日志
flume通过tcp/udp采集数据并存到kafka配置
/*官方提供的kafka sink*/
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = mytopic
a1.sinks.k1.kafka.bootstrap.servers = localhost:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.ki.kafka.producer.compression.type = snappy
/**在kafka中创建一个名为 flumetest的topic*/
bin/kafka-console-consumer.sh --zookeeper mpc5:2181,mpc6:2181,mpc7 --from-beginning --topic flumetest
/**kafka中在控制台上消费消息队列的启动方式*/
bin/kafka-console-consumer.sh --zookeeper mpc5:2181,mpc6:2181,mpc7 --from-beginning --topic flumetest
/*比较好用的kafka sink 但是不可靠*/
producer.sinks.r.type = org.apache.flume.plugins.KafkaSink
producer.sinks.r.metadata.broker.list=dn1:9092,dn2:9092,dn3:9092
producer.sinks.r.partition.key=0
producer.sinks.r.partitioner.class=org.apache.flume.plugins.SinglePartition
producer.sinks.r.serializer.class=kafka.serializer.StringEncoder
producer.sinks.r.request.required.acks=0
producer.sinks.r.max.message.size=1000000
producer.sinks.r.producer.type=sync
producer.sinks.r.custom.encoding=UTF-8
producer.sinks.r.custom.topic.name=test
/*一个配置文件开始*/
a1.sources = r1
a1.channels = c1
a1.sinks =k1
#source
a1.sources.r1.type = netcat
a1.sources.r1.bind = mpc1
a1.sources.r1.port = 11203
a1.sources.r1.channels = c1
# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#sink
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = flumetest
a1.sinks.k1.kafka.bootstrap.servers = mpc5:9092,mpc6:9092,mpc7:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 0
a1.sinks.k1.kafka.producer.compression.type = snappy
a1.sinks.k1.kafka.producer.zk.connect=mpc5:2181,mpc6:2181,mpc7:2181
a1.sinks.k1.kafka.producer.serializer.class=kafka.serializer.StringEncoder
/*一个配置文件结束*/
\x0D
/*tcp采集源*/
a1.sources = r1
a1.channels = c1
a1.sources.r1.type = syslogtcp
a1.sources.r1.port = 5140
a1.sources.r1.host = localhost
a1.sources.r1.channels = c1
/*多个采集源的flume，分别是tcp和udp；sink到kafka中 开始*/
a1.sources = r1 r2
a1.channels = c1
a1.sinks =k1
#source
a1.sources.r1.type = multiport_syslogtcp
a1.sources.r1.channels = c1
a1.sources.r1.host = mpc1
a1.sources.r1.ports = 10001 10002 10003
a1.sources.r1.portHeader = port
a1.sources.r2.type = syslogudp
a1.sources.r2.port = 5140
a1.sources.r2.host = mpc1
a1.sources.r2.channels = c1
# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#sink
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = flumetest
a1.sinks.k1.kafka.bootstrap.servers = mpc5:9092,mpc6:9092,mpc7:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 0
a1.sinks.k1.kafka.producer.compression.type = snappy
a1.sinks.k1.kafka.producer.zk.connect=mpc5:2181,mpc6:2181,mpc7:2181
a1.sinks.k1.kafka.producer.serializer.class=kafka.serializer.StringEncoder
/*多个采集源的flume，分别是tcp和udp；sink到kafka中 结束*/
/*启动flume的方法*/
bin/flume-ng agent -n a1 -c conf -f conf/flume-conf.properties
/*删除一个topic在zookeeper上的元数据*/
bin/kafka-run-class.sh kafka.admin.DeleteTopicCommand --topic mytri1 --zookeeper mpc5:2181
/**flume到kafka利用id来进行分区的配置*/
a1.sources = r1 r2
a1.channels = c1
a1.sinks =k1
#source
a1.sources.r1.type = multiport_syslogtcp
a1.sources.r1.channels = c1
a1.sources.r1.host = mpc1
a1.sources.r1.ports = 10001 10002 10003
a1.sources.r1.portHeader = port
a1.sources.r1.interceptors = i2
a1.sources.r1.interceptors.i2.type=org.apache.flume.sink.solr.morphline.UUIDInterceptor$Builder
a1.sources.r1.interceptors.i2.headerName=key
a1.sources.r1.interceptors.i2.preserveExisting=false
a1.sources.r2.type = syslogudp
a1.sources.r2.port = 5140
a1.sources.r2.host = mpc1
a1.sources.r2.channels = c1
a1.sources.r2.interceptors = i2
a1.sources.r2.interceptors.i2.type=org.apache.flume.sink.solr.morphline.UUIDInterceptor$Builder
a1.sources.r2.interceptors.i2.headerName=key
a1.sources.r2.interceptors.i2.preserveExisting=false
# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#sink
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = mytri3
a1.sinks.k1.kafka.bootstrap.servers = mpc5:9092,mpc6:9092,mpc7:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 0
a1.sinks.k1.kafka.producer.zk.connect=mpc5:2181,mpc6:2181,mpc7:2181
a1.sinks.k1.kafka.producer.serializer.class=kafka.serializer.StringEncoder
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