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 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.type = logger
# 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
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 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 /var/log/test.log
a1.sources.r1.shell = /bin/sh -c
# Describe the sink
a1.sinks.k1.type = logger
# 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
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 sink
avro source + memory channel + logger sink
代码实现
A端服务器
exec-memory-avro.sources = exec-source
exec-memory-avro.sinks = avro-sink
exec-memory-avro.channels = memory-channel
exec-memory-avro.sources.exec-source.type = exec
exec-memory-avro.sources.exec-source.command = tail -F /home/hadoop/data/data.log
exec-memory-avro.sources.exec-source.shell = /bin/sh -c
exec-memory-avro.sinks.avro-sink.type = avro
exec-memory-avro.sinks.avro-sink.hostname = hadoop000
exec-memory-avro.sinks.avro-sink.port = 44444
exec-memory-avro.channels.memory-channel.type = memory
exec-memory-avro.sources.exec-source.channels = memory-channel
exec-memory-avro.sinks.avro-sink.channel = memory-channel
B端服务器
avro-memory-logger.sources = avro-source
avro-memory-logger.sinks = logger-sink
avro-memory-logger.channels = memory-channel
avro-memory-logger.sources.avro-source.type = avro
avro-memory-logger.sources.avro-source.bind = hadoop000
avro-memory-logger.sources.avro-source.port = 44444
avro-memory-logger.sinks.logger-sink.type = logger
avro-memory-logger.channels.memory-channel.type = memory
avro-memory-logger.sources.avro-source.channels = memory-channel
avro-memory-logger.sinks.logger-sink.channel = memory-channel
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