Spark Streaming——Flume实例

 

Flume 官网http://flume.apache.org/releases/content/1.9.0/FlumeUserGuide.html

此文章共有三个实例:

crtl+c后停止flume

实例一直接监控端口

配置文件

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

a1.sources.r1.type = netcat

a1.sources.r1.bind = dblab-VirtualBox

a1.sources.r1.port = 44444

 

# Describe the sink

a1.sinks.k1.type = logger

 

# Use a channel which buffers events in memory

a1.channels.c1.type = memory

 

# Bind the source and sink to the channel

a1.sources.r1.channels = c1

a1.sinks.k1.channel = c1

 

 

启动agent:

flume-ng agent \

-n a1 \

-c $FLUME_HOME/conf \

-f $FLUME_HOME/conf/example.conf \

-Dflume.root.logger=INFO,console

 

实例二监控文件

配置文件

a1.sources = r1

a1.sinks = k1

a1.channels = c1

 

a1.sources.r1.type = exec

a1.sources.r1.command = tail -F /home/hadoop/data/data.log

a1.sources.r1.shell = /bin/sh -c

 

a1.sinks.k1.type = logger

 

a1.channels.c1.type = memory

 

a1.sources.r1.channels = c1

a1.sinks.k1.channel = c1

 

启动agent:

flume-ng agent \

-n a1 \

-c $FLUME_HOME/conf \

-f $FLUME_HOME/conf/exec-memory-logger.conf \

-Dflume.root.logger=INFO,console

 

 

目前是sink到控制台a1.sinks.k1.type = logger 如果是离线处理的话可以sink到HDFS

书写格式

 

实例三Flume实战

机器配置图

技术选型:

      A:  exec source +memory channel +avro sink

      B:  avro source +memory channel +logger sink

 

配置文件

exec-memory-avro.conf

exec-memory-avro.sources = exec-source

exec-memory-avro.sinks = avro-sink

exec-memory-avro.channels = memory-channel

 

exec-memory-avro.sources.exec-source.type = exec

exec-memory-avro.sources.exec-source.command = tail -F /home/hadoop/data/data.log

exec-memory-avro.sources.exec-source.shell = /bin/sh -c

 

exec-memory-avro.sinks.avro-sink.type = avro

exec-memory-avro.sinks.avro-sink.hostname = dblab-VirtualBox

exec-memory-avro.sinks.avro-sink.port = 44444

 

exec-memory-avro.channels.memory-channel.type = memory

 

exec-memory-avro.sources.exec-source.channels = memory-channel

exec-memory-avro.sinks.avro-sink.channel = memory-channel

 

avro-memory-logger.conf

avro-memory-logger.sources = avro-source

avro-memory-logger.sinks = logger-sink

avro-memory-logger.channels = memory-channel

 

avro-memory-logger.sources.avro-source.type = avro

avro-memory-logger.sources.avro-source.bind= dblab-VirtualBox

avro-memory-logger.sources.avro-source.port=44444

 

avro-memory-logger.sinks.logger-sink.type = logger

 

avro-memory-logger.channels.memory-channel.type = memory

 

avro-memory-logger.sources.avro-source.channels = memory-channel

avro-memory-logger.sinks.logger-sink.channel = memory-channel

 

启动agent:

先启动avro-memory-logger.conf  wang-one启动

flume-ng agent --name avro-memory-logger \

--conf $FLUME_HOME/conf \

--conf-file $FLUME_HOME/conf/avro-memory-logger.conf -Dflume.root.logger=INFO,console

再启动exec-memory-avro.conf  wang-two启动

flume-ng agent --name exec-memory-avro \

--conf $FLUME_HOME/conf \

--conf-file $FLUME_HOME/conf/exec-memory-avro.conf \

-Dflume.root.logger=INFO,console

exec-memory-avro.conf

avro-memory-logger.conf

posted @ 2019-01-26 10:40 夏延 阅读(...) 评论(...) 编辑 收藏