　　不多说，直接上干货！

一、自定义拦截器类型必须是：类全名$内部类名，其实就是内部类名称
　　如：zhouls.bigdata.MySearchAndReplaceInterceptor$Builder

二、为什么这样写
　　至于为什么这样写：是因为Interceptor接口还有一个公共的内部接口（Builder），所以自定义拦截器要是实现 Builder接口，
　　也就是实现一个内部类（该内部类的主要作用是：获取flume-conf.properties 自定义的参数，并将参数传递给自定义拦截器）
三、
　　本人知识有限,可能描述的不太清楚，可自行了解 java接口与内部类

　　由于有时候内置的拦截器不够用，所以需要针对特殊的业务需求自定义拦截器。
官方文档中没有发现自定义interceptor的步骤，但是可以根据flume源码参考内置的拦截器的代码
flume-1.7/flume-ng-core/src/main/java/org/apache/flume/interceptor/***Iterceptor.java

　　无论，是flume的自带拦截器，还是，flume的自定义拦截器，我这篇博文呢，是想给大家，去规范和方便化！！！

[hadoop@master app]$ rm -rf flume

[hadoop@master app]$ ln -s flume-1.7./ flume

[hadoop@master app]$ ll

lrwxrwxrwx    hadoop hadoop    Jul  : flume -> flume-1.7./

drwxrwxr-x    hadoop hadoop  Apr  : flume-1.6.

drwxrwxr-x    hadoop hadoop  Apr  : flume-1.7.

　　Host Interceptor的应用场景是，将同一主机或服务器上的数据flume在一起。

　　 Regex Extractor Iterceptor的应用场景是，

这里，教大家一个非常实用的技巧，

[hadoop@master flume-1.7.0]$ pwd

/home/hadoop/app/flume-1.7.0

[hadoop@master flume-1.7.0]$ ll

total 148

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$ cp -r conf conf_HostInterceptor

[hadoop@master flume-1.7.0]$ ll

total 152

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 11:59 conf_HostInterceptor

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$

[hadoop@master flume-1.7.0]$ ll

total 152

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:01 conf_HostInterceptor

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$ cp -r conf conf_RegexExtractorInterceptor

[hadoop@master flume-1.7.0]$ ll

total 156

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:01 conf_HostInterceptor

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:03 conf_RegexExtractorInterceptor

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:01 conf_HostInterceptor

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:03 conf_RegexExtractorInterceptor

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$ cp -r conf conf_SearchandReplaceInterceptor

[hadoop@master flume-1.7.0]$ ll

total 160

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 bin

-rw-r--r--  1 hadoop hadoop 77387 Oct 11  2016 CHANGELOG

drwxr-xr-x  2 hadoop hadoop  4096 Apr 20 12:00 conf

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:01 conf_HostInterceptor

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:03 conf_RegexExtractorInterceptor

drwxr-xr-x  2 hadoop hadoop  4096 Jul 27 12:04 conf_SearchandReplaceInterceptor

-rw-r--r--  1 hadoop hadoop  6172 Sep 26  2016 DEVNOTES

-rw-r--r--  1 hadoop hadoop  2873 Sep 26  2016 doap_Flume.rdf

drwxr-xr-x 10 hadoop hadoop  4096 Oct 13  2016 docs

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 lib

-rw-r--r--  1 hadoop hadoop 27625 Oct 13  2016 LICENSE

-rw-r--r--  1 hadoop hadoop   249 Sep 26  2016 NOTICE

-rw-r--r--  1 hadoop hadoop  2520 Sep 26  2016 README.md

-rw-r--r--  1 hadoop hadoop  1585 Oct 11  2016 RELEASE-NOTES

drwxrwxr-x  2 hadoop hadoop  4096 Apr 20 12:00 tools

[hadoop@master flume-1.7.0]$

　　大家，想必，很想问，为什么要这么cp复制出来呢？如flume的以下3种重要的自带拦截器？？？

cp -r conf conf_HostInterceptor

cp -r conf conf_SearchandReplaceInterceptor

cp -r conf conf_RegexExtractorInterceptor

　　你想啊，若不复制的话，则我们在使用时，则会不方便管理。尤其是，见如下，共用同一个log4j.properties，日志排查起来一点都不方便！！！

　　而，现在是

　　这样做下来，就是非常的方便和正规。

　　同时，大家，还要如下更改下

[hadoop@master conf_HostInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_HostInterceptor

[hadoop@master conf_HostInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_HostInterceptor]$ mv flume-conf.properties.template flume-conf.properties

[hadoop@master conf_HostInterceptor]$ vim log4j.properties

#flume.root.logger=DEBUG,console

flume.root.logger=INFO,LOGFILE

flume.log.dir=./logs

flume.log.file=flume_HostInterceptor.log

　　同理

[hadoop@master conf_RegexExtractorInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_RegexExtractorInterceptor

[hadoop@master conf_RegexExtractorInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_RegexExtractorInterceptor]$ mv flume-conf.properties.template flume-conf.properties

[hadoop@master conf_RegexExtractorInterceptor]$ vim log4j.properties

#flume.root.logger=DEBUG,console

flume.root.logger=INFO,LOGFILE

flume.log.dir=./logs

flume.log.file=flume_RegexExtractorInterceptor.log

　　同理

[hadoop@master conf_SearchandReplaceInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_SearchandReplaceInterceptor

[hadoop@master conf_SearchandReplaceInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_SearchandReplaceInterceptor]$ mv flume-conf.properties.template flume-conf.properties

[hadoop@master conf_SearchandReplaceInterceptor]$ vim log4j.properties

#flume.root.logger=DEBUG,console

flume.root.logger=INFO,LOGFILE

flume.log.dir=./logs

flume.log.file=flume_SearchandReplaceInterceptor.log

Host Interceptor

　　conf_HostInterceptor的flume-conf.properties

agent1.sources = r1

agent1.sinks = k1

agent1.channels = c1

# Describe/configure the source

agent1.sources.r1.type = netcat

agent1.sources.r1.bind = localhost

agent1.sources.r1.port = 

agent1.sources.r1.interceptors = i1

agent1.sources.r1.interceptors.i1.type = host

agent1.sources.r1.interceptors.i1.hostHeader = hostname

# Use a channel which buffers events in memory

agent1.channels.c1.type = memory

agent1.channels.c1.capacity =

agent1.channels.c1.transactionCapacity = 

# Bind the source and sink to the channel

agent1.sources.r1.channels = c1

agent1.sinks.k1.channel = c1

# Describe the sink

agent1.sinks.k1.type = logger

则，注意，启动命令也要发生变化

[hadoop@master flume-1.7.0]$ bin/flume-ng agent --conf conf_HostInterceptor/  --conf-file conf_HostInterceptor/flume-conf.properties --name agent1  -Dflume.root.logger=INFO,console

SLF4J: Found binding in [jar:file:/home/hadoop/app/hbase-0.98.19/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: Found binding in [jar:file:/home/hadoop/app/hive-1.0.0/lib/hive-jdbc-1.0.0-standalone.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.

2017-07-27 12:41:49,451 (lifecycleSupervisor-1-0) [INFO - org.apache.flume.node.PollingPropertiesFileConfigurationProvider.start(PollingPropertiesFileConfigurationProvider.java:62)] Configuration provider starting

2017-07-27 12:41:50,137 (conf-file-poller-0) [INFO - org.apache.flume.node.PollingPropertiesFileConfigurationProvider$FileWatcherRunnable.run(PollingPropertiesFileConfigurationProvider.java:134)] Reloading configuration file:conf_HostInterceptor/flume-conf.properties

2017-07-27 12:41:50,188 (conf-file-poller-0) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:1016)] Processing:k1

2017-07-27 12:41:50,189 (conf-file-poller-0) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:1016)] Processing:k1

2017-07-27 12:41:50,189 (conf-file-poller-0) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:930)] Added sinks: k1 Agent: agent1

2017-07-27 12:41:50,280 (conf-file-poller-0) [INFO - org.apache.flume.conf.FlumeConfiguration.validateConfiguration(FlumeConfiguration.java:140)] Post-validation flume configuration contains configuration for agents: [agent1]

2017-07-27 12:41:50,280 (conf-file-poller-0) [INFO - org.apache.flume.node.AbstractConfigurationProvider.loadChannels(AbstractConfigurationProvider.java:147)] Creating channels

2017-07-27 12:41:50,337 (conf-file-poller-0) [INFO - org.apache.flume.channel.DefaultChannelFactory.create(DefaultChannelFactory.java:42)] Creating instance of channel c1 type memory

2017-07-27 12:41:50,423 (conf-file-poller-0) [INFO - org.apache.flume.node.AbstractConfigurationProvider.loadChannels(AbstractConfigurationProvider.java:201)] Created channel c1

2017-07-27 12:41:50,425 (conf-file-poller-0) [INFO - org.apache.flume.source.DefaultSourceFactory.create(DefaultSourceFactory.java:41)] Creating instance of source r1, type netcat

2017-07-27 12:41:51,478 (conf-file-poller-0) [INFO - org.apache.flume.sink.DefaultSinkFactory.create(DefaultSinkFactory.java:42)] Creating instance of sink: k1, type: logger

2017-07-27 12:41:51,490 (conf-file-poller-0) [INFO - org.apache.flume.node.AbstractConfigurationProvider.getConfiguration(AbstractConfigurationProvider.java:116)] Channel c1 connected to [r1, k1]

2017-07-27 12:41:52,050 (conf-file-poller-0) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:137)] Starting new configuration:{ sourceRunners:{r1=EventDrivenSourceRunner: { source:org.apache.flume.source.NetcatSource{name:r1,state:IDLE} }} sinkRunners:{k1=SinkRunner: { policy:org.apache.flume.sink.DefaultSinkProcessor@13f948e counterGroup:{ name:null counters:{} } }} channels:{c1=org.apache.flume.channel.MemoryChannel{name: c1}} }

2017-07-27 12:41:52,052 (conf-file-poller-0) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:144)] Starting Channel c1

2017-07-27 12:41:53,484 (lifecycleSupervisor-1-0) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.register(MonitoredCounterGroup.java:119)] Monitored counter group for type: CHANNEL, name: c1: Successfully registered new MBean.

2017-07-27 12:41:53,517 (lifecycleSupervisor-1-0) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.start(MonitoredCounterGroup.java:95)] Component type: CHANNEL, name: c1 started

2017-07-27 12:41:53,522 (conf-file-poller-0) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:171)] Starting Sink k1

2017-07-27 12:41:53,524 (conf-file-poller-0) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:182)] Starting Source r1

2017-07-27 12:41:53,531 (lifecycleSupervisor-1-3) [INFO - org.apache.flume.source.NetcatSource.start(NetcatSource.java:155)] Source starting

2017-07-27 12:41:54,384 (lifecycleSupervisor-1-3) [INFO - org.apache.flume.source.NetcatSource.start(NetcatSource.java:169)] Created serverSocket:sun.nio.ch.ServerSocketChannelImpl[/127.0.0.1:44444]

　　等待数据的采集

[hadoop@master ~]$ yum -y install telnet

Loaded plugins: fastestmirror, refresh-packagekit, security

You need to be root to perform this command.

[hadoop@master ~]$ su root

Password:

[root@master hadoop]# yum -y install telnet

Loaded plugins: fastestmirror, refresh-packagekit, security

Loading mirror speeds from cached hostfile

 * base: mirrors.cqu.edu.cn

 * extras: mirrors.sohu.com

　　成功地，然后，这边随便输入什么。比如hello

[root@master ~]# telnet localhost 44444

Trying ::1...

telnet: connect to address ::1: Connection refused

Trying 127.0.0.1...

Connected to localhost.

Escape character is '^]'.

hello

OK

Event: { headers:{hostname=192.168.80.145} body: 68 65 6C 6C 6F 0D                               hello. }

　　这就是Host Interceptor的作用体现！

agent1.sources.r1.interceptors = i1

agent1.sources.r1.interceptors.i1.type = host

agent1.sources.r1.interceptors.i1.hostHeader = hostname

　　若想要如下的效果，则

Event: { headers:{hostname=master} body: 7A 68 6F 75 6C 73 0D                            zhouls. }

　　则

agent1.sources = r1

agent1.sinks = k1

agent1.channels = c1

# Describe/configure the source

agent1.sources.r1.type = netcat

agent1.sources.r1.bind = localhost

agent1.sources.r1.port = 

agent1.sources.r1.interceptors = i1

agent1.sources.r1.interceptors.i1.type = host

agent1.sources.r1.interceptors.i1.useIP = false

agent1.sources.r1.interceptors.i1.hostHeader = hostname

# Use a channel which buffers events in memory

agent1.channels.c1.type = memory

agent1.channels.c1.capacity =

agent1.channels.c1.transactionCapacity = 

# Bind the source and sink to the channel

agent1.sources.r1.channels = c1

agent1.sinks.k1.channel = c1

# Describe the sink

agent1.sinks.k1.type = logger

[hadoop@master flume-1.7.]$ bin/flume-ng agent --conf conf_HostInterceptor/  --conf-file conf_HostInterceptor/flume-conf.properties --name agent1  -Dflume.root.logger=INFO,console

[root@master ~]# telnet localhost

Trying ::...

telnet: connect to address ::: Connection refused

Trying 127.0.0.1...

Connected to localhost.

Escape character is '^]'.

zhouls

OK

Event: { headers:{hostname=master} body: 7A 68 6F 75 6C 73 0D                            zhouls. }

Regex Extractor Interceptor（正则抽取拦截器）

　　conf_RegexExtractorInterceptor的flume-conf.properties

[hadoop@master conf_RegexExtractorInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_RegexExtractorInterceptor

[hadoop@master conf_RegexExtractorInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_RegexExtractorInterceptor]$ vim flume-conf.properties

　　首先，我们来说说这个拦截器的应用场景　　

　　假设，有如下的flume测试数据

video_info

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

{"id":"","uid":"","lat":"53.530598","lnt":"-2.5620373","hots":,"title":"","status":"","topicId":"","end_time":"","watch_num":,"share_num":"","replay_url":null,"replay_num":,"start_time":"","timestamp":,"type":"video_info"}

userinfo

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

{"uid":"","nickname":"mick","usign":"","sex":,"birthday":"","face":"","big_face":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"","level":,"exp":,"anchor_level":,"anchor_exp":,"os":"android","timestamp":,"type":"userinfo"}

gift_record

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

{"send_id":"","good_id":"","video_id":"","gold":"","timestamp":,"type":"gift_record"}

　　以上是flume采集后的数据。假设都是在这个flume测试数据.txt里，现在呢，我想按照type来存放到不同的目录下。

　　即video_info的存放到video_info目录下、userinfo的存放到userinfo目录下、gift_record的存放到gift_record目录下。

　　则，这样的应用场景，即根据数据里内容的type字段的值的不同，来分别存储。则需要Regex Extractor Interceptor派上用场了。

　　　怎么做呢，其实很简单，把type的值，放到

# 定义拦截器

agent1.sources.r1.interceptors = i1

# 设置拦截器类型

agent1.sources.r1.interceptors.i1.type = regex_extractor

# 设置正则表达式，匹配指定的数据，这样设置会在数据的header中增加log_type=”对应的值”

agent1.sources.r1.interceptors.i1.regex = "type":"(\\w+)"

agent1.sources.r1.interceptors.i1.serializers = s1

agent1.sources.r1.interceptors.i1.serializers.s1.name = log_type

　　为什么是这么来写？

agent1.sources.r1.interceptors.i1.regex = "type":"(\\w+)"

　　是因为数据的内容决定的。

"type":"video_info"

"type":"userinfo"

"type":"gift_record"

#source的名字

agent1.sources = fileSource

# channels的名字，建议按照type来命名

agent1.channels = memoryChannel

# sink的名字，建议按照目标来命名

agent1.sinks = hdfsSink

# 指定source使用的channel名字

agent1.sources.fileSource.channels = memoryChannel

# 指定sink需要使用的channel的名字,注意这里是channel

agent1.sinks.hdfsSink.channel = memoryChannel

agent1.sources.fileSource.type = exec

agent1.sources.fileSource.command = tail -F /usr/local/log/server.log

#------- fileChannel-1相关配置-------------------------

# channel类型

agent1.channels.memoryChannel.type = memory

agent1.channels.memoryChannel.capacity =

agent1.channels.memoryChannel.transactionCapacity =

agent1.channels.memoryChannel.byteCapacityBufferPercentage =

agent1.channels.memoryChannel.byteCapacity = 

#---------拦截器相关配置------------------

# 定义拦截器

agent1.sources.fileSource.interceptors = i1

# 设置拦截器类型

agent1.sources.fileSource.interceptors.i1.type = regex_extractor

# 设置正则表达式，匹配指定的数据，这样设置会在数据的header中增加log_type="某个值"

agent1.sources.fileSource.interceptors.i1.regex = "type":"(\\w+)"

agent1.sources.fileSource.interceptors.i1.serializers = s1

agent1.sources.fileSource.interceptors.i1.serializers.s1.name = log_type

#---------hdfsSink 相关配置------------------

agent1.sinks.hdfsSink.type = hdfs

# 注意, 我们输出到下面一个子文件夹datax中

agent1.sinks.hdfsSink.hdfs.path = hdfs://master:9000/data/types/%Y%m%d/%{log_type}

agent1.sinks.hdfsSink.hdfs.writeFormat = Text

agent1.sinks.hdfsSink.hdfs.fileType = DataStream

agent1.sinks.hdfsSink.hdfs.callTimeout =

agent1.sinks.hdfsSink.hdfs.useLocalTimeStamp = true

#当文件大小为52428800字节时，将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollSize =

#events数据达到该数量的时候，将临时文件滚动成目标文件

agent1.sinks.hdfsSink.hdfs.rollCount =

#每隔N s将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollInterval = 

#配置前缀和后缀

agent1.sinks.hdfsSink.hdfs.filePrefix=run

agent1.sinks.hdfsSink.hdfs.fileSuffix=.data

　　监控文件是在

/usr/local/log/server.log

[root@master local]# pwd

/usr/local

[root@master local]# ll

total

drwxr-xr-x.  root root  Sep    bin

drwxr-xr-x.  root root  Sep    etc

drwxr-xr-x.  root root  Sep    games

drwxr-xr-x.  root root  May   : include

drwxr-xr-x.  root root  May   : lib

drwxr-xr-x.  root root  Sep    lib64

drwxr-xr-x.  root root  Sep    libexec

drwxr-xr-x.  root root  Sep    sbin

drwxr-xr-x.  root root  May   : share

drwxr-xr-x.  root root  Sep    src

[root@master local]# mkdir log

[root@master local]# cd log

[root@master log]# pwd

/usr/local/log

[root@master log]# ll

total

[root@master log]#

　　然后，执行

[hadoop@master flume-1.7.]$ bin/flume-ng agent --conf conf_RegexExtractorInterceptor/  --conf-file conf_RegexExtractorInterceptor/flume-conf.properties --name agent1  -Dflume.root.logger=INFO,console

　　然后，我这边，采用如下的一个shell脚本来模拟产生测试数据。

　　producerLog.sh

[root@master log]# pwd

/usr/local/log

[root@master log]# ll

total

[root@master log]# vim producerLog.sh

#!/bin/bash

log1='{"id":"14943445328940974610","uid":"840717325115457536","lat":"53.530598","lnt":"-2.5620373","hot

s":0,"title":"","status":"","topicId":"","end_time":"","watch_num":0,"share_num":"","repl

ay_url":null,"replay_num":0,"start_time":"","timestamp":1494344571,"type":"video_info"}'

log2='{"uid":"861848974414839810","nickname":"mick","usign":"","sex":1,"birthday":"","face":"","big_fac

e":"","email":"abc@qq.com","mobile":"","reg_type":"","last_login_time":"","reg_time":"

","last_update_time":"","status":"","is_verified":"","verified_info":"","is_seller":"

","level":1,"exp":0,"anchor_level":0,"anchor_exp":0,"os":"android","timestamp":1494344580,"type":"user_info"}'

log3='{"send_id":"834688818270961664","good_id":"223","video_id":"14943443045138661356","gold":"10","ti

mestamp":1494344574,"type":"gift_record"}'

declare -i count

count=

while [ 'a' = 'a' ]

do

echo -e $log1 >> /usr/local/log/server.log

echo -e $log2 >> /usr/local/log/server.log

echo -e $log3 >> /usr/local/log/server.log

count+=

    if [ ${count} -eq  ]

    then

    count=

    echo "sleep..."

    sleep

    fi

done

　　这个shell脚本不太难哈。即log1会生成500条、log2会生成500条、log3会生成500条。每隔3秒。

　　然后，再来创建server.log文件

[root@master log]# pwd

/usr/local/log

[root@master log]# ll

total

-rw-r--r--  root root  Jul  : producerLog.sh

[root@master log]# vim producerLog.sh

[root@master log]# touch server.log

[root@master log]# ll

total

-rw-r--r--  root root  Jul  : producerLog.sh

-rw-r--r--  root root     Jul  : server.log

[root@master log]# cat server.log

[root@master log]#

　　然后，来执行这个脚本，以模拟产生数据。

[root@master log]# pwd

/usr/local/log

[root@master log]# ll

total

-rw-r--r--  root root  Jul  : producerLog.sh

-rw-r--r--  root root     Jul  : server.log

[root@master log]# chmod  producerLog.sh

[root@master log]# ll

total

-rwxr-xr-x  root root  Jul  : producerLog.sh

-rw-r--r--  root root     Jul  : server.log

[root@master log]# ./producerLog.sh

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [WARN - org.apache.flume.sink.hdfs.BucketWriter.append(BucketWriter.java:)] Block Under-replication detected. Rotating file.

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:)] Closing hdfs://master:9000/data/types/20170727//run.1501137914366.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [INFO - org.apache.flume.sink.hdfs.BucketWriter$.call(BucketWriter.java:)] Renaming hdfs://master:9000/data/types/20170727/run.1501137914366.data.tmp to hdfs://master:9000/data/types/20170727/run.1501137914366.data

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170727//run.1501137914367.data.tmp

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [WARN - org.apache.flume.sink.hdfs.BucketWriter.append(BucketWriter.java:)] Block Under-replication detected. Rotating file.

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:)] Closing hdfs://master:9000/data/types/20170727/video_info/run.1501137883920.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [INFO - org.apache.flume.sink.hdfs.BucketWriter$.call(BucketWriter.java:)] Renaming hdfs://master:9000/data/types/20170727/video_info/run.1501137883920.data.tmp to hdfs://master:9000/data/types/20170727/video_info/run.1501137883920.data

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170727/video_info/run.1501137883921.data.tmp

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [WARN - org.apache.flume.sink.hdfs.BucketWriter.append(BucketWriter.java:)] Block Under-replication detected. Rotating file.

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:)] Closing hdfs://master:9000/data/types/20170727//run.1501137914367.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [INFO - org.apache.flume.sink.hdfs.BucketWriter$.call(BucketWriter.java:)] Renaming hdfs://master:9000/data/types/20170727/run.1501137914367.data.tmp to hdfs://master:9000/data/types/20170727/run.1501137914367.data

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170727//run.1501137914368.data.tmp

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [WARN - org.apache.flume.sink.hdfs.BucketWriter.append(BucketWriter.java:)] Block Under-replication detected. Rotating file.

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:)] Closing hdfs://master:9000/data/types/20170727/gift_record/run.1501137916399.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [INFO - org.apache.flume.sink.hdfs.BucketWriter$.call(BucketWriter.java:)] Renaming hdfs://master:9000/data/types/20170727/gift_record/run.1501137916399.data.tmp to hdfs://master:9000/data/types/20170727/gift_record/run.1501137916399.data

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170727/gift_record/run.1501137916400.data.tmp

Search and Replace Interceptor

　　以上存放，是在

　　模拟产生的gift_record是存放在/data/types/20170727/gift_record

　　但是呢。我现在需求是

　　模拟产生的gift_record是存放在/data/types/20170727/giftRecord

　　则改为

agent1.sources.r1.interceptors = i1 i2 i3 i4

agent1.sources.r1.interceptors.i1.type = search_replace

agent1.sources.r1.interceptors.i1.searchPattern = "type":"gift_record"

agent1.sources.r1.interceptors.i1.replaceString = "type":"giftRecord"

agent1.sources.r1.interceptors.i2.type = search_replace

agent1.sources.r1.interceptors.i2.searchPattern = "type":"video_info"

agent1.sources.r1.interceptors.i2.replaceString = "type":"videoInfo"

agent1.sources.r1.interceptors.i3.type = search_replace

agent1.sources.r1.interceptors.i3.searchPattern = "type":"user_info"

agent1.sources.r1.interceptors.i3.replaceString = "type":"userInfo"

agent1.sources.fileSource.interceptors.i4.type = regex_extractor

agent1.sources.fileSource.interceptors.i4.regex = "type":"(\\w+)"

agent1.sources.fileSource.interceptors.i4.serializers = s1

agent1.sources.fileSource.interceptors.i4.serializers.s1.name = log_type

[hadoop@master conf_SearchandReplaceInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_SearchandReplaceInterceptor

[hadoop@master conf_SearchandReplaceInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_SearchandReplaceInterceptor]$ vim flume-conf.properties

#source的名字

agent1.sources = fileSource

# channels的名字，建议按照type来命名

agent1.channels = memoryChannel

# sink的名字，建议按照目标来命名

agent1.sinks = hdfsSink

# 指定source使用的channel名字

agent1.sources.fileSource.channels = memoryChannel

# 指定sink需要使用的channel的名字,注意这里是channel

agent1.sinks.hdfsSink.channel = memoryChannel

agent1.sources.fileSource.type = exec

agent1.sources.fileSource.command = tail -F /usr/local/log/server.log

#------- fileChannel-1相关配置-------------------------

# channel类型

agent1.channels.memoryChannel.type = memory

agent1.channels.memoryChannel.capacity =

agent1.channels.memoryChannel.transactionCapacity =

agent1.channels.memoryChannel.byteCapacityBufferPercentage =

agent1.channels.memoryChannel.byteCapacity = 

#---------拦截器相关配置------------------

agent1.sources.r1.interceptors = i1 i2 i3 i4
agent1.sources.r1.interceptors.i1.type = search_replace
agent1.sources.r1.interceptors.i1.searchPattern = "type":"gift_record"
agent1.sources.r1.interceptors.i1.replaceString = "type":"giftRecord"

agent1.sources.r1.interceptors.i2.type = search_replace
agent1.sources.r1.interceptors.i2.searchPattern = "type":"video_info"
agent1.sources.r1.interceptors.i2.replaceString = "type":"videoInfo"

agent1.sources.r1.interceptors.i3.type = search_replace
agent1.sources.r1.interceptors.i3.searchPattern = "type":"user_info"
agent1.sources.r1.interceptors.i3.replaceString = "type":"userInfo"

agent1.sources.fileSource.interceptors.i4.type = regex_extractor

agent1.sources.fileSource.interceptors.i4.regex = "type":"(\\w+)"

agent1.sources.fileSource.interceptors.i4.serializers = s1

agent1.sources.fileSource.interceptors.i4.serializers.s1.name = log_type

#---------hdfsSink 相关配置------------------

agent1.sinks.hdfsSink.type = hdfs

# 注意, 我们输出到下面一个子文件夹datax中

agent1.sinks.hdfsSink.hdfs.path = hdfs://master:9000/data/types/%Y%m%d/%{log_type}

agent1.sinks.hdfsSink.hdfs.writeFormat = Text

agent1.sinks.hdfsSink.hdfs.fileType = DataStream

agent1.sinks.hdfsSink.hdfs.callTimeout =

agent1.sinks.hdfsSink.hdfs.useLocalTimeStamp = true

#当文件大小为52428800字节时，将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollSize =

#events数据达到该数量的时候，将临时文件滚动成目标文件

agent1.sinks.hdfsSink.hdfs.rollCount =

#每隔N s将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollInterval = 

#配置前缀和后缀

agent1.sinks.hdfsSink.hdfs.filePrefix=run

agent1.sinks.hdfsSink.hdfs.fileSuffix=.data

　　然后，执行

[hadoop@master flume-1.7.]$ bin/flume-ng agent --conf conf_SearchandReplaceInterceptor/  --conf-file conf_SearchandReplaceInterceptor/flume-conf.properties --name agent1  -Dflume.root.logger=INFO,console

　　我这里，出现了这个错误

-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.start(MonitoredCounterGroup.java:)] Component type: SOURCE, name: fileSource started

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.HDFSDataStream.configure(HDFSDataStream.java:)] Serializer = TEXT, UseRawLocalFileSystem = false

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170729//run.1501294672792.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [WARN - org.apache.hadoop.util.NativeCodeLoader.<clinit>(NativeCodeLoader.java:)] Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

-- ::, (pool--thread-) [ERROR - org.apache.flume.source.ExecSource$ExecRunnable.run(ExecSource.java:)] Failed while running command: tail -F /usr/local/log/server.log

org.apache.flume.ChannelFullException: Space for commit to queue couldn't be acquired. Sinks are likely not keeping up with sources, or the buffer size is too tight

    at org.apache.flume.channel.MemoryChannel$MemoryTransaction.doCommit(MemoryChannel.java:)

    at org.apache.flume.channel.BasicTransactionSemantics.commit(BasicTransactionSemantics.java:)

    at org.apache.flume.channel.ChannelProcessor.processEventBatch(ChannelProcessor.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.flushEventBatch(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.run(ExecSource.java:)

    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:)

    at java.util.concurrent.FutureTask.run(FutureTask.java:)

    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:)

    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:)

    at java.lang.Thread.run(Thread.java:)

-- ::, (timedFlushExecService21-) [ERROR - org.apache.flume.source.ExecSource$ExecRunnable$.run(ExecSource.java:)] Exception occured when processing event batch

org.apache.flume.ChannelException: java.lang.InterruptedException

    at org.apache.flume.channel.BasicTransactionSemantics.commit(BasicTransactionSemantics.java:)

    at org.apache.flume.channel.ChannelProcessor.processEventBatch(ChannelProcessor.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.flushEventBatch(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.access$(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable$.run(ExecSource.java:)

    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:)

    at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:)

    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$(ScheduledThreadPoolExecutor.java:)

    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:)

　　然后，这边模拟产生数据。

[root@master log]# pwd

/usr/local/log

[root@master log]# ll

total

-rwxr-xr-x  root root  Jul  : producerLog.sh

-rw-r--r--  root root     Jul  : server.log

[root@master log]# ./producerLog.sh

sleep...

sleep...

sleep...

Flume自定义拦截器（Interceptors）

一、自定义拦截器类型必须是：类全名$内部类名，其实就是内部类名称
　　如：zhouls.bigdata.MySearchAndReplaceInterceptor$Builder

　　由于有时候内置的拦截器不够用，所以需要针对特殊的业务需求自定义拦截器
　　官方文档中没有发现自定义interceptor的步骤，但是可以根据flume源码参考内置的拦截器的代码
　　flume-1.7/flume-ng-core/src/main/java/org/apache/flume/interceptor/HostInterceptor.java

　　大家，去https://github.com/找到，因为，我的flume是1.7.0的。所以如下

　　修改后的pom.xml为

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">

    <modelVersion>4.0.</modelVersion>

    <groupId>zhouls.bigdata</groupId>

    <artifactId>flumeDemo</artifactId>

    <version>0.0.-SNAPSHOT</version>

    <packaging>jar</packaging>

    <name>flumeDemo</name>

    <url>http://maven.apache.org</url>

    <properties>

        <project.build.sourceEncoding>UTF-</project.build.sourceEncoding>

    </properties>

    <dependencies>

        <dependency>

            <groupId>junit</groupId>

            <artifactId>junit</artifactId>

            <version>4.12</version>

            <scope>test</scope>

        </dependency>

        <!-- 此版本的curator操作的zk是3..6版本 -->

        <dependency>

            <groupId>org.apache.curator</groupId>

            <artifactId>curator-framework</artifactId>

            <version>2.10.</version>

        </dependency>

    <!-- https://mvnrepository.com/artifact/org.apache.flume/flume-ng-core -->

    <dependency>

        <groupId>org.apache.flume</groupId>

        <artifactId>flume-ng-core</artifactId>

        <version>1.7.</version>

    </dependency> 

    </dependencies>

</project>

　　然后，我这里，参考github上的给定参考代码，来写出属于我们自己业务需求的flume自定义拦截器代码编程。

　　MySearchAndReplaceInterceptor.java.java

package zhouls.bigdata.flumeDemo;

import com.google.common.base.Preconditions;

import org.apache.commons.lang.StringUtils;

import org.apache.flume.Context;

import org.apache.flume.Event;

import org.apache.flume.interceptor.Interceptor;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import java.util.HashMap;

import java.util.List;

import java.util.regex.Matcher;

import java.util.regex.Pattern;

/**

 * Created by zhouls.

 *

 * 使用说明：

 * ======================================================

 * # 定义拦截器

 * agent.sources.kafkaSource.interceptors = i0

 * # 设置拦截器类型

 * # gift_record:giftRecord的意思是会把日志中的gift_record替换为giftRecord

 * agent.sources.kafkaSource.interceptors.i0.type = zhouls.MySearchAndReplaceInterceptor

 * agent.sources.kafkaSource.interceptors.i0.searchReplace = "gift_record:giftRecord,video_info:videoInfo"

 * ======================================================

 */

public class MySearchAndReplaceInterceptor implements Interceptor {

    private static final Logger logger = LoggerFactory

            .getLogger(MySearchAndReplaceInterceptor.class);

    /**

     * 需要替换的字符串信息

     * 格式："key:value,key:value"

     */

    private final String search_replace;

    private String[] splits;

    private String[] key_value;

    private String key;

    private String value;

    private HashMap<String, String> hashMap = new HashMap<String, String>();

    private Pattern compile = Pattern.compile("\"type\":\"(\\w+)\"");

    private Matcher matcher;

    private String group;

    private MySearchAndReplaceInterceptor(String search_replace) {

        this.search_replace = search_replace;

    }

    /**

     * 初始化放在，最开始执行一次

     * 把配置的数据初始化到map中，方便后面调用

     */

    public void initialize() {

        try{

            if(StringUtils.isNotBlank(search_replace)){

                splits = search_replace.split(",");

                for (String key_value_pair:splits) {

                    key_value = key_value_pair.split(":");

                    key = key_value[];

                    value = key_value[];

                    hashMap.put(key,value);

                }

            }

        }catch (Exception e){

            logger.error("数据格式错误，初始化失败。"+search_replace,e.getCause());

        }

    }

    public void close() {

    }

    /**

     * 具体的处理逻辑

     * @param event

     * @return

     */

    public Event intercept(Event event) {

        try{

            String origBody = new String(event.getBody());

            matcher = compile.matcher(origBody);

            if(matcher.find()){

                group = matcher.group();

                if(StringUtils.isNotBlank(group)){

                    String newBody = origBody.replaceAll("\"type\":\""+group+"\"", "\"type\":\""+hashMap.get(group)+"\"");

                    event.setBody(newBody.getBytes());

                }

            }

        }catch (Exception e){

            logger.error("拦截器处理失败！",e.getCause());

        }

        return event;

    }

    public List<Event> intercept(List<Event> events) {

        for (Event event : events) {

            intercept(event);

        }

        return events;

    }

    public static class Builder implements Interceptor.Builder {

        private static final String SEARCH_REPLACE_KEY = "searchReplace";

        private String searchReplace;

        public void configure(Context context) {

            searchReplace = context.getString(SEARCH_REPLACE_KEY);

            Preconditions.checkArgument(!StringUtils.isEmpty(searchReplace),

                    "Must supply a valid search pattern " + SEARCH_REPLACE_KEY +

                            " (may not be empty)");

        }

        public Interceptor build() {

            Preconditions.checkNotNull(searchReplace,

                    "Regular expression searchReplace required");

            return new MySearchAndReplaceInterceptor(searchReplace);

        }

    }

}

　　然后把MySearchAndReplaceInterceptor这个类导出成一个jar包。

　　同时，大家也可以用maven来打jar包

　　把这个jar包上传到flume1.7.0的lib目录下

[hadoop@master lib]$ rz

[hadoop@master lib]$ ls

apache-log4j-extras-1.1.jar    flume-file-channel-1.7..jar              flume-taildir-source-1.7..jar  kite-data-core-1.0..jar             parquet-hive-bundle-1.4..jar

async-1.4..jar                flume-hdfs-sink-1.7..jar                 flume-thrift-source-1.7..jar   kite-data-hbase-1.0..jar            parquet-jackson-1.4..jar

asynchbase-1.7..jar           flume-hive-sink-1.7..jar                 flume-tools-1.7..jar           kite-data-hive-1.0..jar             protobuf-java-2.5..jar

avro-1.7..jar                 flume-irc-sink-1.7..jar                  flume-twitter-source-1.7..jar  kite-hadoop-compatibility-1.0..jar  scala-library-2.10..jar

avro-ipc-1.7..jar             flume-jdbc-channel-1.7..jar              gson-2.2..jar                  libthrift-0.9..jar                  serializer-2.7..jar

commons-cli-1.2.jar            flume-jms-source-1.7..jar                guava-11.0..jar                log4j-1.2..jar                     servlet-api-2.5-.jar

commons-codec-1.8.jar          flume-kafka-channel-1.7..jar             httpclient-4.2..jar            lz4-1.2..jar                        slf4j-api-1.6..jar

commons-collections-3.2..jar  flume-kafka-source-1.7..jar              httpcore-4.1..jar              mapdb-0.9..jar                      slf4j-log4j12-1.6..jar

commons-compress-1.4..jar     flume-ng-auth-1.7..jar                   irclib-1.10.jar                 metrics-core-2.2..jar               snappy-java-1.1..jar

commons-dbcp-1.4.jar           flume-ng-configuration-1.7..jar          jackson-annotations-2.3..jar   mina-core-2.0..jar                  twitter4j-core-3.0..jar

commons-io-2.1.jar             flume-ng-core-1.7..jar                   jackson-core-2.3..jar          MySearchAndReplaceInterceptor.jar    twitter4j-media-support-3.0..jar

commons-jexl-2.1..jar         flume-ng-elasticsearch-sink-1.7..jar     jackson-core-asl-1.9..jar      netty-3.9..Final.jar                twitter4j-stream-3.0..jar

commons-lang-2.5.jar           flume-ng-embedded-agent-1.7..jar         jackson-databind-2.3..jar      opencsv-2.3.jar                      velocity-1.7.jar

commons-logging-1.1..jar      flume-ng-hbase-sink-1.7..jar             jackson-mapper-asl-1.9..jar    paranamer-2.3.jar                    xalan-2.7..jar

commons-pool-1.5..jar         flume-ng-kafka-sink-1.7..jar             jetty-6.1..jar                parquet-avro-1.4..jar               xercesImpl-2.9..jar

curator-client-2.6..jar       flume-ng-log4jappender-1.7..jar          jetty-util-6.1..jar           parquet-column-1.4..jar             xml-apis-1.3..jar

curator-framework-2.6..jar    flume-ng-morphline-solr-sink-1.7..jar    joda-time-2.1.jar               parquet-common-1.4..jar             xz-1.0.jar

curator-recipes-2.6..jar      flume-ng-node-1.7..jar                   jopt-simple-3.2.jar             parquet-encoding-1.4..jar           zkclient-0.7.jar

derby-10.11.1.1.jar            flume-ng-sdk-1.7..jar                    jsr305-1.3..jar                parquet-format-2.0..jar

flume-avro-source-1.7..jar    flume-scribe-source-1.7..jar             kafka_2.-0.9.0.1.jar          parquet-generator-1.4..jar

flume-dataset-sink-1.7..jar   flume-spillable-memory-channel-1.7..jar  kafka-clients-0.9.0.1.jar       parquet-hadoop-1.4..jar

[hadoop@master lib]$ pwd

/home/hadoop/app/flume-1.7./lib

[hadoop@master lib]$

drwxr-xr-x   hadoop hadoop   Apr  : conf

drwxr-xr-x   hadoop hadoop   Jul  : conf_HostInterceptor

drwxr-xr-x   hadoop hadoop   Jul  : conf_RegexExtractorInterceptor

drwxr-xr-x   hadoop hadoop   Jul  : conf_SearchandReplaceInterceptor

-rw-r--r--   hadoop hadoop   Sep    DEVNOTES

-rw-r--r--   hadoop hadoop   Sep    doap_Flume.rdf

drwxr-xr-x  hadoop hadoop   Oct    docs

drwxrwxr-x   hadoop hadoop   Jul  : lib

-rw-r--r--   hadoop hadoop  Oct    LICENSE

-rw-r--r--   hadoop hadoop    Sep    NOTICE

-rw-r--r--   hadoop hadoop   Sep    README.md

-rw-r--r--   hadoop hadoop   Oct    RELEASE-NOTES

drwxrwxr-x   hadoop hadoop   Apr  : tools

[hadoop@master flume-1.7.]$ cp -r conf conf_MySearchAndReplaceInterceptor

[hadoop@master flume-1.7.]$ ll

total

drwxr-xr-x   hadoop hadoop   Apr  : bin

-rw-r--r--   hadoop hadoop  Oct    CHANGELOG

drwxr-xr-x   hadoop hadoop   Apr  : conf

drwxr-xr-x   hadoop hadoop   Jul  : conf_HostInterceptor

drwxr-xr-x   hadoop hadoop   Jul  : conf_MySearchAndReplaceInterceptor

drwxr-xr-x   hadoop hadoop   Jul  : conf_RegexExtractorInterceptor

drwxr-xr-x   hadoop hadoop   Jul  : conf_SearchandReplaceInterceptor

-rw-r--r--   hadoop hadoop   Sep    DEVNOTES

-rw-r--r--   hadoop hadoop   Sep    doap_Flume.rdf

drwxr-xr-x  hadoop hadoop   Oct    docs

drwxrwxr-x   hadoop hadoop   Jul  : lib

-rw-r--r--   hadoop hadoop  Oct    LICENSE

-rw-r--r--   hadoop hadoop    Sep    NOTICE

-rw-r--r--   hadoop hadoop   Sep    README.md

-rw-r--r--   hadoop hadoop   Oct    RELEASE-NOTES

drwxrwxr-x   hadoop hadoop   Apr  : tools

[hadoop@master flume-1.7.]$

　　修改好log4j.properties ，为了方便管理查看日志

[hadoop@master conf_MySearchAndReplaceInterceptor]$ pwd

/home/hadoop/app/flume-1.7./conf_MySearchAndReplaceInterceptor

[hadoop@master conf_MySearchAndReplaceInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_MySearchAndReplaceInterceptor]$ mv flume-conf.properties.template flume-conf.properties

[hadoop@master conf_MySearchAndReplaceInterceptor]$ vim log4j.properties

#flume.root.logger=DEBUG,console

flume.root.logger=INFO,LOGFILE

flume.log.dir=./logs

flume.log.file=flume_MySearchAndReplaceInterceptor.log

[hadoop@master conf_MySearchAndReplaceInterceptor]$ ll

total

-rw-r--r--  hadoop hadoop  Jul  : flume-conf.properties

-rw-r--r--  hadoop hadoop  Jul  : flume-env.ps1.template

-rw-r--r--  hadoop hadoop  Jul  : flume-env.sh.template

-rw-r--r--  hadoop hadoop  Jul  : log4j.properties

[hadoop@master conf_MySearchAndReplaceInterceptor]$ vim flume-conf.properties

　　然后，修改flume的配置文件如下：

　　注意：不能为上面。

　　除非你的程序需要引号（“”），否则不要加引号（“”），本程序不需要引号，因此是错误的

#source的名字

agent1.sources = fileSource

# channels的名字，建议按照type来命名

agent1.channels = memoryChannel

# sink的名字，建议按照目标来命名

agent1.sinks = hdfsSink

# 指定source使用的channel名字

agent1.sources.fileSource.channels = memoryChannel

# 指定sink需要使用的channel的名字,注意这里是channel

agent1.sinks.hdfsSink.channel = memoryChannel

agent1.sources.fileSource.type = exec

agent1.sources.fileSource.command = tail -F /usr/local/log/server.log

#------- fileChannel-1相关配置-------------------------

# channel类型

agent1.channels.memoryChannel.type = memory

agent1.channels.memoryChannel.capacity =

agent1.channels.memoryChannel.transactionCapacity =

agent1.channels.memoryChannel.byteCapacityBufferPercentage =

agent1.channels.memoryChannel.byteCapacity = 

#---------拦截器相关配置------------------

#定义拦截器

agent1.sources.r1.interceptors = i1 i2

# 设置拦截器类型

agent1.sources.r1.interceptors.i1.type = zhouls.bigdata.MySearchAndReplaceInterceptor

agent1.sources.r1.interceptors.i1.searchReplace = gift_record:giftRecord,video_info:videoInfo,user_info:userInfo

# 设置拦截器类型

agent1.sources.r1.interceptors.i2.type = regex_extractor

# 设置正则表达式，匹配指定的数据，这样设置会在数据的header中增加log_type="某个值"

agent1.sources.r1.interceptors.i2.regex = "type":"(\\w+)"

agent1.sources.r1.interceptors.i2.serializers = s1

agent1.sources.r1.interceptors.i2.serializers.s1.name = log_type



#---------hdfsSink 相关配置------------------

agent1.sinks.hdfsSink.type = hdfs

# 注意, 我们输出到下面一个子文件夹datax中

agent1.sinks.hdfsSink.hdfs.path = hdfs://master:9000/data/types/%Y%m%d/%{log_type}

agent1.sinks.hdfsSink.hdfs.writeFormat = Text

agent1.sinks.hdfsSink.hdfs.fileType = DataStream

agent1.sinks.hdfsSink.hdfs.callTimeout =

agent1.sinks.hdfsSink.hdfs.useLocalTimeStamp = true

#当文件大小为52428800字节时，将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollSize =

#events数据达到该数量的时候，将临时文件滚动成目标文件

agent1.sinks.hdfsSink.hdfs.rollCount =

#每隔N s将临时文件滚动成一个目标文件

agent1.sinks.hdfsSink.hdfs.rollInterval = 

#配置前缀和后缀

agent1.sinks.hdfsSink.hdfs.filePrefix=run

agent1.sinks.hdfsSink.hdfs.fileSuffix=.data

　　主要在里面添加拦截器的配置是如下

#---------拦截器相关配置------------------

#定义拦截器

agent1.sources.r1.interceptors = i1 i2

# 设置拦截器类型

agent1.sources.r1.interceptors.i1.type = zhouls.bigdata.MySearchAndReplaceInterceptor

agent1.sources.r1.interceptors.i1.searchReplace = "gift_record:giftRecord,video_info:videoInfo,user_info:userInfo"

# 设置拦截器类型

agent1.sources.r1.interceptors.i2.type = regex_extractor

# 设置正则表达式，匹配指定的数据，这样设置会在数据的header中增加log_type="某个值"

agent1.sources.r1.interceptors.i2.regex = "type":"(\\w+)"

agent1.sources.r1.interceptors.i2.serializers = s1

agent1.sources.r1.interceptors.i2.serializers.s1.name = log_type

　　意思就是，即把gift_record 换成giftRecord

　　　　　　　　　video_info转换成videoInfo

　　　　　　　　　user_info转换成userInfo

　　然后，启动agent服务即可。

[hadoop@master flume-1.7.]$ bin/flume-ng agent --conf conf_MySearchAndReplaceInterceptor/  --conf-file conf_MySearchAndReplaceInterceptor/flume-conf.properties --name agent1  -Dflume.root.logger=INFO,console

　　我这里，出现了这个错误

-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.start(MonitoredCounterGroup.java:)] Component type: SOURCE, name: fileSource started

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.HDFSDataStream.configure(HDFSDataStream.java:)] Serializer = TEXT, UseRawLocalFileSystem = false

-- ::, (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:)] Creating hdfs://master:9000/data/types/20170729//run.1501294672792.data.tmp

-- ::, (hdfs-hdfsSink-call-runner-) [WARN - org.apache.hadoop.util.NativeCodeLoader.<clinit>(NativeCodeLoader.java:)] Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

-- ::, (pool--thread-) [ERROR - org.apache.flume.source.ExecSource$ExecRunnable.run(ExecSource.java:)] Failed while running command: tail -F /usr/local/log/server.log

org.apache.flume.ChannelFullException: Space for commit to queue couldn't be acquired. Sinks are likely not keeping up with sources, or the buffer size is too tight

    at org.apache.flume.channel.MemoryChannel$MemoryTransaction.doCommit(MemoryChannel.java:)

    at org.apache.flume.channel.BasicTransactionSemantics.commit(BasicTransactionSemantics.java:)

    at org.apache.flume.channel.ChannelProcessor.processEventBatch(ChannelProcessor.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.flushEventBatch(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.run(ExecSource.java:)

    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:)

    at java.util.concurrent.FutureTask.run(FutureTask.java:)

    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:)

    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:)

    at java.lang.Thread.run(Thread.java:)

-- ::, (timedFlushExecService21-) [ERROR - org.apache.flume.source.ExecSource$ExecRunnable$.run(ExecSource.java:)] Exception occured when processing event batch

org.apache.flume.ChannelException: java.lang.InterruptedException

    at org.apache.flume.channel.BasicTransactionSemantics.commit(BasicTransactionSemantics.java:)

    at org.apache.flume.channel.ChannelProcessor.processEventBatch(ChannelProcessor.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.flushEventBatch(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable.access$(ExecSource.java:)

    at org.apache.flume.source.ExecSource$ExecRunnable$.run(ExecSource.java:)

    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:)

    at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:)

    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$(ScheduledThreadPoolExecutor.java:)

    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:)

　　见博客

Flume启动运行时报错org.apache.flume.ChannelFullException: Space for commit to queue couldn't be acquired. Sinks are likely not keeping up with sources, or the buffer size is too tight解决办法（图文详解）

　　中间，我这里还出现下面这个错误

Flume启动时报错Caused by: java.lang.InterruptedException: Timed out before HDFS call was made. Your hdfs.callTimeout might be set too low or HDFS calls are taking too long.解决办法（图文详解）

　　中间，我这里还出现下面这个错误

Flume启动报错[ERROR - org.apache.flume.sink.hdfs. Hit max consecutive under-replication rotations (30); will not continue rolling files under this path due to under-replication解决办法（图文详解）

[root@master log]# ll

total

-rwxr-xr-x  root root  Jul  : producerLog.sh

-rw-r--r--  root root     Jul  : server.log

[root@master log]# ./producerLog.sh

　　查看

对于目标文件的生成
我这里，貌似懂了
是要达到那么多的临时文件大小生成后
才会有一股目标目录出来
让它等吧

　　　还有资料说，

flume自定义拦截器实现多行读取日志

　　加了还是没用。

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