Flume:单数据源多输出 之 选择器实现

需求

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使用Flume-1监控文件Hive日志,Flume-1将变动内容传递给Flume-2,Flume-2负责存储到HDFS。同时Flume-1将变动内容传递给Flume-3,Flume-3负责输出到Local FileSystem。

实现

第一步:在flume目录下创建文件夹job,然后在其下面创建配置文件:

  • flume-file-flume.conf

    # Name the components on this agent
    a1.sources = r1
    a1.sinks = k1 k2
    a1.channels = c1 c2
    # 将数据流复制给所有channel
    a1.sources.r1.selector.type = replicating
    
    # Describe/configure the source
    a1.sources.r1.type = exec
    a1.sources.r1.command = tail -F /usr/local/apache-hive-3.1.1/logs/hive.log
    a1.sources.r1.shell = /bin/bash -c
    
    # Describe the sink
    a1.sinks.k1.type = avro
    a1.sinks.k1.hostname = hcmaster 
    a1.sinks.k1.port = 4141
    
    a1.sinks.k2.type = avro
    a1.sinks.k2.hostname = hcmaster
    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-flume-dir.conf

    # Name the components on this agent
    a3.sources = r1
    a3.sinks = k1
    a3.channels = c2
    
    # Describe/configure the source
    a3.sources.r1.type = avro
    a3.sources.r1.bind = hcmaster
    a3.sources.r1.port = 4142
    
    # Describe the sink
    a3.sinks.k1.type = file_roll
    a3.sinks.k1.sink.directory = /usr/local/test
    
    # Describe the channel
    a3.channels.c2.type = memory
    a3.channels.c2.capacity = 1000
    a3.channels.c2.transactionCapacity = 100
    
    # Bind the source and sink to the channel
    a3.sources.r1.channels = c2
    a3.sinks.k1.channel = c2
    
  • flume-flume-hdfs.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 = hcmaster
    a2.sources.r1.port = 4141
    
    # Describe the sink
    a2.sinks.k1.type = hdfs
    a2.sinks.k1.hdfs.path = hdfs://hcmaster:8020/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
    

第二步:启动flume
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第三步:启动hive
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在hive shell中做一些简单操作

第四步:查看结果:
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转载自blog.csdn.net/lianghecai52171314/article/details/104896843