Flume案例二

案例四：Flume与Flume之间数据传递：单Flume多Channel、Sink

目标：使用flume1监控文件变动，flume1将变动内容传递给flume-2，flume-2负责存储到HDFS。同时flume1将变动内容传递给flume-3，flume-3负责输出到local

分步实现：

1：创建flume1.conf，用于监控某文件的变动，同时产生两个channel和两个sink分别输送给flume2和flume3：

在bigdata31，创建/opt/mod/flume/conf/flume-1.conf文件

# 1.agent     source->channel对应关系1/n    sink->channel对应关系1/1
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

# 2.source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /opt/zhang
a1.sources.r1.shell = /bin/bash -c

# 3.sink1
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = bigdata32
a1.sinks.k1.port = 4141

# sink2
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = bigdata33
a1.sinks.k2.port = 4141

# 4.channel—1
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# 4.channel—2
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flume1的event，同时产生1个channel和1个sink，将数据输送给hdfs：

在bigdata32，创建/opt/mod/flume/conf/flume-2.conf文件

# 1 agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1

# 2 source
a2.sources.r1.type = avro
a2.sources.r1.bind = bigdata32
a2.sources.r1.port = 4141

# 3 sink
a2.sinks.k1.type = hdfs
a2.sinks.k1.hdfs.path = hdfs://192.168.1.31:9000/flume2/%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
#最小副本数
a2.sinks.k1.hdfs.minBlockReplicas = 1

# 4 channel
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100

#5 Bind 
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1

3：创建flume-3.conf，用于接收flume1的event，同时产生1个channel和1个sink，将数据输送给本地目录：

在bigdata33，创建/opt/mod/flume/conf/flume-3.conf文件

#1 agent
a3.sources = r1
a3.sinks = k1
a3.channels = c1

# 2 source
a3.sources.r1.type = avro
a3.sources.r1.bind = bigdata33
a3.sources.r1.port = 4141

#3 sink
a3.sinks.k1.type = file_roll
#备注：此处的文件夹需要先创建好
a3.sinks.k1.sink.directory = /opt/flume3

# 4 channel
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100

# 5 Bind
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flume1，flume-2，flume-3），同时产生文件变动并观察结果：

案例五：Flume与Flume之间数据传递，多Flume汇总数据到单Flume

目标：flume11监控文件hive.log，flume-22监控某一个端口的数据流，flume11与flume-22将数据发送给flume-33，flume33将最终数据写入到HDFS。

分步实现：

1：在bigdata31创建/opt/mod/flume/conf/flume-11.conf，用于监控/opt/zhang文件，同时sink数据到flume-33
# 1 agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# 2 source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /opt/zhang 
a1.sources.r1.shell = /bin/bash -c

# 3 sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = bigdata33
a1.sinks.k1.port = 4141

# 4 channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# 5. Bind
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

2：在bigdata32创建/opt/mod/flume/conf/flume-22.conf，用于监控端口44444数据流，同时sink数据到flume-33
# 1 agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1

# 2 source
a2.sources.r1.type = netcat
a2.sources.r1.bind = bigdata32
a2.sources.r1.port = 44444

#3 sink
a2.sinks.k1.type = avro
a2.sinks.k1.hostname = bigdata33
a2.sinks.k1.port = 4141

# 4 channel
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100

# 5 Bind
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1

3：在bigdata33创建/opt/mod/flume/conf/flume-33.conf，用于接收flume11与flume22发送过来的数据流，最终合并后sink到HDFS
# 1 agent
a3.sources = r1
a3.sinks = k1
a3.channels = c1

# 2 source
a3.sources.r1.type = avro
a3.sources.r1.bind = bigdata33
a3.sources.r1.port = 4141

# 3 sink
a3.sinks.k1.type = hdfs
a3.sinks.k1.hdfs.path = hdfs://192.168.1.32:9000/flume3/%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

# 4 channel
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100

# 5 Bind
a3.sources.r1.channels = c1
a3.sinks.k1.channel = c1

4：执行测试：分别开启对应flume-job（在bigdata33、bigdata32、bigdata31，依次启动flume-33，flume-22，flume-11），同时产生文件变动并观察结果：
/opt/mod/flume/bin/flume-ng agent --conf /opt/mod/flume/conf/ --name a3 --conf-file /opt/mod/flume/conf/flume-33.conf
/opt/mod/flume/bin/flume-ng agent --conf /opt/mod/flume/conf/ --name a2 --conf-file /opt/mod/flume/conf/flume-22.conf
/opt/mod/flume/bin/flume-ng agent --conf /opt/mod/flume/conf/ --name a1 --conf-file /opt/mod/flume/conf/flume-11.conf