多个agent串联
采集需求：比如业务系统使用log4j生成的日志，日志内容不断增加，需要把追加到日志文件中的数据实时采集到hdfs,使用agent串联
根据需求，首先定义以下3大要素
第一台flume agent
l 采集源，即source——监控文件内容更新 : exec ‘tail -F file’
l 下沉目标，即sink——数据的发送者，实现序列化 : avro sink
l Source和sink之间的传递通道——channel，可用file channel 也可以用 内存channel
第二台flume agent
l 采集源，即source——接受数据。并实现反序列化 : avro source
l 下沉目标，即sink——HDFS文件系统 : HDFS sink
l Source和sink之间的传递通道——channel，可用file channel 也可以用 内存channel
配置文件编写：
Flume-agent1:tail-avro-avro-logger.conf
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#tail-avro-avro-logger.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 /home/hadoop/bigdatasoftware/datas/access.log a1.sources.r1.channels = c1
# Describe the sink ##sink端的avro是一个数据发送者 a1.sinks.k1.type = avro a1.sinks.k1.hostname = hadoop-001 a1.sinks.k1.port = 41414 a1.sinks.k1.batch-size = 10
# 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 |
Flume-agent2: avro-hdfs.conf
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a1.sources = r1 a1.sinks =s1 a1.channels = c1
##source中的avro组件是一个接收者服务 a1.sources.r1.type = avro a1.sources.r1.bind = 0.0.0.0 a1.sources.r1.port = 41414
a1.sinks.s1.type=hdfs a1.sinks.s1.hdfs.path=hdfs://hadoop-001:9000/logs/flume/ a1.sinks.s1.hdfs.filePrefix = access_log a1.sinks.s1.hdfs.batchSize= 100 a1.sinks.s1.hdfs.fileType = DataStream a1.sinks.s1.hdfs.writeFormat =Text a1.sinks.s1.hdfs.rollSize = 10240 a1.sinks.s1.hdfs.rollCount = 1000 a1.sinks.s1.hdfs.rollInterval = 10 a1.sinks.s1.hdfs.round = true a1.sinks.s1.hdfs.roundValue = 10 a1.sinks.s1.hdfs.roundUnit = minute
a1.channels.c1.type = memory a1.channels.c1.capacity = 1000 a1.channels.c1.transactionCapacity = 100
a1.sources.r1.channels = c1 a1.sinks.s1.channel = c1 |