Description

The online course In Apache Kafka-Real time Stream Processing is completely beginner-oriented. Kafka is a client library used for processing and analyzing the data. If you are eager to learn and understand theories and practical examples of Kafka, then this course will help you gain knowledge of Kafka programming techniques.


You should learn Kafka streams because it has a low barrier to enter in. It is quick and runs small-level proof of concepts in the particular machine. In this course, you will understand each such as Ingestion time, Processing time, and event time

What are the reasons to learn Apache Kafka?

  • from the basics of Kafka concepts and architecture, we'll start
  • Real-time stream experience in designing and developing and testing 
  • Understanding auto-generated java objects from JSON
  • Testings like Unit and Integration
  • clearing concepts and fundamentals of AVRO
  • Kafka streams architecture, DSL, and API

Besides this, you will understand Apache Kafka's open-source distribution. You will also understand its confluent platform function. The course is comprehensive and in-depth, so you need not worry about concepts and their industrial relatability.

The requirements are quite basic you just need to have a sound knowledge of Java and be familiar with Java 8 Lamda. You need to have a PC or laptop with internet connectivity and also your system configuration should have an OS like Windows or Mac with 4 GB ram. 

Course Content

Total: 66 lectures
  • Introduction
  • Debugging Problems
  • Emergence of Bigdata - A Quick Recap
  • Conception of Event Streams
  • Real-time Streaming - Use Cases
  • Real-time Streaming Challenges
  • Real-time Streaming Design Consideration
  • What is Apache Kafka?
  • Kafka Storage Architecture
  • Kafka Cluster Architecture
  • Kafka Work Distribution Architecture - Part 1
  • Kafka Work Distribution Architecture - Part 2
  • Streaming into Kafka
  • Kafka Producers - Quick Start
  • Kafka Producer Internals
  • Scaling Kafka Producer
  • Advanced Kafka Producers (Exactly Once)
  • Advanced Kafka Producer (Implementing Transaction)
  • Kafka Producer - Micro Project
  • Kafka Producer - Final Note and References
  • Stream Processing in Apache Kafka
  • Kafka Consumer - Practical Introduction
  • Kafka Consumer - Scalability, Fault tolerance and Missing Features
  • Kafka Streams API - Quick Start
  • Creating Streams Topology
  • Implementing Streams Topology
  • Kafka Streams Architecture
  • Introduction to Types and Serialization in Kafka
  • JSON Schema to POJO for JSON Serdes
  • Creating and Using JSON Serdes
  • AVRO Schema to POJO for AVRO Serdes
  • Creating and using AVRO schema in Producers
  • Creating and using AVRO schema in Kafka Streams
  • Understanding States and State Stores
  • Creating your First State Store
  • Caution with States
  • State Store Fault Tolerance
  • Introducing KTable
  • Creating your First Update Stream - Ktable
  • Table Caching and Emit Rates
  • Introducing GlobalKTable
  • Computing Your First Aggregate - Real-time Streaming Word Count
  • Streaming Aggregates - Core Concept
  • KStream Aggregation using Reduce()
  • KStream Aggregation using Aggregate()
  • Common Mistakes in Aggregation
  • Count on KTable
  • KTable Aggregation using Aggregate()
  • Timestamps and Timestamp Extractors
  • Creating Tumbling Windows
  • Stream Time and Grace Period
  • Supressing Intermediate Results
  • Creating Hopping Windows
  • Creating Session Windows
  • Streaming Joins
  • Joining a KStrem to another KStream
  • Joining a KTable to another KTable
  • Joining a KStream to a KTable and GlobalKTable
  • Mixing Joins with Aggregates - Computing Top 3
  • Mixing Joins with Aggregates - Advert CTR
  • How to test a Stream Processing Application
  • Unit Testing Your Topology
  • Introducing Micro-services Requirement
  • Understanding Local Vs Remote State Store
  • Implementing Interactive Query Micro-service
  • Setting up Apache Kafka Development Environment

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