（二十二）大数据实战——Flume数据采集之故障转移案例实战

前言

本节内容我们完成Flume数据采集的故障转移案例，使用三台服务器，一台服务器负责采集nc数据，通过使用failover模式的Sink处理器完成监控数据的故障转移，使用Avro的方式完成flume之间采集数据的传输。整体架构如下：

正文

①在hadoop101服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-nc-flume-avro.conf配置文件，用于监控nc并传输到avro sink

- job-nc-flume-avro.conf配置文件

# Name the components on this agent
a1.sources = r1
a1.channels = c1
a1.sinkgroups = g1
a1.sinks = k1 k2
# Describe/configure the source
a1.sources.r1.type = netcat
a1.sources.r1.bind = localhost
a1.sources.r1.port = 44444
a1.sinkgroups.g1.processor.type = failover
a1.sinkgroups.g1.processor.priority.k1 = 5
a1.sinkgroups.g1.processor.priority.k2 = 10
a1.sinkgroups.g1.processor.maxpenalty = 10000
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop102
a1.sinks.k1.port = 4141
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = hadoop103
a1.sinks.k2.port = 4142
# 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.sinkgroups.g1.sinks = k1 k2
a1.sinks.k1.channel = c1
a1.sinks.k2.channel = c1

②在hadoop102服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-avro-flume-console102.conf配置文件，用于监控avro source数据到控制台

 - job-avro-flume-console102.conf配置文件

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
a1.sources.r1.type = avro
a1.sources.r1.bind = hadoop102
a1.sources.r1.port = 4141
# Describe the sink
a1.sinks.k1.type = logger
# 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

③ 在hadoop103服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-avro-flume-console103.conf配置文件，用于监控avro source数据到控制台

- job-avro-flume-console103.conf配置文件

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
a1.sources.r1.type = avro
a1.sources.r1.bind = hadoop103
a1.sources.r1.port = 4142
# Describe the sink
a1.sinks.k1.type = logger
# 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

④启动hadoop102上的flume任务job-avro-flume-console102.conf

- 命令：

bin/flume-ng agent -c conf/ -n a1 -f job/job-avro-flume-console102.conf -Dflume.root.logger=INFO,console

⑤启动hadoop103上的flume任务job-avro-flume-console103.conf 

- 命令：

bin/flume-ng agent -c conf/ -n a1 -f job/job-avro-flume-console103.conf -Dflume.root.logger=INFO,console

⑥启动hadoop101上的flume任务job-nc-flume-avro.conf

- 命令：

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

⑦使用nc向本地44444监控端口发送数据

 - 由于hadoop103中的sink avro优先级高于hadoop102中的sink avro，故hadoop103接收到了nc发送的数据

- 此时将hadoop103中的flume任务停止，继续通过nc发送数据，hadoop102的sink avro替换hadoop103中的flume任务继续接收数据打印到控制台

- 此时在将hadoop103中的flume监控恢复，继续通过nc发送数据，数据继续通过hadoop103中的sink avro接收数据

结语

至此，关于Flume数据采集之故障转移案例实战到这里就结束了，我们下期见。。。。。。