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

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Alexander Wong

7:30:28

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1. Course Introduction

1. Course content introduction.mp4

03:27

2. Course objective and scope.mp4

01:39

3. Course Characteristics & how to learning (suggestions).mp4

01:37

4.1 The Ultimate Apache Kafka Streams Real-time Data Processing.pptx

4.2 udemy-kafka-streams.zip

4. Download the source code & PowerPoint.html

2. Apache Kafka Streams Introduction

1. What is Kafka Streams.mp4

04:44

2. Kafka Streams Key Terms.mp4

05:38

3. Kafka Streams Parallel mode.mp4

02:40

4. Data process strategy in Kafka Streams.mp4

02:21

5. Kafka Streams Development Environment Setup(Kafka Broker Setup).mp4

07:36

6. Kafka Streams Development Environment setup(Maven Project).mp4

04:46

7. Quick Start-Develop First Kafka Streams Application.mp4

09:49

8. Setup the First Kafka Stream Application and Testing.mp4

02:24

3. Build Kafka Stateless Streams Application

1. What is stateless streams application.mp4

01:43

2. Stateless Operation- Map & KeyValueMapper.mp4

05:36

3. Stateless Operation- MapValues & ValueMapper & ValueMapperWithKey.mp4

05:05

4. Stateless Operation- Filter & FilterNot & Predicate.mp4

04:37

5. Stateless Operation-FlatMap & KeyValueMapper.mp4

04:32

6. Stateless Operation-FlatMapValues&ValueMapper&ValueMapperWithKey.mp4

04:05

7. Stateless Operation-SelectKey & KeyValueMapper.mp4

03:59

8. Stateless Operation-Foreach & ForeachAction.mp4

03:16

9. Stateless Operation-Print and Peek.mp4

02:41

10. Stateless Operation-(BranchedKStream)Split Streams to multiple sub-streams.mp4

07:59

11. Stateless Operation-Merge Small KStreams to big one.mp4

02:30

12. Stateless Operation-Sink the transformed records to target topic.mp4

04:32

13. Assemble Together XMall Transaction data real-time analysis practise.mp4

05:07

14. Assemble Together XMall Transaction data real-time analysis - Data Model Define.mp4

09:36

15. Assemble Together XMall Transaction data real-time analysis-Custom Serdes.mp4

07:04

16. Assemble Together XMall Transaction data real-time analysis-Streams Application.mp4

12:01

17. Assemble Together XMall Transaction data real-time analysis-Deploy & Testing.mp4

05:12

18. Kafka Stateless Streams Recap & Summarize.mp4

01:57

4. Build Kafka Stateful Streams application & statestore(RocksDB)

1. What is stateful streams application.mp4

02:57

2. State store & state store solution.mp4

04:51

3. Stateful transformation practical (Word Count).mp4

09:50

4. Stateful transformation practical(Word Count) test and result verify.mp4

03:35

5. Understand the Kafka streams internal data redistribution and stateful transform.mp4

10:26

6. Enhancement XMall transaction reward point processor support total reward points.mp4

09:19

7. Stateful transform operations.mp4

02:11

8. KStream Joining operation introduction.mp4

02:52

9. KStream inner joining operation.mp4

09:23

10. KStream inner joining operation application startup & testing.mp4

03:04

11. Depth understand the joining operation and underlying change logs.mp4

04:32

12. KStream left joining operation.mp4

03:13

13. KStream outer joining operation.mp4

02:17

14. KStream grouping operation.mp4

02:16

15. KGroupedStream count aggregation operation practical(word count).mp4

06:38

16. KGroupedStream reduce aggregation operation practical(word count).mp4

05:40

17. Real-Time analysis the sales champion application by reduce aggregate operation.mp4

02:51

18. Develop the sales champion application by reduce aggregating operation and test.mp4

07:58

19. KGroupedStream aggregate operation for Real-Time compute sales stats reporter.mp4

11:33

20. Stateful KStream Queryable Storestore(KeyValueStore)-single instance.mp4

09:49

21. Stateful KStream Queryable Storestore(KeyValueStore)-multiple instance.mp4

06:15

22. Stateful process and ProcessorSupplier(Official documentation has bugs).mp4

03:19

23. Kafka Stateful Streams Recap & Summarize.mp4

01:57

5. Build complex streaming application with KGroupedStream windowing operation

1. Kafka Streams Time Semantics.mp4

03:46

2. Kafka LogAppendTime&CreateTime.mp4

05:26

3. Kafka Streams TimestampExtractor.mp4

03:06

4. The Kafka Streams Windowing Operation introduction.mp4

04:11

5. Tumbling time window analyzes network attack behavior in real time.mp4

04:16

6. Tumbling time window real-time analysis of network attack behavior app building.mp4

08:02

7. Suppress some updates from this changelog stream.mp4

04:36

8. Hopping time window for real-time statistics the website access traffic.mp4

08:06

9. Sliding time window for real-time statistics the website access traffic.mp4

08:47

10. Hopping time window vs Sliding time window.html

11. Session time window for real-time statistics website PV&UV.mp4

06:03

12. Assembly-Heartbeat sensor data real-time analysis patient health monitoring-I.mp4

02:55

13. Assembly-Heartbeat sensor data real-time analysis patient health monitoring-II.mp4

14:01

14. Assembly-Heartbeat sensor data real-time analysis patient health monitoring-III.mp4

04:35

15. KGroupedStream Interactive Queryable Storestore(WindowStore).mp4

05:47

16. KGroupedStream & Windowing Aggregation Recap and Summarize.mp4

01:39

6. Build Updatable Streams Application with KTable

1. What is KTable.mp4

02:52

2. Create KTable from StreamsBuilder(Official documentation has bugs).mp4

10:31

3. Create KTable from KStream.mp4

04:00

4. KTable basic operation introduction and Tombstone records explanation.mp4

02:43

5. Lab KTable basic operation exercises(contains tombstone records).mp4

09:45

6. KTable transformValues operation and shoot game.mp4

15:56

7. KStream inner join the KTable.mp4

06:27

8. KStream left join the KTable.mp4

02:29

9. KTable inner join the KTable.mp4

03:38

10. KTable Foreign Key inner join the KTable.mp4

04:27

11. KTable supported joining operations.mp4

01:05

12. KTable grouping & count aggregating count the number of employees.mp4

06:21

13. KTable grouping & reduce aggregating statistics department total salary.mp4

09:16

14. KTable grouping & aggregate aggregating statistics department total salary.mp4

07:36

15. KTable Recap and Summarize.mp4

01:17

7. GlobalKTable API

1. What is GlobalKTable.mp4

01:56

2. GlobalKTable vs KTable.mp4

04:02

3. KStream joining(inner&left) GlobalKTable.mp4

05:52

Description

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

Who is this for?

Big Data Developer

Senior Java/Scala/Groovy/Clojure Developer

Kafka Engineer

Big Data Engineer

More details

Description
** 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 stepï¼ŒFrom 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

ã€Course Characteristicsã€‘
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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Apache Kafka

Alexander Wong

Instructor's Courses

He has more than 10 years of development experience, familiar with CI, CD and other related technologies, and is good at high concurrency, distributed application architecture and design. He is a bestselling author and has published three books in total.More than 20 sets of video courses have been released on Chinese websites, with more than 1 million downloads.

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