Flume-复制和多路复用案例

梦里梦外; 2022-11-29 00:58 195阅读 0赞

### 文章目录 ###

*  复制和多路复用

# 复制和多路复用 #

**1）案例需求**

使用 Flume-1 监控文件变动，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 File System。

**2）需求分析：**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMyNzI3MDk1_size_16_color_FFFFFF_t_70_pic_center]  
**3）实现步骤：**

（1）准备工作

在/opt/module/flume/job目录下创建group1文件夹

[qinjl@hadoop102 job]$ cd group1/

在/opt/module/datas/目录下创建flume3文件夹

[qinjl@hadoop102 datas]$ mkdir flume3

（2）创建flume-file-flume.conf

*  配置1个接收日志文件的 source 和 两个channel、两个sink，分别输送给`flume-flume-hdfs` 和 `flume-flume-dir`。

[qinjl@hadoop102 group1]$ vim flume-file-flume.conf
    
    添加如下内容
    # Name the components on this agent
    a1.sources = r1
    a1.sinks = k1 k2
    a1.channels = c1 c2
    
    # Describe/configure the source
    # 将数据流复制给所有channel
    a1.sources.r1.selector.type = replicating
    a1.sources.r1.type = exec
    a1.sources.r1.command = tail -F /opt/module/hive/logs/hive.log
    a1.sources.r1.shell = /bin/bash -c
    
    # Describe the sink
    # sink端的avro是一个数据发送者
    a1.sinks.k1.type = avro
    a1.sinks.k1.hostname = hadoop102 
    a1.sinks.k1.port = 4141
    
    a1.sinks.k2.type = avro
    a1.sinks.k2.hostname = hadoop102
    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

（3）创建flume-flume-hdfs.conf

*  配置上级Flume输出的Source，输出是到HDFS的Sink。  
    编辑配置文件

[qinjl@hadoop102 group1]$ vim flume-flume-hdfs.conf
    
    添加如下内容
    # Name the components on this agent
    a2.sources = r1
    a2.sinks = k1
    a2.channels = c1
    
    # Describe/configure the source
    # source端的avro是一个数据接收服务
    a2.sources.r1.type = avro
    a2.sources.r1.bind = hadoop102
    a2.sources.r1.port = 4141
    
    # Describe the sink
    a2.sinks.k1.type = hdfs
    a2.sinks.k1.hdfs.path = /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，文本类型
    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
    #是否根据Event数量滚动文件（0：否）
    a2.sinks.k1.hdfs.rollCount = 0
    
    # 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

（4）创建flume-flume-dir.conf

*  配置上级Flume输出的Source，输出是到本地目录的Sink。  
    编辑配置文件

# 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 = hadoop102
    a3.sources.r1.port = 4142
    
    # Describe the sink
    a3.sinks.k1.type = file_roll
    a3.sinks.k1.sink.directory = /opt/module/datas/flume3
    
    # 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

提示：输出的本地目录必须是已经存在的目录，如果该目录不存在，并不会创建新的目录。

（5）执行配置文件

分别启动对应的flume进程：flume-flume-dir，flume-flume-hdfs，flume-file-flume。

[qinjl@hadoop102 flume]$ bin/flume-ng agent -c conf/ -n a3 -f job/group1/flume-flume-dir.conf
    
    [qinjl@hadoop102 flume]$ bin/flume-ng agent -c conf/ -n a2 -f job/group1/flume-flume-hdfs.conf
    
    [qinjl@hadoop102 flume]$ bin/flume-ng agent -c conf/ -n a1 -f job/group1/flume-file-flume.conf

（7）查看HDFS上数据  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMyNzI3MDk1_size_16_color_FFFFFF_t_70_pic_center 1]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMyNzI3MDk1_size_16_color_FFFFFF_t_70_pic_center]: /images/20221124/c5ec7e52016c4c88b5df63405a5ca784.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMyNzI3MDk1_size_16_color_FFFFFF_t_70_pic_center 1]: /images/20221124/baec077bbd2941c69425e44c7f589091.png