Configuring and Running Apache Kafka in IBM BigInsights

This blog describes on Configuring and running the Kafka from IBM BigInsights.

Apache Kafka is an open source that provides a publish-subscribe model for messaging system. Refer : https://kafka.apache.org/

I assume that you were aware of  terminologies like Producer, Subscriber, Kafka Brokers, Topic and Partitions. Here, I will be focusing on creating multiple Brokers in BigInsights then create a topic and publish the messages from command line and consumer getting it from the Broker.


Environment: BigInsights 4.2

 Step 1: Creating Kafka Brokers from Ambari

By default, Ambari will have one Kafka Broker configured.  Based on your usecase, you may need to create multiple brokers.

Login to Ambari UI --> Click on Host and add the Kafka Broker to the node where you need to install Broker.

 You can see multiple brokers running in Kafka UI.

 
Step 2: Create a Topic

Login to one of the node where broker is running.  Then create a topic.

cd /usr/iop/4.2.0.0/kafka/bin

su kafka -c "./kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 2 -partitions 1 --topic CustomerOrder"

You can get the details of the topic using the below describe command.

su kafka -c "./kafka-topics.sh --describe --zookeeper localhost:2181 --topic CustomerOrder"

 
Step 3: Start the Producer

In the argument --broker-list, pass all the brokers that are running.

su kafka -c "./kafka-console-producer.sh --broker-list bi1.test.com:6667,bi2.test.com:6667 --topic CustomerOrder"

When you run the above command, it will be waiting for user input. You can pass a sample message

{"ID":99, "CUSTOMID":234,"ADDRESS":"12,5-7,westmead", "ORDERID":99, "ITEM":"iphone6", "COST":980}

Step 4: Start the Consumer

Open an other Linux terminal and start the consumer. It will display all the messages send to producer.

su kafka -c "./kafka-console-consumer.sh --zookeeper localhost:2181 --from-beginning --topic CustomerOrder"

 

 Thus, We are able to configure and perfom a sample pub-sub system using Kafka.