Flume使用案例五

Flume与Flume之间数据传递，多Flume汇总数据到单Flume

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

1)创建 flume-1.conf，用于监控 hive.log 文件，同时 sink 数据到 flume-3

# 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 /tmp/root/hive.log
a1.sources.r1.shell = /bin/bash -c
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = 172.17.0.2
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

# 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 = 172.17.0.2
a2.sources.r1.port = 44444
# Describe the sink
a2.sinks.k1.type = avro
a2.sinks.k1.hostname = 172.17.0.2
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

# 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 = 172.17.0.2
a3.sources.r1.port = 4141
# Describe the sink
a3.sinks.k1.type = hdfs
a3.sinks.k1.hdfs.path = hdfs://172.17.0.2:8020/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)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

bin/flume-ng agent --conf conf/ --name a3 --conf-file flume-3.conf
bin/flume-ng agent --conf conf/ --name a2 --conf-file flume-2.conf
bin/flume-ng agent --conf conf/ --name a1 --conf-file flume-1.conf

如图所示：

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