Published 10/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 87 lectures (7h 31m) | Size: 4 GB
Apache Kafka Streams: Stateless Streams, Stateful Streams, KTable, Window, Statestore, RocksDB,Real-Time data analysis
What you’ll learn
Fullly understand Real-Time data process model of Kafka Streams
In Depth understand Kafka Streams stateless operation
In Depth understand Kafka Streams stateful operation
In Depth understand Kafka Streams KTable & GlobalKTable
Build Complex Event Process Application
Rocksdb and statestore in Kafka Streams
Requirements
Java(1.8+) Development Experiences
Apache Kafka Fundamental Knowledge
Big Data Development Experiences
Apache Maven project build tools
Description
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.
Who this course is for
Big Data Developer
Senior Java/Scala/Groovy/Clojure Developer
Kafka Engineer
Big Data Engineer
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