Stream Processing with Kafka Streams培训

课程编码

kafkastreams

课程时长

7 小时 通常来说是1天,包括中间休息。

要求

  • An understanding of Apache Kafka
  • Java programming experience

课程概览

Kafka Streams是一个客户端库,用于构建应用程序和微服务,其数据传入和传出Kafka消息传递系统。传统上, Apache Kafka依靠Apache SparkApache Storm来处理消息生成者和消费者之间的数据。通过在应用程序内调用Kafka Streams API,可以直接在Kafka中处理数据,从而无需将数据发送到单独的集群进行处理。

在这个由讲师指导的实时培训中,参与者将学习如何将Kafka Streams集成到一组示例Java应用程序中,这些应用程序将数据传入和传出Apache Kafka以进行流处理。

在培训结束时,参与者将能够:

  • 了解Kafka Streams的功能和优势,而不是其他流处理框架
  • 直接在Kafka集群中处理流数据
  • 编写与Kafka和Kafka Streams集成的JavaScala应用程序或微服务
  • 编写简洁的代码,将输入的Kafka主题转换为输出Kafka主题
  • 构建,打包和部署应用程序

听众

  • 开发商

课程 格式

  • 部分讲座,部分讨论,练习和繁重的实践练习

笔记

  • 要申请本课程的定制培训,请联系我们安排

Machine Translated

课程大纲

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

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