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Kafka Tutorial

Home » Data Science » Data Science Tutorials » Kafka Tutorial

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Kafka Tutorial

Kafka is a distributed streaming platform which was created by LinkedIn and was later open-sourced and handed over to Apache Foundation. It has a huge vast network with active contributions from users and developers. Kafka is based on a distributed environment approach, which means it can run across multiple servers making it capable of using additional processing power and storage capacity.

Component of Kafka: Topic, Producer, Consumer and Brokers

In this article, we will be through the understanding of the need, application, prerequisites and a simple implementation of a Hello World program using Kafka.

Why do we need Kafka?

Following are the few key aspects which justify the need for Kafka:

  • Backend Architecture is simplified: Kafka is a streamlined platform. A streamlined platform can store huge amount of data, these data are persistent and are replicated for fault tolerance. The following figure is the architecture of a complex system that is simplified by using Kafka.

Backend Architecture is simplified

  • Real-Time Processing of Data: In a real-time application, a continuous flow of data is needed. These data should be processed immediately with reduced latency. Kafka Stream is used to building and deploying packages without any sperate stream processor or any heavy expensive infrastructure.
  • Connects to an Existing System: Kafka provides a framework known as Kafka connect to the existing systems in order to maintain the universal data pipeline.

Application

Following are the few application of Kafka :

  • Netflix: It uses Kafka to perform real-time monitoring and event processing to understand user interest and predict the media in which the user might be interested.
  • LinkedIn: LinkedIn uses Kafka messaging system in there various products like LinkedIn Newsfeed, LinkedIn Today and Hadoop. Its strong durability makes it a key factor to be used in LinkedIn.
  • Twitter:  Storm Kafka is used by Twitter as a part of their stream processing infrastructure.

Example

Let us take an example to understand how a message is sent over topics in Kafka. Suppose we want to send a message ‘Hello World’ over the topic from scratch. To do so we will follow the following steps :

Note: Syntax for each step is out of scope for this blog. You will just get an idea of the flow of the exécution of the program on how to send the message over the topic.

Step-1: Start the Zookeeper Server
Step-2: Start the Kafka Server
Step-3: Creation of a topic
Step-4: Create a producer node
Step-5: Send a message using the producer node
Step-6: Create a consumer note and Subscribe to the topic

Following the above steps, the consumer node will be able to subscribe the message over the topic.

Prerequisites

In order to learn Kafka, you must have a good understanding of the Distributed messaging system, Scala, Java, and Linux environment.

Target Audience

Kafka is for a professional who wants to make their career in big data analytics by using the Apache Kafka messaging system.

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