The Ultimate Kafka Streams (3.x) : Real-time Data Processing

Apache Kafka Streams: Stateless Streams, Stateful Streams, KTable, Window, Statestore, RocksDB,Real-Time data analysis

**** 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 code

• Lots of practices

• From shallow to deep

• Absolutely detailed and step by step

• Covers all knowledge points of Kafka Streams framework

• Rich comprehensive cases

[Course Agenda]

• Introduce the Kafka Streams

• Tutorial the Kafka Streams key terms and concepts

• Kafka Streams Parallel Mode

• Stateless operation of map transform

• Stateless operation of mapValues transform

• Stateless operation of flatMap transform

• Stateless operation of flatMapValues transform

• Stateless operation of selectKey transform

• Stateless operation of foreach

• Stateless operation of Print&Peek

• Stateless operation split & merge & BranchedKStream

• How to custom Serdes

• XMall Transaction data real-time analysis practise

• Tutorial the kafka stateful operation and statestore

• Explain in details of internal data redistribution and stateful transform

• Stateful operation of Joining(inner join/left join/outer join)

• Stateful operation of grouping

• Stateful operation of aggregation(count,reduce,aggregate)

• Build Real-time analysis the sales champion application

• Build Real-time analysis the sales stats application

• Stateful KStream Queryable Storestore

• Stateful TimeWindowedKStream Queryable state store for interactive

• KGroupedStream windowing operation

• Time Semantics and custom TimestampExtractor

• Tumbling time window for analysis of Potential Cyber Attacks

• Hopping time window for Site Visit real-time statistics

• Heartbeat sensor data real-time analysis for patient health monitoring

• What is KTable and how to create the KTable

• KTable basis operation such as map values, filtering

• KTable basis stateful operation transformValues implement the shooting game

• KStream inner&left join the KTable enrichment/enhancement the orginal records

• KTable inner join, inner foreign key with other KTable

• KTable left join, left foreign join, outer join KTable

• KTable & KGroupedTable aggregating operation such as count/reduce/aggregate

[Course Objectives]

• Fully understand the kafka Streams concepts and key terms

• Fully understand the kafak Streams parallel mode

• Master the stateless streams application building and in depth understand every stateless operation

• Master the stateful streams application building and in depth understand every stateful operation

• Master the internal data distribution underlying mechanism

• Master the statestore, can base on the statestore build complex event process real-time application

• Fully understand the KTable and Windowing operation

  
  

Hope 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.