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Flume集成Kafka

之前提到Flume可以直接采集数据存储到HDFS中,那为什么还要引入Kafka这个中间件呢,这个是因为在实际应用场景中,我们既需要实时计算也需要离线计算。

image-20240313120335406

Kfka to HDFS配置

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# source
a1.sources.r1.type = org.apache.flume.source.kafka.KafkaSource
a1.sources.r1.channels = channel1
a1.sources.r1.batchSize =10
a1.sources.r1.batchDurationMillis =2000
a1.sources.r1.kafka.bootstrap.servers = hadoop01:9092,hadoop02:9092,hadoop03:9092
a1.sources.r1.kafka.topics = test_r2p5
a1.sources.r1.kafka.consumer.group.id = flume-group1

# Bind the source and sink to the channel
a1.channels.c1.type = memory
a1.channels.c1.capacity =1000
a1.channels.c1.transactionCapacity =1000# Describe the sink
a1.sinks.k1.type = hdfs
a1.sinks.k1.channel = c1
a1.sinks.k1.hdfs.path = hdfs://192.168.52.100:9000/kafkaout/%Y-%m-%d
a1.sinks.k1.hdfs.filePrefix = access
a1.sinks.k1.hdfs.writeFormat = Text
a1.sinks.k1.hdfs.useLocalTimeStamp =true
a1.sinks.k1.hdfs.fileType = DataStream
a1.sinks.k1.hdfs.rollCount =0
a1.sinks.k1.hdfs.rollInterval =3600
a1.sinks.k1.hdfs.rollSize =134217728# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

File to Kafka配置

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# source
a1.sources.r1.type =exec
a1.sources.r1.command =tail-F /home/log/test.log

# Bind the source and sink to the channel
a1.channels.c1.type = memory
a1.channels.c1.capacity =1000
a1.channels.c1.transactionCapacity =1000# Describe the sink
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = test_r2p5
a1.sinks.k1.kafka.bootstrap.servers = hadoop01:9092,hadoop02:9092,hadoop03:9092
a1.sinks.k1.kafka.flumeBatchSize =10
a1.sinks.k1.kafka.producer.acks =1
a1.sinks.k1.kafka.producer.linger.ms =1
a1.sinks.k1.kafka.producer.compression.type = snappy

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

创建Topic

[root@hadoop01 kafka_2.12-2.4.0]# bin/kafka-topics.sh --create --zookeeper hadoop01:2181 --partitions 5 --replication-factor 2 --topic test_r2p5

启动flume

[root@hadoop04 conf-kafka-hdfs]# bin/flume-ng agent --name a1 --conf conf-kafka-hdfs --conf-file conf-kafka-hdfs/kafka-to-hdfs.conf -Dflume.root.logger=INFO,console[root@hadoop04 apache-flume-1.11.0-bin]# bin/flume-ng agent --name a1 --conf conf-file-kafka --conf-file conf-file-kafka/file-to-kafka.conf -Dflume.root.logger=INFO,console

创建test.log文件

[root@hadoop04 log]# echo hello world >> /home/log/test.log

验证

[root@hadoop01 kafka_2.12-2.4.0]# hdfs dfs -cat /kafkaout/2024-03-13/access.1710307375351.tmp
hello world

p01 kafka_2.12-2.4.0]# hdfs dfs -cat /kafkaout/2024-03-13/access.1710307375351.tmp
hello world

标签: flume kafka 大数据

本文转载自: https://blog.csdn.net/Grady00/article/details/136677725
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