文档

http://flume.apache.org/FlumeUserGuide.html

http://flume.apache.org/FlumeUserGuide.html#starting-an-agent

Flume使用思路

使用flume的关键就是写配置文件

（1）配置Source

（2）配置Channerl

（3）配置Sink

（4）把以上三个组件串起来

样例

样例1：从指定网络端口采集数据输出到控制台

代码实现：

# example.conf: A single-node Flume configuration# Name the components on this agenta1.sources = r1a1.sinks = k1a1.channels = c1# Describe/configure the sourcea1.sources.r1.type = netcata1.sources.r1.bind = localhosta1.sources.r1.port = 44444# Describe the sinka1.sinks.k1.type = logger# Use a channel which buffers events in memorya1.channels.c1.type = memorya1.channels.c1.capacity = 1000a1.channels.c1.transactionCapacity = 100# Bind the source and sink to the channela1.sources.r1.channels = c1a1.sinks.k1.channel = c1

启动agent

http://flume.apache.org/FlumeUserGuide.html#starting-an-agent

$ bin/flume-ng agent -n $agent_name -c conf -f conf/flume-conf.properties.template -Dflume.root.logger=INFO,console

-n 和-name同样含义，为agent名称

-c 和-conf同样含义，为指定一个配置文件

-Dflume.root.logger=INFO,console 在控制台输出执行信息

使用telnet进行测试

telnet localhost 44444

输出结果分析

Event：{headers:{} body: 68 65 6c 6c 6f 0d hello}

Event是Flume数据传输的基本单元

Event = 可选的header + byte array

样例2:监控一个文件实时采集新增的数据输出到控制台

Agent选型

exec source + memory channel + logger sink

Exec Source文档地址

http://flume.apache.org/FlumeUserGuide.html#exec-source

代码实现

# Name the components on this agenta1.sources = r1a1.sinks = k1a1.channels = c1# Describe/configure the sourcea1.sources.r1.type = execa1.sources.r1.command = tail -F /var/log/test.loga1.sources.r1.shell = /bin/sh -c# Describe the sinka1.sinks.k1.type = logger# Use a channel which buffers events in memorya1.channels.c1.type = memorya1.channels.c1.capacity = 1000a1.channels.c1.transactionCapacity = 100# Bind the source and sink to the channela1.sources.r1.channels = c1a1.sinks.k1.channel = c1

样例3:将A端服务器日志实时采集到B端服务器

技术选型

exec source + memory channel + avro sinkavro source + memory channel + logger sink

代码实现

A端服务器

exec-memory-avro.sources = exec-sourceexec-memory-avro.sinks = avro-sinkexec-memory-avro.channels = memory-channelexec-memory-avro.sources.exec-source.type = execexec-memory-avro.sources.exec-source.command = tail -F /home/hadoop/data/data.logexec-memory-avro.sources.exec-source.shell = /bin/sh -cexec-memory-avro.sinks.avro-sink.type = avroexec-memory-avro.sinks.avro-sink.hostname = hadoop000exec-memory-avro.sinks.avro-sink.port = 44444exec-memory-avro.channels.memory-channel.type = memoryexec-memory-avro.sources.exec-source.channels = memory-channelexec-memory-avro.sinks.avro-sink.channel = memory-channel

B端服务器

avro-memory-logger.sources = avro-sourceavro-memory-logger.sinks = logger-sinkavro-memory-logger.channels = memory-channelavro-memory-logger.sources.avro-source.type = avroavro-memory-logger.sources.avro-source.bind = hadoop000avro-memory-logger.sources.avro-source.port = 44444avro-memory-logger.sinks.logger-sink.type = loggeravro-memory-logger.channels.memory-channel.type = memoryavro-memory-logger.sources.avro-source.channels = memory-channelavro-memory-logger.sinks.logger-sink.channel = memory-channel