Flume案例-Avro&Exec&Exec&Syslogtcp&JSONHandler&HDFS sink&File Roll Sink&channels

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flume案例-Avro、Exec、Exec、Syslogtcp、JSONHandler、HDFS sink、File Roll Sink、channels

1、Avro

Avro可以发送一个给定的文件给Flume，Avro 源使用AVRO RPC机制。

• 创建agent配置文件
  在flume_home/conf目录下创建一个名为avro.conf的文件，内容如下

  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe configure the source
  a1.sources.r1.type = avro
  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
  

  对以上内容解释：

  指定名称：a1是我们要启动的Agent名字
  类似别名：Select u.id ,u.name from user as u where u.id =1;
  a1.sources = r1		命名Agent的sources为r1
  a1.sinks = k1		命名Agent的sinks为k1
  a1.channels = c1		命名Agent的channels 为c1
  
  # Describe configure the source
  a1.sources.r1.type = avro		指定r1的类型为AVRO
  a1.sources.r1.bind = 0.0.0.0 	将Source与IP地址绑定（这里指本机）
  a1.sources.r1.port = 4141	指定通讯端口为4141
  
  # Describe the sink
  a1.sinks.k1.type = logger	指定k1的类型为Logger（不产生实体文件，只在控制台显示）
  
  # Use a channel which buffers events in memory
  a1.channels.c1.type = memory		指定Channel的类型为Memory	
  a1.channels.c1.capacity = 1000	设置Channel的最大存储event数量为1000	
  a1.channels.c1.transactionCapacity = 100		每次最大可以source中拿到或者送到sink中的event数量也是100
  
  这里还可以设置Channel的其他属性：
  a1.channels.c1.keep-alive=1000	event添加到通道中或者移出的允许时间（秒）
  a1.channels.c1.byteCapacity = 800000	event的字节量的限制，只包括eventbody
  a1.channels.c1.byteCapacityBufferPercentage = 20
  event的缓存比例为20%（800000的20%），即event的最大字节量为800000*120%
  
  # Bind the source and sink to the channel
  a1.sources.r1.channels = c1
  a1.sinks.k1.channel = c1
  将source、sink分别与Channel c1绑定
  

• 启动flume agent a1

  flume-ng agent -c flume_home/conf -f  flume_home/conf/avro.conf -n a1 -Dflume.root.logger=INFO,console
  
  # -c：使用配置文件所在目录（这里指默认路径，即$FLUME_HOME/conf）
  # -f：flume定义组件的配置文件 
  # -n：启动Agent的名称，该名称在组件配置文件中定义 
  # -Dflume.root.logger：flume自身运行状态的日志，按需配置，详细信息，控制台打印
  

​

• 创建指定文件

   echo "hello world" > /home/data/log.00
  ``` ​
  
  

• 使用avro-client发送文件

   flume-ng avro-client -c flume_home/conf -H min1 -p 4141 -F /home/data/log.00
   
  #	-H：指定主机
  #	-p：指定端口
  #	-F：制定要发送的文件
  

  ​

• 在min1的控制台，可以看到以下信息，注意最后一行：

  

2 Exec

• 创建agent配置文件

  vi /home/bigdata/flume/conf/exec_tail.conf
  
  #添加以下内容：
  
  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/data/log_exec_tail
  
  # 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flume agent a1

   flume-ng agent -c flume_home/conf -f /home/bigdata/flume/conf/exec_tail.conf -n a1 -Dflume.root.logger=INFO,console
  

• 制作log_exec_tail文件

   echo "exec tail 1" >> /home/data/log_exec_tail
   
   #在flume的控制台，可以看到以下信息：
  

  

• 向log_exec_tail文件中追加数据

  echo "exec tail 2" >> /hadoop/flume/log_exec_tail
  
  #在flume的控制台，可以看到以下信息：
  

  

• 在shell中编写一个shell程序

  # for i in {1..100}
  > do echo "flume +" $i >> /home/data/log_exec_tail 
  > done
  
  for i in $(seq 1 100) ;do echo "flume"+$i >> /home/data/log_exec_tail ; done
  

##3 Spool

• Spool监测配置的目录下新增的文件，并将文件中的数据读取出来。需要注意两点：

  • 拷贝到spool目录下的文件不可以再打开编辑。
  • spool目录下不可包含相应的子目录
  • 此方式的缺点：指定文件下不能有重名(如：kk.log 和 kk.log. COMPLETED),会报错 使得flume死掉

• 创建agent配置文件

  vi /home/bigdata/flume/conf/spool.conf
  
  #添加以下内容：
  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe configure the source
  a1.sources.r1.type = spooldir
  a1.sources.r1.spoolDir = /home/data/logs
  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flume agent a1

  #创建/home/data/logs文件夹
  mkdir / home/data /logs
  flume-ng agent -c flume_home/conf -f flume_home/conf/spool.conf -n a1 -Dflume.root.logger=INFO,console
  

• 追加文件到/hadoop/flume/logs目录

   echo "spool test1" > /home/data/logs/spool_text.log
  

4 Syslogtcp

Syslogtcp监听TCP的端口做为数据源

• 创建agent配置文件

  vi /home/bigdata/flume/conf/syslog_tcp.conf
  
  #添加以下内容：
  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe/configure the source
  a1.sources.r1.type = syslogtcp
  a1.sources.r1.port = 5140
  a1.sources.r1.host = localhost
  
  # 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flume agent a1

  flume-ng agent -c flume_home/conf -f /home/bigdata/flume/conf/syslog_tcp.conf -n a1 -Dflume.root.logger=INFO,console
  

• 测试产生syslogy

  #需要安装nc
  Rpm –ivh nc-1.84-22.el6.x86_64
  
  echo "hello idoall.org syslog" | nc localhost 5140
  

5 JSONHandler

• 创建agent配置文件

  vi /home/bigdata/flume/conf/post_json.conf
  
  #添加如下内容：
  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe/configure the source
  a1.sources.r1.type = org.apache.flume.source.http.HTTPSource
  a1.sources.r1.port = 8888
  
  # 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flume agent a1

  flume-ng agent -c flume_home/conf -f /home/bigdata/flume/conf/post_json.conf -n a1 -Dflume.root.logger=INFO,console
  

• 生成JSON 格式的POST request

  curl -X POST -d '[{ "headers" :{"a" : "a1","b" : "b1"},"body" : "idoall.org_body"}]' http://localhost:8888
  

​

6 HDFS sink

• 创建agent配置文件

  vi /home/bigdata/flume/conf/hdfs_sink.conf
  
  #添加以下内容：
  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe/configure the source
  a1.sources.r1.type = syslogtcp
  a1.sources.r1.port = 5140
  a1.sources.r1.host = localhost
  
  # Describe the sink
  a1.sinks.k1.type = hdfs
  a1.sinks.k1.hdfs.path = hdfs:// zookeepertest01:8020/user/flume/syslogtcp
  a1.sinks.k1.hdfs.filePrefix = Syslog
  a1.sinks.k1.hdfs.round = true
  a1.sinks.k1.hdfs.roundValue = 1
  a1.sinks.k1.hdfs.roundUnit = minute
  a1.sinks.k1.hdfs.fileType=DataStream
  a1.sinks.k1.hdfs.writeFormat=Text
  a1.sinks.k1.hdfs.rollInterval=0
  a1.sinks.k1.hdfs.rollSize=10240
  a1.sinks.k1.hdfs.rollCount=0
  a1.sinks.k1.hdfs.idleTimeout=60
  
  # 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flume agent a1

  flume-ng agent -c flume_home/conf -f /home/bigdata/flume/conf/hdfs_sink.conf -n a1 -Dflume.root.logger=INFO,console
  

• 测试产生syslog

  echo "hello idoall flume -> hadoop testing one" | nc localhost 5140
  

• 在master上再打开一个窗口，去Hadoop上检查文件是否生成

  hadoop fs -ls /user/flume/syslogtcp
  
  hadoop fs -cat /user/flume/syslogtcp/Syslog.1407644509504
  
  for i in {1..30}; do echo “Flume  +”$i |nc localhost 5140;done
  

​

7 hdfs sink 按照日期创建

• 创建agent配置文件

  vi conf/hdfsDate.conf
  
  #定义agent名， source、channel、sink的名称
  a5.sources = source1
  a5.channels = channel1
  a5.sinks = sink1
  
  #配置source
  a5.sources.source1.type = spooldir
  a5.sources.source1.spoolDir = /home/data/beicai
  a5.sources.source1.channels = channel1
  a5.sources.source1.fileHeader = false
  a5.sources.source1.interceptors = i1
  a5.sources.source1.interceptors.i1.type = timestamp
  
  #配置sink
  a5.sinks.sink1.type = hdfs
  a5.sinks.sink1.hdfs.path = hdfs://192.168.10.11:9000/usr/beicai
  a5.sinks.sink1.hdfs.fileType = DataStream
  a5.sinks.sink1.hdfs.writeFormat = TEXT
  a5.sinks.sink1.hdfs.rollInterval = 1
  a5.sinks.sink1.channel = channel1
  a5.sinks.sink1.hdfs.filePrefix = %Y-%m-%d
  
  #配置channel
  a5.channels.channel1.type = memory
  

• 启动flume agent a1

  flume-ng agent -n a5 -c flume_home/conf -f conf/hdfsDate.conf -Dflume.root.logger=DEBUG,console
  

  ​

8 File Roll Sink

• 创建agent配置文件

  vi /home/bigdata/flume/conf/file_roll.conf
  
  #添加以下内容：
  a1.sources = r1
  a1.sinks = k1
  a1.channels = c1
  
  # Describe/configure the source
  a1.sources.r1.type = syslogtcp
  a1.sources.r1.port = 5555
  a1.sources.r1.host = localhost
  
  # Describe the sink
  a1.sinks.k1.type = file_roll
  a1.sinks.k1.sink.directory = /home/data/logs2
  a1.sinks.k1.sink.serializer = TEXT
  
  # 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flume agent a1

  flume-ng agent -c flume_home/conf -f /home/bigdata/flume/conf/file_roll.conf -n a1 -Dflume.root.logger=INFO,console
  

• 测试产生logcat

   echo "hello idoall.org syslog" | nc localhost 5555
   echo "hello idoall.org syslog 2" | nc localhost 5555
  

• 查看/home/data/logs2下是否生成文件,默认每30秒生成一个新文件

  ll /home/data/logs2
  

​

9 channels通道类型为文件形式

• channelsFile

  vi  conf/channelsFile.conf
  a1.sources = s1
  a1.channels = c1
  a1.sinks = k1
  
  # For each one of the sources, the type is defined
  a1.sources.s1.type = syslogtcp
  a1.sources.s1.host = localhost
  a1.sources.s1.port = 5180
  
  # Each sink's type must be defined
  a1.sinks.k1.type = logger
  
  # Each channel's type is defined.
  a1.channels.c1.type = file
  a1.channels.c1.checkpointDir = /home/bigdata/flume/logs/checkpoint
  a1.channels.c1.dataDir = /home/bigdata/flume/logs/data
  
  #Bind the source and sinks to channels
  a1.sources.s1.channels = c1
  a1.sinks.k1.channel = c1
  
  #flume-ng agent -n a1 -c conf -f conf/ channelsFile.conf -Dflume.root.logger=DEBUG,console