Flume Integration with Kafka

Below we will see how kafka can be integrated with Flume as a Source, Channel and Sink. If you are new to Flume and Kafka, you can refer FLUME and KAFKA.

Let us Start :

  1. Using Kafka as a SOURCE for Flume:
    We want to pass messages to a Kafka Producer, which will go through Flume channel (In-Memory) and finally getting Stored in Flume Sink (say HDFS).
    Start Zookeeper & Kafka Services and create a Topic ‘testing’ :

     

    nohup ./${kafka_home}/bin/zookeeper-server-start.sh ${kafka_home}/conf/zookeeper.properties &
    nohup ./${kafka_home}/bin/kafka-server-start.sh ${kafka_home}/conf/server.properties &
    ./${kafka_home}/bin/kafka-topic.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testing
    ./${kafka_home}/bin/kafka-topic.sh --list --zookeeper localhost:2181

    Set-up Flume Conf:

    vi ${flume_home}/conf/excercise5.conf and add below contents:
    ## Configuring Components
    a1.sources=source1
    a1.channels=channel1
    a1.sinks=sink1
    ## Configuring Source
    a1.sources.source1.type=org.apache.flume.source.kafka.KafkaSource
    a1.sources.source1.zookeeperConnect=localhost:2181
    a1.sources.source1.topic=testing
    a1.sources.source1.groupId=flume
    a1.sources.source1.channels=channel1
    a1.sources.source1.interceptors=i1
    a1.sources.source1.interceptors.i1.type=timestamp
    a1.sources.source1.kafka.consumer.timeout.ms=100
    ## Configuring Channel
    a1.channels.channel1.type=memory
    a1.channels.channel1.capacity=10000
    a1.channels.channel1.transactionCapacity=1000
    ## Configuring sink
    a1.sinks.sink1.type=hdfs
    a1.sinks.sink1.channel=channel1
    a1.sinks.sink1.hdfs.path=/tmp/kafka/%{topic}/%y-%m-%d
    ## Number of seconds to wait before rolling current file
    a1.sinks.sink1.hdfs.rollInterval=5
    ## File size to trigger roll, in byte
    a1.sinks.sink1.hdfs.rollSize=1024
    ## Number of events written to file before it rolled
    a1.sinks.sink1.hdfs.rollCount=10
    ## DataStrem - Stores data instead of ASCII values of data
    a1.sinks.sink1.hdfs.fileType=DataStream

    Start Flume agent:

    ./${flume_home}/bin/flume-ng agent -c ${flume_home}/conf/ -f ${flume_home/conf/exercise5.conf --name a1 -Dflume.root.logger=INFO,console

    Pass your Messages from Kafka Producer and Monitor the Flume agent window:

    ./${kafka_home}/bin/kafka-console-producer.sh --broker-list localhost:9092 --topic testing                                                                    [2015-09-17 02:34:54,415] WARN Property topic is not valid (kafka.utils.VerifiableProperties)
    This is a Test for flume and Kafka intigration
    We can expect these messages into Flume SINK (HDFS)
    you can see on flume agent console window that flume is creating
    Files in HDFS

    produce_mesg
    You can see from Flume agent window that it would be storing those messages to the sink (HDFS):
    HDFS_SINK

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  2. Using Kafka as a SINK for Flume:
    Now we will pass messages from Netcat (Flume Source), which will go through Flume channel (In-Memory), finally getting Stored into Kafka and Can be accessed from Kafka Consumers.
    Create a new topic ‘testing3’:

     

    [student4@nbc-n4 flume]$ ~/kafka_2.10-0.8.2.0/bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testing3

    Listing the Topics:

    [student4@nbc-n4 flume]$ ~/kafka_2.10-0.8.2.0/bin/kafka-topics.sh --list --zookeeper localhost:2181
    testing
    testing3

    Set-up Flume Conf:

    [student4@nbc-n4 flume]$ cat confFiles/exercise6.conf
    ##Configuring Components
    a1.sources=source1
    a1.channels=channel1
    a1.sinks=sink1
    ## Configuring Source
    a1.sources.source1.channels=channel1
    a1.sources.source1.type=netcat
    a1.sources.source1.bind=10.11.12.122
    a1.sources.source1.port=44444
    ## Configuring Channel
    a1.channels.channel1.type=memory
    a1.channels.channel1.capacity=10000
    a1.channels.channel1.transactionCapacity=1000
    ## Configuring Sink
    a1.sinks.sink1.type=org.apache.flume.sink.kafka.KafkaSink
    a1.sinks.sink1.topic=testing2
    a1.sinks.sink1.zookeeperConnect=localhost:2181
    a1.sinks.sink1.brokerList=localhost:9092
    a1.sinks.sink1.channel=channel1
    a1.sinks.sink1.batchSize=20

    Start Flume Agent:

    ./${flume_home}/bin/flume-ng agent -c ${flume_home}/conf/ -f ${flume_home/conf/exercise5.conf --name a1 -Dflume.root.logger=INFO,console

    Pass the Messages using Netcat and Access the same message via Kafka-consumers:

  3. [student4@nbc-n4 ~]$ # Passing Messages via Netcat
    [student4@nbc-n4 ~]$ nc 10.11.12.122 44444
    Hi
    OK
    This is Kafka-Flume Integration Testing
    OK
    We are using Kafka as Sink here
    OK
    You can access these message from Kafka-Consumers
    OK
    [student4@nbc-n4 ~]$ # Checking these messages in Kafka
    [student4@nbc-n4 ~]$ ./kafka_2.10-0.8.2.0/bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic testing3 --from-beginning
    Hi
    This is Kafka-Flume Integration Testing
    We are using Kafka as Sink here
    You can access these message from Kafka-Consumers


    3. Using Kafka as a CHANNEL for Flume:
    Now we will pass messages from Netcat (Flume Source), which will go through Kafka Topics (act as channel) and finally, can be accessed from Kafka Consumers.
    Below is the configuration file:

    [student4@nbc-n4 flume]$ cat confFiles/exercise7.conf
    #Name the components on this agent
    a1.sources = r1
    a1.channels = c1
    #Describe/configure the source
    a1.sources.r1.type = netcat
    a1.sources.r1.bind = localhost
    a1.sources.r1.port = 44444
    a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel
    a1.channels.c1.capacity = 10000
    a1.channels.c1.transactionCapacity = 1000
    a1.channels.c1.brokerList=localhost:9092
    a1.channels.c1.topic=testing3
    a1.channels.c1.zookeeperConnect=localhost:2181
    #Bind the source and sink to the channel
    a1.sources.r1.channels = c1

    Using above config file, you can try sending messages via Netcat and access them via Kafka-consumers.
     

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