Stream Processing Design Patterns with Kafka Streams

Stream Processing Design Patterns with Kafka Streams

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 07m | 228 MB

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

Table of Contents

1 Stream processing with Kafka
2 Prerequisites
3 What is stream processing
4 Streaming opportunities and challenges
5 Streaming with Kafka Streams
6 Kafka Streams DSL
7 Setting up the exercise files
8 Setting up Kafka
9 Setting up MariaDB and Redis
10 Streaming analytics Pattern
11 Streaming analytics Use case design
12 Streaming analytics Helper classes
13 Streaming analytics Pipeline implementation
14 Streaming analytics Results review
15 Alerts and thresholds Pattern
16 Alerts and thresholds Use case design
17 Alerts and thresholds Helper classes
18 Alerts and thresholds Pipeline implementation
19 Alerts and thresholds Review
20 Leaderboards Pattern
21 Leaderboards Use case design
22 Leaderboards Helper classes
23 Leaderboards Pipeline implementation
24 Leaderboards Review
25 Real-time predictions Pattern
26 Real-time predictions Use case design
27 Real-time predictions Helper classes
28 Real-time predictions Pipeline implementation
29 Real-time predictions Review
30 Use case definition
31 Design of the project
32 Code walk-through
33 Execute and analyze
34 Next steps