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Mixed Branching of a KStream
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Classroom Contents
Kafka Streams with Spring Cloud
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- 1 Kafka Streams using Spring Cloud | Learn Apache Kafka for Spring Boot Developers
- 2 Kafka Streams using Spring Cloud Streams | Who should learn take course | Course Prerequisite
- 3 Installing and Running Spring Kafka | Spring Kafka Development Environment
- 4 Kafka Spring Boot Starter Project | Initializing Spring Kafka Project | Kafka Project in Gradle
- 5 Installing Confluent Kafka on Windows | Setup Kafka cluster in WSL2 | Windows sub system for Linux
- 6 Kafka Streams Project | Creating and Running Kafka Streams using Spring Cloud on windows machine
- 7 Installing Kafka on Mac | Confluent Kafka on Mac | Setup your Kafka Development Environment on Mac
- 8 Creating Kafka Streams project on Mac | Kafka Streams using Spring Cloud Streams on Mac machine
- 9 Kafka Support in Spring | Spring Boot Vs Spring Cloud Vs Spring Cloud Stream Vs Spring Kafka Streams
- 10 Spring Cloud Architecture | Introduction to Spring Cloud Streams for real-time stream processing
- 11 How Kafka Streams work in Spring Cloud | What is Kafka Streams | Kafka Streams Vs Spring Cloud
- 12 Simple RESTful Kafka Producer
- 13 Creating Retail POS Simulator
- 14 Producing JSON Messages
- 15 Producing AVRO Messages
- 16 Real time Stream Processing Requirement
- 17 Implementing POS Fanout JSON to Avro
- 18 Real life Serialization Scenarios
- 19 Processing AVRO message Stream
- 20 Understanding Record Serialization
- 21 Overview of KStream Methods
- 22 Kafka Streams Exactly Once Implementation
- 23 Implementing Exactly Once
- 24 Let's Practice - A Complex Problem Statement
- 25 Working with XML Inputs
- 26 Handling Errors and Exceptions
- 27 Mixed Branching of a KStream
- 28 Handling Poison Pills
- 29 Introducing KTable
- 30 Deep Dive into KTable
- 31 Computing Streaming Aggregates
- 32 Aggregation Concepts
- 33 Reducing A Kafka Stream
- 34 Aggregating a Kafka Stream
- 35 Aggregation Challenges
- 36 KTable Aggregation
- 37 Kafka Time Semantics
- 38 Windowing Aggregates
- 39 Tumbling Window Vs Hopping Time Window
- 40 Session Window and Grace Period
- 41 Joins in Kafka Stream
- 42 KStream to KStream Joins
- 43 KTable to KTable Join
- 44 KStream to KTable Join
- 45 Implementing Complex Aggregation
- 46 Super Simple Stream Listener
- 47 Unit Testing Stream Listeners
- 48 Converting Stream Listener to Functional Style
- 49 Epilog
