Video description
Learn the Kafka Streams API with hands-on examples. Learn exactly once, build and deploy apps with Java 8
About This Video
- The easiest way to transform your data using the High Level DSL
- Exactly once semantics support out of the box!
- Deploy and scale your Kafka Streams application without a cluster!
- Perform aggregations, joins, and any operations you may think of using only a few lines of code!
- Built on top of Kafka, for fault tolerance, scalability and resiliency
In Detail
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!
Who this book is for
Developers and devops who would like to learn how to write, package, deploy and run a Kafka Streams applications. Architects who would like to understand how Kafka Streams works and its position in the Kafka-centered data pipeline and enterprise architecture. People who fully understand the basics of Kafka. Java 8 and Scala developers only
Publisher resources
Table of contents
- Chapter 1 : Kafka Streams - First Look
-
Chapter 2 : End to End Kafka Streams Application - Word Count
- Section Objective
- Kafka Streams Core Concepts
- Environment and IDE Setup: Java 8, Maven, IntelliJ IDEA
- Starter Project Setup
- Kafka Streams Application Properties
- Java 8 Lambda Functions - quick overview
- Word Count Application Topology
- Printing the Kafka Streams Topology
- Kafka Streams Graceful Shutdown
- Running Application from IntelliJ IDEA
- Debugging Application from IntelliJ IDEA
- Internal Topics for our Kafka Streams Application
- Packaging the application as Fat Jar Running the Fat Jar
- Scaling our Application
- Section Wrap-Up
-
Chapter 3 : KStreams and KTables Simple Operations (Stateless)
- Section Objectives
- KStream KTables
- Stateless vs Stateful Operations
- MapValues / Map
- Filter / FilterNot
- FlatMapValues / FlatMap
- Branch
- SelectKey
- Reading from Kafka
- Writing to Kafka
- Streams Marked for Re-Partition
- Refresher on Log Compaction
- KStream and KTables Duality
- Transforming a KTable to a KStream
- Transforming a KStream to a KTable
- Section Summary
- Chapter 4 : Practice Exercise – FavouriteColour
- Chapter 5 : KStreams and KTables Advanced Operations (Stateful)
- Chapter 6 : Exactly Once Semantics – Theory
- Chapter 7 : Exactly Once Semantics - Practice Exercise – BankBalance
- Chapter 8 : Joins - KStream to GlobalKTable example
- Chapter 9 : Testing your Kafka Streams Application
- Chapter 10 : Next Steps
Product information
- Title: Apache Kafka Series - Kafka Streams for Data Processing
- Author(s):
- Release date: May 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789343496
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