原文的地址：https://www.cnblogs.com/re-myself/p/5180249.html
了解过flume的人，差不多都看过这张或则类似的图片，本文即实现上图部分内容。（由于条件有限，目前是单机上实现）
flume-agent配置文件
#flume agent conf
source_agent.sources = server
source_agent.sinks = avroSink
source_agent.channels = memoryChannel
source_agent.sources.server.type = exec
source_agent.sources.server.command = tail -F /data/hudonglogs/self/channel.log
source_agent.sources.server.channels = memoryChannel
source_agent.channels.memoryChannel.type = memory
source_agent.channels.memoryChannel.capacity = 1000
source_agent.channels.memoryChannel.transactionCapacity = 100
source_agent.sinks = avroSink
source_agent.sinks.avroSink.type = avro
source_agent.sinks.avroSink.hostname = 127.0.0.1
source_agent.sinks.avroSink.port = 41414
source_agent.sinks.avroSink.channel = memoryChannel
flume-hbase 配置文件
#hbase flume conf sinks
collector.sources = avroSource
collector.sinks = hbaseSink
collector.channels =memChannel
collector.sources.avroSource.type = avro
collector.sources.avroSource.bind = 127.0.0.1
collector.sources.avroSource.port = 41414
collector.sources.avroSource.channels = memChannel
collector.channels.memChannel.type = memory
collector.channels.memChannel.capacity = 1000
collector.sinks.hbaseSink.type = asynchbase
collector.sinks.hbaseSink.channel = memChannel
collector.sinks.hbaseSink.table = logs
collector.sinks.hbaseSink.columnFamily = content
collector.sinks.hbaseSink.batchSize = 5hbase中创建表logs 以及列族content
create 'logs','content'启动flume
bin/flume-ng agent -c conf/ -f conf/flume-hbase.conf -n collector -Dflume.root.logger=INFO,console
bin/flume-ng agent -c conf/ -f conf/flume-agent.conf -n source_agent -Dflume.root.logger=INFO,console注：这两条命令启动是有顺序的，先启动collector，否则会报错
在不断向文件中写入日志后，可以使用scan命令查看hbase
scan 'logs'
ROW COLUMN+CELL
default09626ade-3f37-49c3-a930-270ef7119dd3 column=content:pCol, timestamp=1454480049481, value=2016-02-03 12:19:36,260 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default09ba09cc-326c-465c-90f9-533c923923a0 column=content:pCol, timestamp=1454480074182, value=2016-02-03 14:14:22,179 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default0c199142-05f8-49c6-b341-8158bb445861 column=content:pCol, timestamp=1454480113199, value=2016-02-03 14:15:07,196 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default0cbb050e-3756-44f2-8c66-419a6e52fd97 column=content:pCol, timestamp=1454480049493, value=2016-02-03 12:19:42,263 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default0f8eb841-7ccd-4abf-9dcf-4fc26d3f55f4 column=content:pCol, timestamp=1454480079188, value=2016-02-03 14:14:34,185 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default133b7acf-ca3c-46e9-90a8-27d553721900 column=content:pCol, timestamp=1454480121214, value=2016-02-03 14:15:18,200 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default13e2a5bc-f79a-4ffe-86a0-bf0ea37d8f35 column=content:pCol, timestamp=1454480139209, value=2016-02-03 14:15:35,206 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default19cae7ca-87ba-42b5-9f13-136c89c0c20e column=content:pCol, timestamp=1454480094196, value=2016-02-03 14:14:50,190 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default1aba06a5-973d-403a-91de-afacc9536172 column=content:pCol, timestamp=1454480139209, value=2016-02-03 14:15:34,206 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default1b240a9c-2b35-4649-b199-29a27a0c4db2 column=content:pCol, timestamp=1454480049481, value=2016-02-03 12:19:40,262 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default1d92a0e3-b427-4958-bae7-c7bb1e9d20ef column=content:pCol, timestamp=1454480106197, value=2016-02-03 14:14:59,193 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145
default25ef2b1b-6d6c-4431-885e-c2e4d2297f59 column=content:pCol, timestamp=1454480085201, value=2016-02-03 14:14:42,187 com.hudong.test.Test01 [main] [INFO]-(Test01.java:22) 145另：
对于现在的日志格式可能不满意，flume支持自定义Serializer，用于日志的清洗，实现AsyncHbaseEventSerializer接口即可，并将flume重新打包，然后将相应的jar复制到flume home目录下lib文件夹下，旧可以！
接口的实现，参照博文：http://blog.csdn.net/yaoyasong/article/details/39400829