{大数据}辅助系统

然后进入flume的目录，修改conf下的flume-env.sh，在里面配置JAVA_HOME

export JAVA_HOME=/opt/jdk1.8.0_121

2、根据数据采集的需求配置采集方案，描述在配置文件中(文件名可任意自定义)

3、指定采集方案配置文件，在相应的节点上启动flume agent

先用一个最简单的例子来测试一下程序环境是否正常

1、先在flume的conf目录下新建一个文件

vi   netcat-logger.conf

# 定义这个agent中各组件的名字

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# 描述和配置source组件：r1

a1.sources.r1.type = netcat

a1.sources.r1.bind = localhost

a1.sources.r1.port = 44444

# 描述和配置sink组件：k1

a1.sinks.k1.type = logger

# 描述和配置channel组件，此处使用是内存缓存的方式

a1.channels.c1.type = memory

a1.channels.c1.capacity = 1000

a1.channels.c1.transactionCapacity = 100

# 描述和配置source  channel   sink之间的连接关系

a1.sources.r1.channels = c1

a1.sinks.k1.channel = c1

​bin/flume-ng agent -c conf -f conf/netcat-logger.conf -n a1  -Dflume.root.logger=INFO,console

​

c conf   指定flume自身的配置文件所在目录

-f conf/netcat-logger.con  指定我们所描述的采集方案

-n a1  指定我们这个agent的名字

1、测试

先要往agent采集监听的端口上发送数据，让agent有数据可采

随便在一个能跟agent节点联网的机器上

telnet anget-hostname  port   （telnet localhost 44444）

如果telnet命令找不到，则用以下方式安装

[root@hdp08 ~]# yum install telnet

1.2.2 采集案例

1、采集指定目录下的日志文件

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

#监听目录,spoolDir指定目录, fileHeader要不要给文件夹前坠名

a1.sources.r1.type = spooldir

a1.sources.r1.spoolDir = /home/hadoop/flumespool

a1.sources.r1.fileHeader = true

# Describe the sink

a1.sinks.k1.type = logger

# Use a channel which buffers events in memory

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

启动命令：  

bin/flume-ng agent -c ./conf -f ./conf/spool-logger.conf -n a1 -Dflume.root.logger=INFO,console

2、采集目录到HDFS采集需求：某服务器的某特定目录下，会不断产生新的文件，每当有新文件出现，就需要把文件采集到HDFS中去

根据需求，首先定义以下3大要素

l 采集源，即source——监控文件目录 :  spooldir

l 下沉目标，即sink——HDFS文件系统  :  hdfs sink

l source和sink之间的传递通道——channel，可用file channel 也可以用内存channel

配置文件编写：

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

#监听目录,spoolDir指定目录, fileHeader要不要给文件夹前坠名

a1.sources.r1.type = spooldir

a1.sources.r1.spoolDir = /home/hadoop/flumespool

a1.sources.r1.fileHeader = true

# Describe the sink

a1.sinks.k1.type = hdfs

a1.sinks.k1.hdfs.path = /flume/events/%y-%m-%d/%H%M/

a1.sinks.k1.hdfs.filePrefix = events-

a1.sinks.k1.hdfs.round = true

a1.sinks.k1.hdfs.roundValue = 10

a1.sinks.k1.hdfs.roundUnit = minute

a1.sinks.k1.hdfs.rollInterval = 3

a1.sinks.k1.hdfs.rollSize = 20

a1.sinks.k1.hdfs.rollCount = 5

a1.sinks.k1.hdfs.batchSize = 1

a1.sinks.k1.hdfs.useLocalTimeStamp = true

#生成的文件类型，默认是Sequencefile，可用DataStream，则为普通文本

a1.sinks.k1.hdfs.fileType = DataStream

# Use a channel which buffers events in memory

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

Channel参数解释：

capacity：默认该通道中较大的可以存储的event数量

trasactionCapacity：每次较大可以从source中拿到或者送到sink中的event数量

keep-alive：event添加到通道中或者移出的允许时间

3、采集文件到HDFS采集需求：比如业务系统使用log4j生成的日志，日志内容不断增加，需要把追加到日志文件中的数据实时采集到hdfs

根据需求，首先定义以下3大要素

l 采集源，即source——监控文件内容更新 :  exec  ‘tail -F file’

l 下沉目标，即sink——HDFS文件系统  :  hdfs sink

l Source和sink之间的传递通道——channel，可用file channel 也可以用 内存channel

配置文件编写：

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

a1.sources.r1.type = exec

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

a1.sources.r1.channels = c1

# Describe the sink

a1.sinks.k1.type = hdfs

a1.sinks.k1.channel = c1

a1.sinks.k1.hdfs.path = /flume/events/%y-%m-%d/%H%M/

a1.sinks.k1.hdfs.filePrefix = events-

a1.sinks.k1.hdfs.round = true

a1.sinks.k1.hdfs.roundValue = 10

a1.sinks.k1.hdfs.roundUnit = minute

a1.sinks.k1.hdfs.rollInterval = 3

a1.sinks.k1.hdfs.rollSize = 20

a1.sinks.k1.hdfs.rollCount = 5

a1.sinks.k1.hdfs.batchSize = 1

a1.sinks.k1.hdfs.useLocalTimeStamp = true

#生成的文件类型，默认是Sequencefile，可用DataStream，则为普通文本

a1.sinks.k1.hdfs.fileType = DataStream

# Use a channel which buffers events in memory

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

启动命令：

bin/flume-ng agent -c conf -f conf/tail-hdfs.conf -n a1 -Dflume.root.logger=INFO,console

4、采集文件发到另一个agent

​

从tail命令获取数据发送到avro端口

另一个节点可配置一个avro源来中继数据，发送外部存储

##################

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

a1.sources.r1.type = spooldir

a1.sources.r1.spoolDir = /home/hadoop/flumespool

a1.sources.r1.fileHeader = true

# Describe the sink

a1.sinks = k1

a1.sinks.k1.type = avro

a1.sinks.k1.channel = c1

a1.sinks.k1.hostname = hdp09

a1.sinks.k1.port = 4141

a1.sinks.k1.batch-size = 2

# Use a channel which buffers events in memory

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

从avro端口接收数据，下沉到logger

采集配置文件，avro-hdfs.conf

# Name the components on this agent

a1.sources = r1

a1.sinks = k1

a1.channels = c1

# Describe/configure the source

a1.sources.r1.type = avro

a1.sources.r1.channels = c1

a1.sources.r1.bind = 0.0.0.0

a1.sources.r1.port = 4141

# Describe the sink

a1.sinks.k1.type = logger

# Use a channel which buffers events in memory

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

发送数据：

$ bin/flume-ng avro-client -H localhost -p 4141 -F /usr/logs/log.10

1.3 更多source和sink组件

​

Flume支持众多的source和sink类型，详细手册可参考官方文档

http://flume.apache.org/FlumeUserGuide.html​