Flume基本操作 #flume#

一、监听端口将结果输出到console

  1. 编写配置文件job_flume_netcat.conf
# 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 = localhost
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
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
  1. 启动flume进程
flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a1 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/job_flume_netcat.conf -Dflume.root.logger==INFO,console
  1. 查看指定端口是否被flume监听
sudo netstat -tunlp | grep 44444
  1. 用telnet发送数据
telnet localhost 44444


二、动态读取日志文件并写入到hdfs

  1. 编写配置文件job_flume_2hdfs.conf
# Name the components on this agent 
a2.sources = r2
a2.sinks = k2
a2.channels = c2
# Describe/configure the source
a2.sources.r2.type = exec
a2.sources.r2.command = tail -F /home/hadoop/app/hive-1.2.2/logs/hive.log
a2.sources.r2.shell = /bin/bash -c

# Describe the sink
a2.sinks.k2.type = hdfs
a2.sinks.k2.hdfs.path = hdfs://hadoop01:9000/flume/hive-logs/%Y%m%d/%H

#上传文件的前缀
a2.sinks.k2.hdfs.filePrefix = logs-

#是否按照时间滚动文件夹
a2.sinks.k2.hdfs.round = true

#多少时间单位创建一个新的文件夹
a2.sinks.k2.hdfs.roundValue = 1

#重新定义时间单位 
a2.sinks.k2.hdfs.roundUnit = hour

#是否使用本地时间戳 
a2.sinks.k2.hdfs.useLocalTimeStamp = true

#积攒多少个Event才flush到HDFS 一次
a2.sinks.k2.hdfs.batchSize = 1000

#设置文件类型，可支持压缩
a2.sinks.k2.hdfs.fileType = DataStream

#多久生成一个新的文件
a2.sinks.k2.hdfs.rollInterval = 600

#设置每个文件的滚动大小 
a2.sinks.k2.hdfs.rollSize = 134217700

#文件的滚动与Event数量无关 
a2.sinks.k2.hdfs.rollCount = 0

#最小冗余数
a2.sinks.k2.hdfs.minBlockReplicas = 1

# Use a channel which buffers events in memory 
a2.channels.c2.type = memory
a2.channels.c2.capacity = 1000
a2.channels.c2.transactionCapacity = 100

# Bind the source and sink to the channel 
a2.sources.r2.channels = c2 
a2.sinks.k2.channel = c2
  1. 启动flume进程
flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a2 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/job_flume_2hdfs.conf


三、实时读取目录文件到HDFS

  1. 编写配置文件flume-dir.conf
a3.sources = r3
a3.sinks = k3
a3.channels = c3

# Describe/configure the source
a3.sources.r3.type = spooldir
a3.sources.r3.spoolDir = /home/hadoop/app/apache-flume-1.7.0/upload
a3.sources.r3.fileSuffix = .COMPLETED
a3.sources.r3.fileHeader = true

#忽略所有以.tmp 结尾的文件，不上传
a3.sources.r3.ignorePattern = ([^ ]*\.tmp)

# Describe the sink
a3.sinks.k3.type = hdfs
a3.sinks.k3.hdfs.path = hdfs://hadoop01:9000/flume/upload/%Y%m%d/%H

#上传文件的前缀
a3.sinks.k3.hdfs.filePrefix = upload-

#是否按照时间滚动文件夹
a3.sinks.k3.hdfs.round = true

#多少时间单位创建一个新的文件夹
a3.sinks.k3.hdfs.roundValue = 1

#重新定义时间单位
a3.sinks.k3.hdfs.roundUnit = hour

#是否使用本地时间戳 
a3.sinks.k3.hdfs.useLocalTimeStamp = true

#积攒多少个Event才flush到HDFS一次
a3.sinks.k3.hdfs.batchSize = 100

#设置文件类型，可支持压缩
a3.sinks.k3.hdfs.fileType = DataStream

#多久生成一个新的文件
a3.sinks.k3.hdfs.rollInterval = 600

#设置每个文件的滚动大小大概是128M
a3.sinks.k3.hdfs.rollSize = 134217700

#文件的滚动与Event数量无关
a3.sinks.k3.hdfs.rollCount = 0

#最小冗余数
a3.sinks.k3.hdfs.minBlockReplicas = 1

# Use a channel which buffers events in memory 
a3.channels.c3.type = memory
a3.channels.c3.capacity = 1000
a3.channels.c3.transactionCapacity = 100

# Bind the source and sink to the channel
a3.sources.r3.channels = c3
a3.sinks.k3.channel = c3
  1. 启动flume进程
flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a3 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-dir.conf


四、Flume与Flume之间数据传递:单Flume多Channel、 Sink

  1. 编写配置文件

    • flume-1.conf
    # Name the components on this agent
a1.sources = r1
a1.sinks = k1 k2
a1.channels = c1 c2

# 将数据流复制给多个 channel 
a1.sources.r1.selector.type = replicating

# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /home/hadoop/app/hive-1.2.2/logs/hive.log
a1.sources.r1.shell = /bin/bash -c

# Describe the sink 
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop01
a1.sinks.k1.port = 4141
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = hadoop01
a1.sinks.k2.port = 4142

# Describe the channel 
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

a1.channels.c2.type = memory
a1.channels.c2.capacity = 1000
a1.channels.c2.transactionCapacity = 100

# Bind the source and sink to the channel
a1.sources.r1.channels = c1 c2
a1.sinks.k1.channel = c1
a1.sinks.k2.channel = c2
    • flume-2.conf
    # Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1

# Describe/configure the source
a2.sources.r1.type = avro
a2.sources.r1.bind = hadoop01
a2.sources.r1.port = 4141

# Describe the sink
a2.sinks.k1.type = hdfs
a2.sinks.k1.hdfs.path = hdfs://hadoop01:9000/flume2/%Y%m%d/%H
#上传文件的前缀
a2.sinks.k1.hdfs.filePrefix = flume2-

#是否按照时间滚动文件夹
a2.sinks.k1.hdfs.round = true

#多少时间单位创建一个新的文件夹
a2.sinks.k1.hdfs.roundValue = 1

#重新定义时间单位
a2.sinks.k1.hdfs.roundUnit = hour

#是否使用本地时间戳
a2.sinks.k1.hdfs.useLocalTimeStamp = true

#积攒多少个Event才flush到HDFS 一次
a2.sinks.k1.hdfs.batchSize = 100

#设置文件类型，可支持压缩
a2.sinks.k1.hdfs.fileType = DataStream

#多久生成一个新的文件
a2.sinks.k1.hdfs.rollInterval = 600

#设置每个文件的滚动大小大概是128M
a2.sinks.k1.hdfs.rollSize = 134217700

#文件的滚动与Event数量无关
a2.sinks.k1.hdfs.rollCount = 0

#最小冗余数 
a2.sinks.k1.hdfs.minBlockReplicas = 1

# Describe the channel
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1
    • flume-3.conf
    # Name the components on this agent
a3.sources = r1
a3.sinks = k1
a3.channels = c1

# Describe/configure the source 
a3.sources.r1.type = avro
a3.sources.r1.bind = hadoop01
a3.sources.r1.port = 4142

# Describe the sink 文件夹必须存在
a3.sinks.k1.type = file_roll
a3.sinks.k1.sink.directory = /home/hadoop/flume2

# Describe the channel 
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a3.sources.r1.channels = c1
a3.sinks.k1.channel = c1

  2. 启动flume进程

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a1 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-1.conf

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a2 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-2.conf

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a3 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-3.conf


五、Flume与Flume之间数据传递，多Flume汇总数据到单Flume

  1. 编写配置文件

    • flume-a.conf
    # 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/app/hive-1.2.2/logs/hive.log
a1.sources.r1.shell = /bin/bash -c

# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop01
a1.sinks.k1.port = 4141

# Describe the channel
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
    • flume-b.conf
    # Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1

# Describe/configure the source
a2.sources.r1.type = netcat
a2.sources.r1.bind = hadoop01
a2.sources.r1.port = 44444

# Describe the sink
a2.sinks.k1.type = avro
a2.sinks.k1.hostname = hadoop01
a2.sinks.k1.port = 4141

# Use a channel which buffers events in memory
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1
    • flume-c.conf
    # Name the components on this agent 
a3.sources = r1
a3.sinks = k1
a3.channels = c1

# Describe/configure the source
a3.sources.r1.type = avro
a3.sources.r1.bind = hadoop01
a3.sources.r1.port = 4141

# Describe the sink
a3.sinks.k1.type = hdfs
a3.sinks.k1.hdfs.path = hdfs://hadoop01:9000/flume3/%Y%m%d/%H

#上传文件的前缀
a3.sinks.k1.hdfs.filePrefix = flume3-

#是否按照时间滚动文件夹
a3.sinks.k1.hdfs.round = true

#多少时间单位创建一个新的文件夹
a3.sinks.k1.hdfs.roundValue = 1

#重新定义时间单位
a3.sinks.k1.hdfs.roundUnit = hour

#是否使用本地时间戳
a3.sinks.k1.hdfs.useLocalTimeStamp = true

#积攒多少个 Event 才 flush 到 HDFS 一次
a3.sinks.k1.hdfs.batchSize = 100

#设置文件类型，可支持压缩
a3.sinks.k1.hdfs.fileType = DataStream

#多久生成一个新的文件
a3.sinks.k1.hdfs.rollInterval = 600

#设置每个文件的滚动大小大概是 128M
a3.sinks.k1.hdfs.rollSize = 134217700

#文件的滚动与 Event 数量无关
a3.sinks.k1.hdfs.rollCount = 0

#最小冗余数
a3.sinks.k1.hdfs.minBlockReplicas = 1

# Describe the channel
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a3.sources.r1.channels = c1
a3.sinks.k1.channel = c1

  2. 启动flume进程

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a1 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-a.conf

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a2 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-b.conf

flume-ng agent --conf /home/hadoop/app/apache-flume-1.7.0/conf/ --name a3 --conf-file /home/hadoop/app/apache-flume-1.7.0/job/flume-c.conf
  1. 用telnet发送数据
telnet localhost 44444
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