Apache Kafka - Real-time Stream Processing (Master Class)

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Prashant Kumar Pandey

10:52:00

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1-Before you start

01-Introduction.mp4

03:44

02-About the Course.mp4

03:37

03-What do you Need for this Course.mp4

02:12

04-Debugging Problems.mp4

02:52

2-Introduction to Real-time Streams

05-Emergence of Bigdata - A Quick Recap.mp4

10:44

06-Conception of Event Streams.mp4

11:27

07-Real-time Streaming - Use Cases.mp4

15:23

08-Real-time Streaming Challenges.mp4

06:21

09-Real-time Streaming Design Consideration.mp4

13:58

10-Section Summary.mp4

01:49

3-Enter the world of Apache Kafka

11-What is Apache Kafka.mp4

03:41

12-Kafka Storage Architecture.mp4

19:49

13-Kafka Cluster Architecture.mp4

10:08

14-Kafka Work Distribution Architecture - Part 1.mp4

10:11

15-Kafka Work Distribution Architecture - Part 2.mp4

15:04

16-Section Summary.mp4

03:55

4-Creating Real-time Streams

17-Streaming into Kafka.mp4

05:06

18-Kafka Producers - Quick Start.mp4

11:49

19-Kafka Producer Internals.mp4

17:48

20-Scaling Kafka Producer.mp4

16:50

21-Advanced Kafka Producers (Exactly Once).mp4

07:01

22-Advanced Kafka Producer (Implementing Transaction).mp4

12:44

23-Kafka Producer - Micro Project.mp4

10:16

24-Kafka Producer - Final Note and References.mp4

14:23

5-Enter the Stream Processing

25-Stream Processing in Apache Kafka.mp4

05:07

26-Kafka Consumer - Practical Introduction.mp4

11:59

27-Kafka Consumer - Scalability, Fault tolerance and Missing Features.mp4

13:45

28-Kafka Streams API - Quick Start.mp4

13:11

29-Creating Streams Topology.mp4

16:03

30-Implementing Streams Topology.mp4

14:44

31-Kafka Streams Architecture.mp4

09:30

32-Section Summary and References.mp4

03:01

6-Foundation for Real Life Implementations

33-Introduction to Types and Serialization in Kafka.mp4

04:01

34-JSON Schema to POJO for JSON Serdes.mp4

09:05

35-Creating and Using JSON Serdes.mp4

08:32

36-AVRO Schema to POJO for AVRO Serdes.mp4

07:47

37-Creating and using AVRO schema in Producers.mp4

11:17

38-Creating and using AVRO schema in Kafka Streams.mp4

12:27

39-Section Summary and References.mp4

01:39

7-States and Stores

40-Understanding States and State Stores.mp4

07:26

41-Creating your First State Store.mp4

20:05

42-Caution with States.mp4

09:32

43-State Store Fault Tolerance.mp4

04:35

44-Section Summary and References.mp4

01:30

8-KTable - An Update Stream

45-Introducing KTable.mp4

05:48

46-Creating your First Update Stream - Ktable.mp4

13:16

47-Table Caching and Emit Rates.mp4

06:40

48-Introducing GlobalKTable.mp4

04:06

9-Real-time Aggregates

49-Computing Your First Aggregate - Real-time Streaming Word Count.mp4

08:15

50-Streaming Aggregates - Core Concept.mp4

07:44

51-KStream Aggregation using Reduce().mp4

06:41

52-KStream Aggregation using Aggregate().mp4

10:16

53-Common Mistakes in Aggregation.mp4

04:42

54-Count on KTable.mp4

04:34

55-KTable Aggregation using Aggregate().mp4

05:36

10-Timestamps and Windows

56-Timestamps and Timestamp Extractors.mp4

09:44

57-Creating Tumbling Windows.mp4

10:53

58-Stream Time and Grace Period.mp4

07:39

59-Supressing Intermediate Results.mp4

07:46

60-Creating Hopping Windows.mp4

03:27

61-Creating Session Windows.mp4

10:52

11-Joining Streams and Tables

62-Streaming Joins.mp4

04:43

63-Joining a KStrem to another KStream.mp4

10:04

64-Joining a KTable to another KTable.mp4

07:36

65-Joining a KStream to a KTable and GlobalKTable.mp4

04:17

66-Mixing Joins with Aggregates - Computing Top 3.mp4

14:48

67-Mixing Joins with Aggregates - Advert CTR.mp4

03:19

12-Testing Streams Application

68-How to test a Stream Processing Application.mp4

08:38

69-Unit Testing Your Topology.mp4

09:03

13-Interactive Query and Micro-Service Responses

70-Introducing Micro-services Requirement.mp4

03:57

71-Understanding Local Vs Remote State Store.mp4

05:34

72-Implementing Interactive Query Micro-service.mp4

22:43

14-Appendix

73-Setting up Apache Kafka Development Environment.mp4

13:11

Description

If you want to understand the concept of stream processing, this course is for you. Using Kafka, the course will help you get to grips with real-time stream processing and enable you to apply that knowledge to learn Kafka programming techniques. This course uses the Kafka Streams library available in Apache Kafka 2.x. All the source code and examples on Apache Kafka 2.3 open-source distribution have been tested. You'll understand and explore Confluent Platform functionalities such as Schema Registry and Avro Serdes using the Confluent Community Version. This course makes extensive use of IntelliJ IDEA and Apache Maven as the preferred development IDE. You'll leverage Log4J2 and JUnit5 for industry-standard log implementation in your application and implementing unit test cases, respectively. The code bundle is available at https://github.com/PacktPublishing/Apache-Kafka---Real-time-Stream-Processing-Master-Class

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Apache Kafka

Prashant Kumar Pandey

Instructor's Courses

Prashant Kumar Pandey is passionate about helping people learn and grow in their careers by bridging the gap between their existing and required skills. In his journey to fulfill this mission, he is authoring books, publishing technical articles, and creating training videos to help IT professionals and students succeed in the industry. He is also the founder, lead author, and chief editor of the Learning Journal portal that has been providing various skill development courses, training sessions, and technical articles since 2018.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.