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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-ultimate-kafka-streams-3x-real-time-data-processing/
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**课程名称：** Kafka Streams (3.x) 实战：实时数据处理终极课程 **课程概述：** 本课程全面深入地讲解 Kafka Streams 框架，从基础概念到高级应用，旨在帮助学员掌握实时数据处理的核心技术。课程内容涵盖 Kafka Streams 的方方面面，并提供大量实践案例，让学员能够从零开始，逐步成长为 Kafka Streams 专家。 **先修要求：** * 必须具备 Java 开发经验。 * 必须具备 Kafka 基础知识。 * 建议具备 Spark Streaming、Storm、Flink 等流处理开发经验。 **课程特色：** * **源码驱动：** 结合源码深入理解 Kafka Streams 工作原理。 * **海量实践：** 通过大量的动手实践巩固所学知识。 * **循序渐进：** 从浅入深，系统性地讲解 Kafka Streams。 * **详尽细致：** 覆盖 Kafka Streams 框架的所有知识点。 * **丰富案例：** 提供全面的综合案例，展示 Kafka Streams 的实际应用。 **课程大纲：** 1. **Kafka Streams 入门：** 介绍 Kafka Streams 的基本概念和术语。 2. **Kafka Streams 并行模式：** 深入理解 Kafka Streams 的并行处理机制。 3. **无状态操作：** * `map`、`mapValues`、`flatMap`、`flatMapValues`、`selectKey`、`foreach` * `Print` & `Peek`、`split` & `merge` & `Branched KStream` * 自定义 Serde 4. **XMall 交易数据实时分析实战。** 5. **有状态操作与状态存储：** * 详细讲解内部数据重分布和有状态转换。 * **Join 操作：** Inner join/left join/outer join。 * **Grouping 操作。** * **Aggregation 操作：** count, reduce, aggregate。 6. **实时销售冠军应用构建。** 7. **实时销售统计应用构建。** 8. **KTable 与窗口操作：** * **KTable 详解：** 创建、基本操作（map values, filtering）及有状态转换。 * `transformValues` 实现射击游戏。 * **KStream & KTable Join：** KStream 与 KTable 的多对一、一对一 join 操作。 * **KTable & KTable Join：** KTable 之间多对一、一对一 join 操作。 9. **状态存储与查询：** * `Queryable Store`：学习如何从有状态的 KStream 中查询数据。 * `TimeWindowedKStream Queryable state store`：学习如何查询带窗口的 KStream 状态。 10. **时间语义与窗口操作：** * 自定义 TimestampExtractor。 * **Tumbling Time Window：** 用于潜在网络攻击分析。 * **Hopping Time Window：** 用于网站访问实时统计。 * **Heartbeat 传感器数据实时分析**：用于患者健康监测。 11. **KGroupedStream Windowing 操作。** **课程目标：** * **完全理解** Kafka Streams 的概念和关键术语。 * **完全理解** Kafka Streams 的并行模式。 * **精通** 无状态流式应用程序的构建，深入理解每种无状态操作。 * **精通** 有状态流式应用程序的构建，深入理解每种有状态操作。 * **精通** 内部数据分布的底层机制。 * **精通** 状态存储，能够基于状态存储构建复杂的事件处理（CEP）实时应用程序。 * **完全理解** KTable 和窗口操作。 **结语：** 学完本课程，您将成为 Kafka Streams 领域的专家，并具备使用 Kafka Streams 框架构建复杂事件处理（CEP）实时应用程序的能力。
**** Please enable the vedio cc function (captions ) *****First of all, welcome to enroll this course. This is a course about Kafka Streams. In this course, every knowledge detail of the Kafka Streams framework is introduced in great detail. Secondly, I sincerely hope that you can enable the vedio cc function (captions ) , because my native language is not English, the spoken language is not very standard, but I assure you that the course content is absolutely detailed and step by step，From shallow to deep.Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.[Pre-Requisites]You should have the Java development experiences(***this is mandatory requirement***)You should have the Kafka foundation knowledge(***this is mandatory requirement***)It's better have another streaming develop experiences such as Spark Streaming, Storm, Flink【Course Characteristics】Driven by source codeLots of practicesFrom shallow to deepAbsolutely detailed and step by stepCovers all knowledge points of Kafka Streams frameworkRich comprehensive cases[Course Agenda]Introduce the Kafka StreamsTutorial the Kafka Streams key terms and conceptsKafka Streams Parallel ModeStateless operation of map transformStateless operation of mapValues transformStateless operation of flatMap transformStateless operation of flatMapValues transformStateless operation of selectKey transformStateless operation of foreachStateless operation of Print & PeekStateless operation split & merge & BranchedKStreamHow to custom SerdesXMall Transaction data real-time analysis practiseTutorial the kafka stateful operation and statestoreExplain in details of internal data redistribution and stateful transformStateful operation of Joining(inner join/left join/outer join)Stateful operation of groupingStateful operation of aggregation(count,reduce,aggregate)Build Real-time analysis the sales champion applicationBuild Real-time analysis the sales stats applicationStateful KStream Queryable StorestoreStateful TimeWindowedKStream Queryable state store for interactiveKGroupedStream windowing operationTime Semantics and custom TimestampExtractorTumbling time window for analysis of Potential Cyber AttacksHopping time window for Site Visit real-time statisticsHeartbeat sensor data real-time analysis for patient health monitoringWhat is KTable and how to create the KTableKTable basis operation such as map values, filteringKTable basis stateful operation transformValues implement the shooting gameKStream inner & left join the KTable enrichment/enhancement the orginal recordsKTable inner join, inner foreign key with other KTableKTable left join, left foreign join, outer join KTableKTable & KGroupedTable aggregating operation such as count/reduce/aggregate[Course Objectives]Fully understand the kafka Streams concepts and key termsFully understand the kafak Streams parallel modeMaster the stateless streams application building and in depth understand every stateless operationMaster the stateful streams application building and in depth understand every stateful operationMaster the internal data distribution underlying mechanismMaster the statestore, can base on the statestore build complex event process real-time applicationFully understand the KTable and Windowing operationHope you will enjoy this course, After learning this course, you will become an expert in Kafka Streams, and ability to build complex event process(CEP) real-time application based on Kafka Streams framework.
