Kafka集成flume

1.flume作为生产者集成Kafka

kafka作为flume的sink,扮演消费者角色

1.1 flume配置文件

vim $kafka/jobs/flume-kafka.conf

bash 复制代码
# agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1 c2

# Describe/configure the source
a1.sources.r1.type = TAILDIR
#记录最后监控文件的断点的文件,此文件位置可不改
a1.sources.r1.positionFile =  /export/server/flume/job/data/tail_dir.json
a1.sources.r1.filegroups = f1 f2
a1.sources.r1.filegroups.f1 = /export/server/flume/job/data/.*file.*
a1.sources.r1.filegroups.f2 =/export/server/flume/job/data/.*log.*

# Describe the sink
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = customers
a1.sinks.k1.kafka.bootstrap.servers =node1:9092,node2:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.k1.kafka.producer.compression.type = snappy


# 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

1.2开启flume监控

flume-ng agent -n a1 -c conf/ -f /export/server/kafka/jobs/kafka-flume.conf

1.3开启Kafka消费者

kafka-console-consumer.sh --bootstrap-server node1:9092,node2:9092 --topic consumers --from-beginning

1.4生产数据

往被监控文件输入数据

ljr@node1 data$echo hello >>file2.txt

ljr@node1 data$ echo ============== >>file2.txt

查看Kafka消费者

可见Kafka集成flume生产者成功。

2.flume作为消费者集成Kafka

kafka作为flume的source,扮演生产者角色

2.1flume配置文件

vim $kafka/jobs/flume-kafka.conf

bash 复制代码
# agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = org.apache.flume.source.kafka.KafkaSource
#注意不要大于channel transactionCapacity的值100
a1.sources.r1.batchSize = 50 
a1.sources.r1.batchDurationMillis = 200
a1.sources.r1.kafka.bootstrap.servers =node1:9092, node1:9092
a1.sources.r1.kafka.topics = consumers
a1.sources.r1.kafka.consumer.group.id = custom.g.id

# Describe the sink
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
#注意transactionCapacity的值不要小于sources batchSize的值50
a1.channels.c1.transactionCapacity = 100

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

2.2开启flume监控

flume-ng agent -n a1 -c conf/ -f /export/server/kafka/jobs/kafka-flume1.conf

2.3开启Kafka生产者并生产数据

kafka-console-producer.sh --bootstrap-server node1:9092,node2:9092 --topic consumers

查看flume监控台

可见Kafka集成flume消费者成功。

相关推荐
pnoker18 小时前
IoT DC3 消息总线:六适配器可插拔设计
物联网·架构·kafka·消息队列·rabbitmq
cxhello20 小时前
消费者活着、心跳正常、日志干净,但它七天没拉过一条消息
python·kafka
Lost of 程序猿1 天前
ASP.NET Core Saga 分布式事务深度实战:备件采购跨服务长流程,如何保证“要么全成,要么全回“
分布式·后端·asp.net
XiYang-DING1 天前
地图城市缓存优化:ApplicationReadyEvent + Caffeine + Redis + Redisson 分布式锁
redis·分布式·缓存
2601_962175661 天前
RabbitMQ 的工作模式
分布式·rabbitmq
头茬韭菜1 天前
图解 Fluss(四):分布式协调 —— 选举、副本状态机与
分布式·fluss
2601_962218612 天前
万象生鲜系统全链路溯源一码查询技术实现食材来源可查
分布式·微服务·云原生·架构
Dreams_l2 天前
RabbitMQ介绍及其工作模式
分布式·rabbitmq
2601_962218612 天前
万象生鲜系统大数据采购预测算法降低库存积压稳居第一
分布式·微服务·云原生·架构
程序员夏洛2 天前
Redis 中如何实现分布式锁?
数据库·redis·分布式