高可用flume-ng搭建

一、概述

1.通过搭建高可用flume来实现对数据的收集并存储到hdfs上，架构图如下：

二、配置Agent

1.cat flume-client.properties

#name the components on this agent  声明source、channel、sink的名称  a1.sources = r1  a1.sinks = k1 k2  a1.channels = c1    #Describe/configure the source    声明source的类型为通过tcp的方式监听本地端口5140  a1.sources.r1.type = syslogtcp  a1.sources.r1.port = 5140  a1.sources.r1.host = localhost  a1.sources.r1.channels = c1    #define sinkgroups   此处配置k1、k2的组策略，类型为均衡负载方式  a1.sinkgroups=g1  a1.sinkgroups.g1.sinks=k1 k2  a1.sinkgroups.g1.processor.type=load_balance  a1.sinkgroups.g1.processor.backoff=true  a1.sinkgroups.g1.processor.selector=round_robin    #define the sink 1       数据流向，都是通过avro方式发到两台collector机器  a1.sinks.k1.type=avro  a1.sinks.k1.hostname=hadoop1 a1.sinks.k1.port=5150    #define the sink 2  a1.sinks.k2.type=avro  a1.sinks.k2.hostname=hadoop2a1.sinks.k2.port=5150      # Use a channel which buffers events in memory   指定channel的类型为内存模式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  a1.sinks.k2.channel=c1

#a2和a3的配置和a1相同

三、配置Collector

1.cat flume-server.properties

#name the components on this agent  声明source、channel、sink的名称collector1.sources = r1  collector1.channels = c1collector1.sinks = k1    # Describe the source   声明source的类型为avrocollector1.sources.r1.type = avro  collector1.sources.r1.port = 5150  collector1.sources.r1.bind = 0.0.0.0  collector1.sources.r1.channels = c1      # Describe channels c1 which buffers events in memory 指定channel的类型为内存模式collector1.channels.c1.type = memory  collector1.channels.c1.capacity = 1000  collector1.channels.c1.transactionCapacity = 100    # Describe the sink k1 to hdfs  指定sink数据流向hdfscollector1.sinks.k1.type = hdfs  collector1.sinks.k1.channel = c1  collector1.sinks.k1.hdfs.path = hdfs://master/user/flume/logcollector1.sinks.k1.hdfs.fileType = DataStream  collector1.sinks.k1.hdfs.writeFormat = TEXT  collector1.sinks.k1.hdfs.rollInterval = 300  collector1.sinks.k1.hdfs.filePrefix = %Y-%m-%d  collector1.sinks.k1.hdfs.round = true  collector1.sinks.k1.hdfs.roundValue = 5  collector1.sinks.k1.hdfs.roundUnit = minute  collector1.sinks.k1.hdfs.useLocalTimeStamp = true

#collector2配置和collector1相同

四、启动

1.在Collector上启动fulme-ng

flume-ng agent -n collector1 -c conf -f /usr/local/flume/conf/flume-server.properties -Dflume.root.logger=INFO,console# -n 后面接配置文件中的Agent Name

2.在Agent上启动flume-ng

flume-ng agent -n a1 -c conf -f /usr/local/flume/conf/flume-client.properties -Dflume.root.logger=INFO,console

五、测试

[root@hadoop5 ~]#  echo "hello" | nc localhost 5140    #需要安装nc

17/09/03 22:56:58 INFO source.AvroSource: Avro source r1 started.17/09/03 22:59:09 INFO ipc.NettyServer: [id: 0x60551752, /192.168.100.15:34310 => /192.168.100.11:5150] OPEN17/09/03 22:59:09 INFO ipc.NettyServer: [id: 0x60551752, /192.168.100.15:34310 => /192.168.100.11:5150] BOUND: /192.168.100.11:515017/09/03 22:59:09 INFO ipc.NettyServer: [id: 0x60551752, /192.168.100.15:34310 => /192.168.100.11:5150] CONNECTED: /192.168.100.15:3431017/09/03 23:03:54 INFO hdfs.HDFSDataStream: Serializer = TEXT, UseRawLocalFileSystem = false17/09/03 23:03:54 INFO hdfs.BucketWriter: Creating hdfs://master/user/flume/log/2017-09-03.1504494234038.tmp

六、总结

高可用flume-ng一般有两种模式：load_balance和failover。此次使用的是load_balance，failover的配置如下：

#set failovera1.sinkgroups.g1.processor.type = failovera1.sinkgroups.g1.processor.priority.k1 = 10a1.sinkgroups.g1.processor.priority.k2 = 1a1.sinkgroups.g1.processor.maxpenalty = 10000

一些常用的source、channel、sink类型如下：