（二十一）大数据实战——Flume数据采集之复制和多路复用案例实战

前言

本节内容我们完成Flume数据采集的一个多路复用案例，使用三台服务器，一台服务器负责采集本地日志数据，通过使用Replicating ChannelSelector选择器，将采集到的数据分发到另外俩台服务器，一台服务器将数据存储到hdfs，另外一台服务器将数据存储在本机，使用Avro的方式完成flume之间采集数据的传输。整体架构如下：

正文

①在hadoop101服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-file-flume-avro.conf配置文件，用于监控hive日志并传输到avro sink

- job-file-flume-avro.conf配置文件

# 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 /tmp/hadoop/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 = hadoop103
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

②在hadoop102服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-avro-flume-hdfs.conf配置文件，将监控数据传输到hadoop的hdfs系统

- job-avro-flume-hdfs.conf配置文件

# 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 = hdfs://hadoop101:8020/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 = 30
#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
# 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在hadoop103服务器的/opt/module/apache-flume-1.9.0/job目录下创建job-avro-flume-dir.conf配置文件，将监控数据传输到/opt/module/apache-flume-1.9.0/flume3目录下

- job-avro-flume-dir.conf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 = hadoop103
a3.sources.r1.port = 4142
# Describe the sink
a3.sinks.k1.type = file_roll
a3.sinks.k1.sink.directory = /opt/module/apache-flume-1.9.0/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

- 创建数据存储目录/opt/module/apache-flume-1.9.0/flume3

④启动hadoop集群

 

⑤启动hadoop102上的flume任务job-avro-flume-hdfs.conf

- 命令：

bin/flume-ng agent -c conf/ -n a2 -f job/job-avro-flume-hdfs.conf -Dflume.root.logger=INFO,console

 ⑥启动hadoop103上的flume任务job-avro-flume-dir.conf

- 命令：

bin/flume-ng agent -c conf/ -n a3 -f job/job-avro-flume-dir.conf -Dflume.root.logger=INFO,console

⑦启动hadoop101上的flume任务job-file-flume-avro.conf

- 命令：

bin/flume-ng agent -c conf/ -n a1 -f job/job-file-flume-avro.conf -Dflume.root.logger=INFO,console

⑧启动hive

 ⑨查看监控结果

- 查看hdfs

- 查看存储目录/opt/module/apache-flume-1.9.0/flume3下的文件

结语

至此，关于Flume数据采集之复制和多路复用案例实战到这里就结束了，我们下期见。。。。。。