尚硅谷大数据技术之Flume第4章 案例实操
4.1 监控端口数据
目标：Flume监控一端Console，另一端Console发送消息，使被监控端实时显示。
分步实现：
1）先将rpm软件包(xinetd-2.3.14-40.el6.x86_64.rpm、telnet-0.17-48.el6.x86_64.rpm和telnet-server-0.17-48.el6.x86_64.rpm)拷入Linux系统。执行RPM软件包安装命令：
[atguigu@hadoop102 software]$ sudo rpm -ivh xinetd-2.3.14-40.el6.x86_64.rpm
[atguigu@hadoop102 software]$ sudo rpm -ivh telnet-0.17-48.el6.x86_64.rpm
[atguigu@hadoop102 software]$ sudo rpm -ivh telnet-server-0.17-48.el6.x86_64.rpm
2）在flume目录下创建job文件夹，并在job文件夹下创建Flume Agent配置文件flume_telnet.conf
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# 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 |
3）判断44444端口是否被占用
[atguigu@hadoop102 software]$ sudo netstat -tunlp | grep 44444
4）先开启flume先听端口
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a1 --conf-file job/flume_telnet.conf -Dflume.root.logger==INFO,console
5）使用telnet工具向本机的44444端口发送内容
[atguigu@hadoop102 software]$ telnet localhost 44444
4.2 实时读取本地文件到HDFS
目标：实时监控hive日志，并上传到HDFS中
分步实现：
1）拷贝Hadoop相关jar到Flume的lib目录下（要学会根据自己的目录和版本查找jar包）
hadoop-auth-2.7.2.jar
commons-configuration-1.6.jar
hadoop-hdfs-2.7.2.jar
hadoop-common-2.7.2.jar
htrace-core-3.1.0-incubating.jar
commons-io-2.4.jar
提示：标红的jar为1.99版本flume必须引用的jar
2）创建flume_hdfs.conf文件
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# 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 /opt/module/hive/hive.log a2.sources.r2.shell = /bin/bash -c
# Describe the sink a2.sinks.k2.type = hdfs a2.sinks.k2.hdfs.path = hdfs://hadoop102:9000/flume/%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 |
3）执行监控配置
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a2 --conf-file job/flume_hdfs.conf
4）开启hive或者操作hive使其产生日志
4.3 实时读取目录文件到HDFS
目标：使用flume监听整个目录的文件
分步实现：
1）创建配置文件flume-dir.conf
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a3.sources = r3 a3.sinks = k3 a3.channels = c3
# Describe/configure the source a3.sources.r3.type = spooldir a3.sources.r3.spoolDir = tail -F /opt/module/flume/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://hadoop102:9000/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 |
2）执行测试：执行如下脚本后，请向upload文件夹中添加文件
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a3 --conf-file job/flume-dir.conf
说明： 在使用Spooling Directory Source时
a.不要在监控目录中创建并持续修改文件
b.上传完成的文件会以.COMPLETED结尾
c.被监控文件夹每600毫秒扫描一次文件变动
4.4 单Flume多Channel、Sink
目标：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 filesystem。
分步实现：
1）创建flume-1.conf，用于监控hive.log文件的变动，同时产生两个channel和两个sink分别输送给flume-2和flume3：
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# 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 /opt/module/hive/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 |
2）创建flume-2.conf，用于接收flume-1的event，同时产生1个channel和1个sink，将数据输送给hdfs：
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# 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-3.conf，用于接收flume-1的event，同时产生1个channel和1个sink，将数据输送给本地目录：
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# 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 = hadoop102 a3.sources.r1.port = 4142
# Describe the sink a3.sinks.k1.type = file_roll a3.sinks.k1.sink.directory = /home/atguigu/flume3
# 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 |
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）执行测试：分别开启对应flume-job（依次启动flume-3，flume-2，flume-1），同时产生文件变动并观察结果：
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group-job1/flume-3.conf
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group-job1/flume-2.conf
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group-job1/flume-1.conf
4.5 多Flume汇总数据到单Flume
目标：flume-1监控文件hive.log，flume-2监控某一个端口的数据流，flume-1与flume-2将数据发送给flume-3，flume3将最终数据写入到HDFS。
分步实现：
1）创建flume-1.conf，用于监控hive.log文件，同时sink数据到flume-3：
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# 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 /opt/module/hive/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
# 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 |
2）创建flume-2.conf，用于监控端口44444数据流，同时sink数据到flume-3：
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# 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 = hadoop102 a2.sources.r1.port = 44444
# Describe the sink a2.sinks.k1.type = avro a2.sinks.k1.hostname = hadoop102 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 |
3）创建flume-3.conf，用于接收flume-1与flume-2发送过来的数据流，最终合并后sink到HDFS：
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# 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 = hadoop102 a3.sources.r1.port = 4141
# Describe the sink a3.sinks.k1.type = hdfs a3.sinks.k1.hdfs.path = hdfs://hadoop102:9000/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 |
4）执行测试：分别开启对应flume-job（依次启动flume-3，flume-2，flume-1），同时产生文件变动并观察结果：
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group-job2/flume-3.conf
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group-job2/flume-2.conf
[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group-job2/flume-1.conf
提示：测试时记得启动hive产生一些日志，同时使用telnet向44444端口发送内容，如：
[atguigu@hadoop102 hive]$ bin/hive
[atguigu@hadoop102 flume]$ telnet hadoop102 44444
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