A practical guide to help you tackle different real-time data
processing and analytics problems using the best tools for each
scenario About This Book * Learn about the various challenges in
real-time data processing and use the right tools to overcome them
* This book covers popular tools and frameworks such as Spark,
Flink, and Apache Storm to solve all your distributed processing
problems * A practical guide filled with examples, tips, and tricks
to help you perform efficient Big Data processing in real-time Who
This Book Is For If you are a Java developer who would like to be
equipped with all the tools required to devise an end-to-end
practical solution on real-time data streaming, then this book is
for you. Basic knowledge of real-time processing would be helpful,
and knowing the fundamentals of Maven, Shell, and Eclipse would be
great. What You Will Learn * Get an introduction to the established
real-time stack * Understand the key integration of all the
components * Get a thorough understanding of the basic building
blocks for real-time solution designing * Garnish the search and
visualization aspects for your real-time solution * Get
conceptually and practically acquainted with real-time analytics *
Be well equipped to apply the knowledge and create your own
solutions In Detail With the rise of Big Data, there is an
increasing need to process large amounts of data continuously, with
a shorter turnaround time. Real-time data processing involves
continuous input, processing and output of data, with the condition
that the time required for processing is as short as possible. This
book covers the majority of the existing and evolving open source
technology stack for real-time processing and analytics. You will
get to know about all the real-time solution aspects, from the
source to the presentation to persistence. Through this practical
book, you'll be equipped with a clear understanding of how to solve
challenges on your own. We'll cover topics such as how to set up
components, basic executions, integrations, advanced use cases,
alerts, and monitoring. You'll be exposed to the popular tools used
in real-time processing today such as Apache Spark, Apache Flink,
and Storm. Finally, you will put your knowledge to practical use by
implementing all of the techniques in the form of a practical,
real-world use case. By the end of this book, you will have a solid
understanding of all the aspects of real-time data processing and
analytics, and will know how to deploy the solutions in production
environments in the best possible manner. Style and Approach In
this practical guide to real-time analytics, each chapter begins
with a basic high-level concept of the topic, followed by a
practical, hands-on implementation of each concept, where you can
see the working and execution of it. The book is written in a DIY
style, with plenty of practical use cases, well-explained code
examples, and relevant screenshots and diagrams.
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