单数据源多出口案例(选择器)
单 Source 多 Channel、Sink 如图 7-2 所示。
图 7-2 单 Source 多 Channel、Sink
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 LocalFileSystem。
2）需求分析：
3）实现步骤：
0．准备工作
在/opt/module/flume/job 目录下创建 group1 文件夹
[atguigu@hadoop102 job]$ cd group1/
在/opt/module/datas/目录下创建 flume3 文件夹
[atguigu@hadoop102 datas]$ mkdir flume3
1．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。
创建配置文件并打开
[atguigu@hadoop102 group1]$ touch flume-file-flume.conf
[atguigu@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 # 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 /opt/module/hive/logs/hive.log a1.sources.r1.shell = /bin/bash -c # Describe the sink 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
注：Avro 是由 Hadoop 创始人 Doug Cutting 创建的一种语言无关的数据序列化和 RPC 框
架。
注：RPC（Remote Procedure Call）—远程过程调用，它是一种通过网络从远程计算机程
序上请求服务，而不需要了解底层网络技术的协议。
2．创建 flume-flume-hdfs.conf
配置上级 Flume 输出的 Source，输出是到 HDFS 的 Sink。
创建配置文件并打开
[atguigu@hadoop102 group1]$ touch flume-flume-hdfs.conf
[atguigu@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 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 = hdfs://hadoop102:9000/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
3．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。
创建配置文件并打开
[atguigu@hadoop102 group1]$ touch flume-flume-dir.conf
[atguigu@hadoop102 group1]$ vim flume-flume-dir.conf
添加如下内容
# 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。
4．执行配置文件
分别开启对应配置文件：flume-flume-dir，flume-flume-hdfs，flume-file-flume。
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group1/flume-flume-dir.conf [atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group1/flume-flume-hdfs.conf [atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group1/flume-file-flume.conf
5．启动 Hadoop 和 Hive
[atguigu@hadoop102 hadoop-2.7.2]$ sbin/start-dfs.sh [atguigu@hadoop103 hadoop-2.7.2]$ sbin/start-yarn.sh [atguigu@hadoop102 hive]$ bin/hive hive (default)>
6．检查 HDFS 上数据
7 检查/opt/module/datas/flume3 目录中数据
[atguigu@hadoop102 flume3]$ ll 总用量 8 -rw-rw-r--. 1 atguigu atguigu 5942 5 月 22 00:09 1526918887550-3