Flume的介绍和简单操作

Flume是什么

Flume是Cloudera提供的一个高可用的，高可靠的，分布式的海量日志采集、聚合和传输的系统，Flume支持在日志系统中定制各类数据发送方，用于收集数据；同时，Flume提供对数据进行简单处理，并写到各种数据接受方（可定制）的能力。
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Flume的功能

支持在日志系统中定制各类数据发送方，用于收集数据
提供对数据简单处理，并写到各类数据接收方（可定制）的能力
Flume的组成
Agent:核心组件
- source 负责数据的产生或搜集
- channel 是一种短暂的存储容器,负责数据的存储持久化
- sink 负责数据的转发
  Flume的工作流示意图
数据流模型
多Agent模型
合并模型

混合模型

Flume的安装

下载安装包并解压

wget http://www.apache.org/dyn/closer.lua/flume/1.8.0/apache-flume-1.8.0-bin.tar.gz
tar -zxvf apache-flume-1.8.0-bin.tar.gz

配置环境变量

vim ~/.bashrc

export FLUME_HOME=/usr/local/src/apache-flume-1.8.0-bin
export PATH=$PATH:$FLUME_HOME/bin

source ~/.bashrc

Flume简单操作

netcat模式
进入conf目录下编写netcat.conf文件，内容如下：

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink

agent.sources.netcatSource.type = netcat
agent.sources.netcatSource.bind = localhost
agent.sources.netcatSource.port = 11111
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink.type = logger
agent.sinks.loggerSink.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 100
agent.channels.memoryChannel.transactionCapacity = 10

启动一个实例

(py27) [root@master conf]# pwd
/usr/local/src/apache-flume-1.8.0-bin/conf
(py27) [root@master conf]# flume-ng agent --conf conf --conf-file ./netcat.conf --name agent -Dflume.root.logger=INFO,console

启动成功

18/10/24 11:26:35 INFO node.PollingPropertiesFileConfigurationProvider: Configuration provider starting
18/10/24 11:26:35 INFO node.PollingPropertiesFileConfigurationProvider: Reloading configuration file:./flume_netcat.conf
18/10/24 11:26:35 INFO conf.FlumeConfiguration: Processing:loggerSink
18/10/24 11:26:35 INFO conf.FlumeConfiguration: Processing:loggerSink
18/10/24 11:26:35 INFO conf.FlumeConfiguration: Added sinks: loggerSink Agent: agent
18/10/24 11:26:35 INFO conf.FlumeConfiguration: Post-validation flume configuration contains configuration for agents: [agent]
18/10/24 11:26:35 INFO node.AbstractConfigurationProvider: Creating channels
18/10/24 11:26:35 INFO channel.DefaultChannelFactory: Creating instance of channel memoryChannel type memory
18/10/24 11:26:35 INFO node.AbstractConfigurationProvider: Created channel memoryChannel
18/10/24 11:26:35 INFO source.DefaultSourceFactory: Creating instance of source netcatSource, type netcat
18/10/24 11:26:35 INFO sink.DefaultSinkFactory: Creating instance of sink: loggerSink, type: logger
18/10/24 11:26:35 INFO node.AbstractConfigurationProvider: Channel memoryChannel connected to [netcatSource, loggerSink]
18/10/24 11:26:35 INFO node.Application: Starting new configuration:{ sourceRunners:{netcatSource=EventDrivenSourceRunner: { source:org.apache.flume.source.NetcatSource{name:netcatSource,state:IDLE} }} sinkRunners:{loggerSink=SinkRunner: { policy:org.apache.flume.sink.DefaultSinkProcessor@262b92ac counterGroup:{ name:null counters:{} } }} channels:{memoryChannel=org.apache.flume.channel.MemoryChannel{name: memoryChannel}} }
18/10/24 11:26:35 INFO node.Application: Starting Channel memoryChannel
18/10/24 11:26:35 INFO node.Application: Waiting for channel: memoryChannel to start. Sleeping for 500 ms
18/10/24 11:26:36 INFO instrumentation.MonitoredCounterGroup: Monitored counter group for type: CHANNEL, name: memoryChannel: Successfully registered new MBean.
18/10/24 11:26:36 INFO instrumentation.MonitoredCounterGroup: Component type: CHANNEL, name: memoryChannel started
18/10/24 11:26:36 INFO node.Application: Starting Sink loggerSink
18/10/24 11:26:36 INFO node.Application: Starting Source netcatSource
18/10/24 11:26:36 INFO source.NetcatSource: Source starting
18/10/24 11:26:36 INFO source.NetcatSource: Created serverSocket:sun.nio.ch.ServerSocketChannelImpl[/172.16.155.120:11111]

然后新开一个终端，发送数据

(py27) [root@master apache-flume-1.8.0-bin]# telnet localhost 11111
Trying 127.0.0.1...
Connected to localhost.
Escape character is '^]'.
1
OK

查看接收数据

18/10/24 11:30:15 INFO sink.LoggerSink: Event: { headers:{} body: 31 0D                                           1. }

注：如果没有telnet工具，请先安装：yum install telnet

Exec模式
编写配置文件exec.conf

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink

agent.sources.netcatSource.type = exec 
agent.sources.netcatSource.command = tail -f /home/master/FlumeTest/test_data/exec.log
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink.type = logger
agent.sinks.loggerSink.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 100
agent.channels.memoryChannel.transactionCapacity = 10

启动实例

(py27) [root@master conf]# flume-ng agent --conf conf --conf-file ./flume_exec.conf --name agent -Dflume.root.logger=INFO,console

启动成功后，创建配置文件中的exec.log文件

(py27) [root@master test_data]# ls
exec.log
(py27) [root@master test_data]# pwd
/home/master/FlumeTest/test_data
(py27) [root@master test_data]#

然后通过echo命令模拟日志的产生

(py27) [root@master test_data]# echo 'Hello World!!!' >> exec.log

查看接收的日志

18/10/25 09:19:52 INFO sink.LoggerSink: Event: { headers:{} body: 48 65 6C 6C 6F 20 57 6F 72 6C 64 21 21 21       Hello World!!! }

如何将日志保存到HDFS上
修改配置文件

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink

agent.sources.netcatSource.type = exec 
agent.sources.netcatSource.command = tail -f /home/master/FlumeTest/test_data/exec.log
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink.type = hdfs 
agent.sinks.loggerSink.hdfs.path = /flume/%y-%m-%d/%H%M/
agent.sinks.loggerSink.hdfs.filePrefix = exec_hdfs_
agent.sinks.loggerSink.hdfs.round = true
agent.sinks.loggerSink.hdfs.roundValue = 1
agent.sinks.loggerSink.hdfs.roundUnit = minute
agent.sinks.loggerSink.hdfs.rollInterval = 3
agent.sinks.loggerSink.hdfs.rollSize = 20
agent.sinks.loggerSink.hdfs.rollCount = 5
agent.sinks.loggerSink.hdfs.useLocalTimeStamp = true
agent.sinks.loggerSink.hdfs.fileType = DataStream
agent.sinks.loggerSink.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 100
agent.channels.memoryChannel.transactionCapacity = 10

然后启动实例

(py27) [root@master conf]# flume-ng agent --conf conf --conf-file ./flume_exec_hdfs.conf --name agent -Dflume.root.logger=INFO,console

然后可以看到它把exec.log文件里的日志给写到了HDFS上

18/10/25 09:54:26 INFO hdfs.HDFSDataStream: Serializer = TEXT, UseRawLocalFileSystem = false
18/10/25 09:54:26 INFO hdfs.BucketWriter: Creating /flume/18-10-25/0954//exec_hdfs_.1540475666623.tmp
18/10/25 09:54:32 INFO hdfs.BucketWriter: Closing /flume/18-10-25/0954//exec_hdfs_.1540475666623.tmp
18/10/25 09:54:32 INFO hdfs.BucketWriter: Renaming /flume/18-10-25/0954/exec_hdfs_.1540475666623.tmp to /flume/18-10-25/0954/exec_hdfs_.1540475666623
18/10/25 09:54:32 INFO hdfs.HDFSEventSink: Writer callback called.

我们进入HDFS查看，可以看到log里的内容

(py27) [root@master sbin]# hadoop fs -ls /flume/18-10-25/0954
Found 1 items
-rw-r--r--   3 root supergroup         15 2018-10-25 09:54 /flume/18-10-25/0954/exec_hdfs_.1540475666623
(py27) [root@master sbin]# hadoop fs -text /flume/18-10-25/0954/exec_hdfs_.1540475666623
Hello World!!!

然后我们再次写入写的log，然后再查看

//写入新的log
(py27) [root@master test_data]# echo 'test001' >> exec.log               
(py27) [root@master test_data]# echo 'test002' >> exec.log
//进入HDFS目录查看
(py27) [root@master sbin]# hadoop fs -ls /flume/18-10-25
Found 2 items
drwxr-xr-x   - root supergroup          0 2018-10-25 09:54 /flume/18-10-25/0954
drwxr-xr-x   - root supergroup          0 2018-10-25 09:56 /flume/18-10-25/0956
(py27) [root@master sbin]# hadoop fs -ls /flume/18-10-25/0956
Found 1 items
-rw-r--r--   3 root supergroup         16 2018-10-25 09:56 /flume/18-10-25/0956/exec_hdfs_.1540475766338
(py27) [root@master sbin]# hadoop fs -text /flume/18-10-25/0956/exec_hdfs_.1540475766338
test001
test002

故障转移实例
首先需要三台机器，master、slave1、slave2，然后分别配置实例并启动，master上的agent实例发送日志，slave1和slave2接收日志
master配置

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink1 loggerSink2

agent.sinkgroups = group

agent.sources.netcatSource.type = exec
agent.sources.netcatSource.command = tail -f /home/master/FlumeTest/test_data/exec.log
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink1.type = avro
agent.sinks.loggerSink1.hostname = slave1
agent.sinks.loggerSink1.port = 52020
agent.sinks.loggerSink1.channel = memoryChannel

agent.sinks.loggerSink2.type = avro
agent.sinks.loggerSink2.hostname = slave2
agent.sinks.loggerSink2.port = 52020
agent.sinks.loggerSink2.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 10000
agent.channels.memoryChannel.transactionCapacity = 1000

agent.sinkgroups.group.sinks = loggerSink1 loggerSink2

agent.sinkgroups.group.processor.type = failover
agent.sinkgroups.group.processor.loggerSink1 = 10
agent.sinkgroups.group.processor.loggerSink2 = 1
agent.sinkgroups.group.processor.maxpenalty = 10000

slave1配置

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink

agent.sources.netcatSource.type = avro
agent.sources.netcatSource.bind = slave1
agent.sources.netcatSource.port = 52020
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink.type = logger
agent.sinks.loggerSink.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 10000
agent.channels.memoryChannel.transactionCapacity = 1000

slave2配置

agent.sources = netcatSource
agent.channels = memoryChannel
agent.sinks = loggerSink

agent.sources.netcatSource.type = avro
agent.sources.netcatSource.bind = slave2
agent.sources.netcatSource.port = 52020
agent.sources.netcatSource.channels = memoryChannel

agent.sinks.loggerSink.type = logger
agent.sinks.loggerSink.channel = memoryChannel

agent.channels.memoryChannel.type = memory
agent.channels.memoryChannel.capacity = 10000
agent.channels.memoryChannel.transactionCapacity = 1000

分别启动master、slave1、slave2的agent，然后在mater上写入日志，然后观察谁收到了

//master
(py27) [root@master test_data]# echo 'hello' >> exec.log  
//slave1
18/10/25 10:53:53 INFO sink.LoggerSink: Event: { headers:{} body: 68 65 6C 6C 6F                                  hello }
//slave2
18/10/25 10:43:00 INFO ipc.NettyServer: [id: 0x8da012e3, /172.16.155.120:39726 => /172.16.155.122:52020] CONNECTED: /172.16.155.120:39726

发现是slave1收到数据，然后我们把slave1的agent关掉，再次发送日志

//master
(py27) [root@master test_data]# echo '11111' >> exec.log      
//slave2
18/10/25 10:43:00 INFO ipc.NettyServer: [id: 0x8da012e3, /172.16.155.120:39726 => /172.16.155.122:52020] CONNECTED: /172.16.155.120:39726
18/10/25 10:56:53 INFO sink.LoggerSink: Event: { headers:{} body: 31 31 31 31 31                                  11111 }

然后再次启动slave1的agent

//master
(py27) [root@master test_data]# echo '22222' >> exec.log      
//slave1
18/10/25 10:58:21 INFO sink.LoggerSink: Event: { headers:{} body: 32 32 32 32 32                                  22222 }
//slave2
18/10/25 10:43:00 INFO ipc.NettyServer: [id: 0x8da012e3, /172.16.155.120:39726 => /172.16.155.122:52020] CONNECTED: /172.16.155.120:39726
18/10/25 10:56:53 INFO sink.LoggerSink: Event: { headers:{} body: 31 31 31 31 31                                  11111 }

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Flume的介绍和简单操作

Flume是什么

Flume的功能

Flume的组成

Flume的工作流示意图

Flume的安装

Flume简单操作

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