a1.sources = r1 a1.sinks = k1 k2 a1.channels = c1 c2
描述和配置source
第1步：配置数据源
a1.sources.r1.type = exec a1.sources.r1.channels = c1
配置需要监控的日志输出目录
a1.sources.r1.command = tail -F /var/log/data
Describe the sink
第2步：配置数据输出
a1.sinks.k1.type=hdfs a1.sinks.k1.channel=c1 a1.sinks.k1.hdfs.useLocalTimeStamp=true a1.sinks.k1.hdfs.path=hdfk://hadoop01:9000/flume/exents/%Y/%m/%d/%H/%M a1.sinks.k1.hdfs.filePrefix=cmcc-%H a1.sinks.k1.hdfs.minBlockReplicas=1 a1.sinks.k1.hdfs.fileType=DataStream a1.sinks.k1.hdfs.rollInterval=3600 a1.sinks.k1.hdfs.rollSize=0 a1.sinks.k1.hdfs.rollCount=0 a1.sinks.k1.hdfs.idleTimeout=0
definel the sink k2, 定义Kafka输出端
a1.sinks.k2.channel=c2 a1.sinks.k2.type=com.cmcc.chiwei.Kafka.CmccKafkaSink a1.sinks.k2.metadata.broker.list=hadoop01:9092,hadoop02:9092,hadoop03:9092 a1.sinks.k2.partition.key=0 a1.sinks.k2.partitioner.class=com.cmcc.chiwei.Kafka.CmccPartition a1.sinks.k2.serializer.class=Kafka.serializer.StringEncoder a1.sinks.k2.request.required.acks=0 a1.sinks.k2.cmcc.encoding=UTF-8 a1.sinks.k2.cmcc.topic.name=cmcc a1.sinks.k2.producer.type=async a1.sinks.k2.batchSize=100
Use a channel which buffers events in memeory
第3步：配置数据通道
define the channel c1
a1.channels.c1.type = file a1.channels.c1.checkpointDir=~/flume/flumeCheckpoint a1.channels.c1.dataDirs=~/flume/flumeData , ~/flume/flumeDataExt a1.channels.c1.capacity = 2000000 a1.channels.c1.transactionCapacity = 100
define the channel c2
a1.channels.c2.type=memeory a1.channels.c2.capacity=2000000 a1.channels.c2.transactionCapacity=100
Bind the source and sink to channel
第4步：将三者联级
a1.sources.r1.channels = c1 a1.sinks.k1.channels = c1
a1.sources.r1.selector.type=replicating
