此篇博文讲的是Flume的负载均衡和故障转移。
单Source、Channel多Sink(负载均衡)如下图所示。
使用Flume-1监控文件变动,Flume-1将变动内容传递给Flume-2,Flume-2负责存储到控制台。同时Flume-1将变动内容传递给Flume-3,Flume-3也负责存储到控制台。
[bigdata@hadoop002 job]$ mkdir group2
[bigdata@hadoop002 job]$ cd group2
配置1个netcat source和1个channel、1个sink group(2个sink),分别输送给flume-flume-console1和flume-flume-console2。
[bigdata@hadoop002 group2]$ vim flume-netcat-flume.conf
# 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 = load_balance
a1.sinkgroups.g1.processor.backoff = true
a1.sinkgroups.g1.processor.selector = round_robin
a1.sinkgroups.g1.processor.selector.maxTimeOut=10000
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop002
a1.sinks.k1.port = 4141
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = hadoop002
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
注:Avro是由Hadoop创始人Doug Cutting创建的一种语言无关的数据序列化和RPC框架。 注:RPC(Remote Procedure Call)—远程过程调用,它是一种通过网络从远程计算机程序上请求服务,而不需要了解底层网络技术的协议。
配置上级Flume输出的Source,输出是到本地控制台。
[bigdata@hadoop002 group2]$ vim flume-flume-console1.conf
# Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1
# Describe/configure the source
a2.sources.r1.type = avro
a2.sources.r1.bind = hadoop002
a2.sources.r1.port = 4141
# Describe the sink
a2.sinks.k1.type = logger
# Describe the channel
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100
# Bind the source and sink to the channel
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1
配置上级Flume输出的Source,输出是到本地控制台。
[bigdata@hadoop002 group2]$ vim flume-flume-console2.conf
# Name the components on this agent
a3.sources = r1
a3.sinks = k1
a3.channels = c2
# Describe/configure the source
a3.sources.r1.type = avro
a3.sources.r1.bind = hadoop002
a3.sources.r1.port = 4142
# Describe the sink
a3.sinks.k1.type = logger
# Describe the channel
a3.channels.c2.type = memory
a3.channels.c2.capacity = 1000
a3.channels.c2.transactionCapacity = 100
# Bind the source and sink to the channel
a3.sources.r1.channels = c2
a3.sinks.k1.channel = c2
分别开启对应配置文件:flume-flume-console2,flume-flume-console1,flume-netcat-flume。
[bigdata@hadoop002 flume]$ bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group2/flume-flume-console2.conf -Dflume.root.logger=INFO,console
[bigdata@hadoop002 flume]$ bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group2/flume-flume-console1.conf -Dflume.root.logger=INFO,console
[bigdata@hadoop002 flume]$ bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group2/flume-netcat-flume.conf
$ nc localhost 44444
我们可以看到,控制台出现的的回应是按照间隔来的,一段时间内输入的内容会在同一个控制台输出。