实战案例目录
- 1. 复制和多路复用
- 1.1 案例需求
- 1.2 需求分析
- 1.3 实现操作
- 2. 负载均衡和故障转移
- 2.1 案例需求
- 2.2 需求分析
- 2.3 实现操作
- 3. 聚合操作
- 3.1 案例需求
- 3.2 需求分析
- 3.3 实现操作
1. 复制和多路复用
1.1 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 FileSystem。
1.2 需求分析
通过使用exec source实时监控Hive日志，将日志以avro为中转站发送给Flume-2,3分别存储到不同的地方，需要注意：保存到本地的目录必须存在，如下图所示：
1.3 实现操作
首先在虚拟机对应目录下创建文件：mkdir flume3
创建配置信息文件vim 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 /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
vim flume-flume-hdfs.conf
# 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://hadoop102:9820/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
vim 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 = hadoop102 a3.sources.r1.port = 4142 # Describe the sink a3.sinks.k1.type = file_roll a3.sinks.k1.sink.directory = /opt/module/data/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
结果查看：
总用量 8
-rw-rw-r–. 1 lcl lcl 5942 5 月 22 00:09 1526918887550-3
2. 负载均衡和故障转移
2.1 案例需求
使用 Flume1 监控一个端口，其 sink 组中的 sink 分别对接 Flume2 和 Flume3，采用
FailoverSinkProcessor，实现故障转移的功能。
2.2 需求分析
通过netcat source监听4444端口，由于这里只有一个channel所以在这里使用了Sink组的形式接收同一个source(这个是可以一个channel对应多个sink，但是不能一个sink对应多个channel)，然后通过kill 命令把Flume2破坏，查看Flume3
2.3 实现操作
编辑以下三个配置文件
vim flume-netcat-flume.conf
# Name the components on this agent a1.sources = r1 a1.channels = c1 a1.sinkgroups = g1 a1.sinks = k1 k2 # Describe/configure the source a1.sources.r1.type = netcat a1.sources.r1.bind = localhost a1.sources.r1.port = 44444 a1.sinkgroups.g1.processor.type = failover a1.sinkgroups.g1.processor.priority.k1 = 5 a1.sinkgroups.g1.processor.priority.k2 = 10 a1.sinkgroups.g1.processor.maxpenalty = 10000 # 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 # Bind the source and sink to the channel a1.sources.r1.channels = c1 a1.sinkgroups.g1.sinks = k1 k2 a1.sinks.k1.channel = c1 a1.sinks.k2.channel = c1
vim flume-flume-console1.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 = hadoop102 a2.sources.r1.port = 4141 # Describe the sink a2.sinks.k1.type = logger # 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
vim flume-flume-console2.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 = hadoop102 a3.sources.r1.port = 4142 # Describe the sink a3.sinks.k1.type = logger # 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
执行命令，启动配置文件：【最后启动属于服务器地一端】
bin/flume-ng agent -n a3 -c conf/ -f job/group2/flume-flume-console2.conf -Dflume.root.logger=INFO,console bin/flume-ng agent -n a3 -c conf/ -f job/group2/flume-flume-console1.conf - Dflume.root.logger=INFO,console bin/flume-ng agent -n a3 -c conf/ -f job/group2/flume-netcat-flume.conf
使用netcat工具向本机的 44444 端口发送内容： nc localhost 44444
查看两个控制台打印日志情况，之后把Flume2 kill掉
查看Flume3打印日志情况
3. 聚合操作
3.1 案例需求
- hadoop102 上的 Flume-1 监控文件/opt/module/group.log，
- hadoop103 上的 Flume-2 监控某一个端口的数据流，
- Flume-1 与 Flume-2 将数据发送给 hadoop104 上的 Flume-3，Flume-3 将最终数据打印到控制台。
3.2 需求分析
由于需要多个虚拟机工作完成任务，所以这里需要分发flume
3.3 实现操作
创建工作目录：mkdir /opt/module/flume/job/group3
hadoop102: vim flume1-logger-flume.conf
# 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/group.log a1.sources.r1.shell = /bin/bash -c # Describe the sink a1.sinks.k1.type = avro a1.sinks.k1.hostname = hadoop104 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
hadoop 103: vim flume2-netcat-flume.conf
# 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 = hadoop103 a2.sources.r1.port = 44444 # Describe the sink a2.sinks.k1.type = avro a2.sinks.k1.hostname = hadoop104 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
hadoop104: vim flume3-flume-logger.conf
# 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 = hadoop104 a3.sources.r1.port = 4141 # Describe the sink a3.sinks.k1.type = logger # 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
执行命令，启动配置文件
bin/flume-ng agent -n a3 -c conf/ -f job/group3/flume3-flume-logger.conf - Dflume.root.logger=INFO,console bin/flume-ng agent -n a3 -c conf/ -f job/group3/flume1-logger-flume.conf bin/flume-ng agent -n a3 -c conf/ -f job/group3/flume2-netcat-flume.conf
使用以下命令在hadoop102上向/opt/module 目录下的 group.log 追加内容
echo 'hello' > group.log
在 hadoop103 上向 44444 端口发送数据
telnet hadoop103 44444
之后在hadoop104上查看接受的数据
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