English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 4h 46m | 1.31 GB
Learn the Kafka Streams API with hands-on examples. Learn exactly once, build and deploy apps with Java 8
The new volume in the Apache Kafka Series! Learn the Kafka Streams data-processing library, for Apache Kafka. Join hundreds of knowledge savvy students in learning one of the most promising data-processing libraries on Apache Kafka. This course is based on Java 8, and will include one example in Scala. Kafka Streams is Java-based and therefore is not suited for any other programming language. This course is the first and only available Kafka Streams course on the web. Get it now to become a Kafka expert!
Kafka is increasingly becoming a must-have skill, and this course will set you up for fast success using the Kafka Streams API. The job market will need people with your newly acquired skillset!
What You Will Learn
- Write four Kafka Streams application in Java 8.
- Configure Kafka Streams to use exactly once semantics.
- Scale Kafka Streams applications.
- Program with the high-level DSL of Kafka Streams.
- Build and package your application.
- Write tests for your Kafka Streams Topology and so much more!
Table of Contents
01 What is Kafka Streams
02 Course Objective _ Prerequisites _ Target Students
03 About your Instructor – Stephane Maarek
04 Running your first Kafka Streams Application – WordCount
05 Kafka Streams vs other stream processing libraries (Spark Streaming, NiFi, Flink
06 Code Download for this Class
07 Section Objective
08 Kafka Streams Core Concepts
09 Environment and IDE Setup – Java 8, Maven, IntelliJ IDEA
10 Starter Project Setup
11 Kafka Streams Application Properties
12 Java 8 Lambda Functions – quick overview
13 Word Count Application Topology
14 Printing the Kafka Streams Topology
15 Kafka Streams Graceful Shutdown
16 Running Application from IntelliJ IDEA
17 Debugging Application from IntelliJ IDEA
18 Internal Topics for our Kafka Streams Application
19 Packaging the application as Fat Jar & Running the Fat Jar
20 Scaling our Application
21 Section Wrap-Up
22 Section Objectives
23 KStream & KTables
24 Stateless vs Stateful Operations
25 MapValues _ Map
26 Filter _ FilterNot
27 FlatMapValues _ FlatMap
28 Branch
29 SelectKey
30 Reading from Kafka
31 Writing to Kafka
32 Streams Marked for Re-Partition
33 Refresher on Log Compaction
34 KStream and KTables Duality
35 Transforming a KTable to a KStream
36 Transforming a KStream to a KTable
37 Section Summary
38 FavouriteColour – Practice Exercise Description & Guidance
39 Stuck Here are some Hints!
40 Java Solution
41 Running the application
42 Scala Solution
43 Section Objective
44 KTable groupBy
45 KGroupedStream _ KGroupedTable Count
46 KGroupedStream _ KGroupedTable Aggregate
47 KGroupedStream _ KGroupedTable Reduce
48 KStream peek
49 KStream Transform _ TransformValues
50 What if I want to write to an external System
51 Summary Diagram
52 What’s Exactly Once
53 Exactly Once in Kafka 0.11
54 What’s the problem with at least once anyway
55 How to do exactly once in Kafka Streams
56 BankBalance – Exercise Overview
57 Kafka Producer Guidance
58 Kafka Producer Solution
59 Kafka Streams Guidance & Hints
60 Kafka Streams Solution
61 Running the BankBalance Application
62 Section Summary
63 What are joins in Kafka Streams
64 Join Constraints and GlobalKTables
65 The different types of joins – Inner Join, Left Join, Outer Join
66 Creating a join with UserEnrich Kafka Streams App
67 Running the Kafka Streams Join application
68 Testing in Kafka Streams
69 Setup your Kafka Streams project
70 Hands-On – Test your WordCount application
71 Congratulations and next steps
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