Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Building Data Streaming Applications with Apache Kafka
  • Table Of Contents Toc
Building Data Streaming Applications with Apache Kafka

Building Data Streaming Applications with Apache Kafka

By : Singh, Kumar
3.8 (4)
close
close
Building Data Streaming Applications with Apache Kafka

Building Data Streaming Applications with Apache Kafka

3.8 (4)
By: Singh, Kumar

Overview of this book

Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it.
Table of Contents (14 chapters)
close
close

Message processing semantics

Exactly-once delivery is the holy grail of streaming analytics. Having duplicates of events processed in a streaming job is inconvenient and often undesirable, depending on the nature of the application. For example, if billing applications miss an event or process an event twice, they could lose revenue or overcharge customers. Guaranteeing that such scenarios never happen is difficult; any project seeking such a property will need to make some choices with respect to availability and consistency. One main difficulty stems from the fact that a streaming pipeline might have multiple stages, and exactly-once delivery needs to happen at each stage. Another difficulty is that intermediate computations could potentially affect the final computation. Once results are exposed, retracting them causes problems.

It is useful to provide exactly-once guarantees...

Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Building Data Streaming Applications with Apache Kafka
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon