一、概述

1.通過搭建高可用flume來實現對數據的收集並存儲到hdfs上，架構圖如下：

二、配置Agent

1.cat flume-client.properties

#name the components on this agent  聲明source、channel、sink的名稱  
a1.sources = r1  
a1.sinks = k1 k2  
a1.channels = c1  
  
#Describe/configure the source    聲明source的類型為通過tcp的方式監聽本地端口5140  
a1.sources.r1.type = syslogtcp  
a1.sources.r1.port = 5140  
a1.sources.r1.host = localhost  
a1.sources.r1.channels = c1  
  
#define sinkgroups   此處配置k1、k2的組策略，類型為均衡負載方式  
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	數據流向，都是通過avro方式發到兩臺collector機器  
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的類型為內存模式
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  聲明source、channel、sink的名稱
collector1.sources = r1  
collector1.channels = c1
collector1.sinks = k1  
  
# Describe the source   聲明source的類型為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的類型為內存模式
collector1.channels.c1.type = memory  
collector1.channels.c1.capacity = 1000  
collector1.channels.c1.transactionCapacity = 100  
  
# Describe the sink k1 to hdfs  指定sink數據流向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、啟動

1.在Collector上啟動fulme-ng

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

2.在Agent上啟動flume-ng

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

五、測試

[[email protected] ~]#  echo "hello" | nc localhost 5140    #需要安裝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、總結

高可用flume-ng一般有兩種模式：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類型如下：

本文出自 “lullaby” 博客，請務必保留此出處http://lullaby.blog.51cto.com/10815696/1962460

高可用flume-ng搭建