高可用flume-ng搭建

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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=hadoop2
a1.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 = c1
collector1.sinks = k1 
   
# Describe the source  声明 source 的类型为 avro
collector1.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 hdfs
collector1.sinks.k1.type = hdfs 
collector1.sinks.k1.channel = c1 
collector1.sinks.k1.hdfs.path = hdfs://master/user/flume/log
collector1.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] OPEN
17/09/03 22:59:09 INFO ipc.NettyServer: [id: 0x60551752, /192.168.100.15:34310 => /192.168.100.11:5150] BOUND: /192.168.100.11:5150
17/09/03 22:59:09 INFO ipc.NettyServer: [id: 0x60551752, /192.168.100.15:34310 => /192.168.100.11:5150] CONNECTED: /192.168.100.15:34310
17/09/03 23:03:54 INFO hdfs.HDFSDataStream: Serializer = TEXT, UseRawLocalFileSystem = false
17/09/03 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 failover
a1.sinkgroups.g1.processor.type = failover
a1.sinkgroups.g1.processor.priority.k1 = 10
a1.sinkgroups.g1.processor.priority.k2 = 1
a1.sinkgroups.g1.processor.maxpenalty = 10000

一些常用的 source、channel、sink 类型如下：

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