Building Stream Processing Applications with Kafka Streams培訓

Introduction

• Kafka vs Spark, Flink, and Storm

Overview of Kafka Streams Features

• Stateful and stateless processing, event-time processing, DSL, event-time based windowing operations, etc.

Case Study: Kafka Streams API for Predictive Budgeting

Setting up the Development Environment

Creating a Streams Application

Starting the Kafka Cluster

Preparing the Topics and Input Data

Options for Processing Stream Data

• High-level Kafka Streams DSL
• Lower-level Processor

Transforming the Input Data

Inspecting the Output Data

Stopping the Kafka Cluster

Options for Deploying the Application

• Classic ops tools (Puppet, Chef and Salt)
• Docker
• WAR file

Troubleshooting

Summary and Conclusion