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Kafka Streams in Action (Manning, 2017, MEAP Edition)
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MEAP Edition, Manning Early Access Program, Kafka Streams in Action, Version 4 PART 1: GETTING STARTED WITH KAFKA STREAMS PART 2: KAFKA STREAMS DEVELOPMENT PART 3: ADMINISTERING KAFKA STREAMS PART 4: ADVANCED CONCEPTS WITH KAFKA STREAMS
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MEAPEdition
ManningEarlyAccessProgram
KafkaStreamsinAction
Version4
Copyright2017ManningPublications
FormoreinformationonthisandotherManningtitlesgoto
www.manning.com
©Manning Publications Co. We welcome reader comments about anything in the manuscript - other than typos and
other simple mistakes. These will be cleaned up during production of the book by copyeditors and proofreaders.
https://forums.manning.com/forums/kafka-streams-in-action
Welcome
After several years of subscribing to Manning’s MEAPs, I’m excited now to welcome you
to the MEAP for my own book, Kafka Streams in Action!
These days, you can’t afford to ignore the hot topics of Big Data, streaming data, and
distributed programming. We’re at a point where stream processing has become an
increasingly important factor for businesses looking to harness the power from data
generated in real time. With 13 years in software development, I’ve spent the last six years
working exclusively on the back end, leading ingest teams, and handling large volumes of
data daily. Kafka is what I use to improve the data flow downstream, and Kafka Streams
makes it seamless to implement stream processing on the data flowing into Kafka. So, while
Kafka is a de facto standard in the industry for feeding and exporting data, Kafka Streams
represents a powerful new feature.
In this book, I will teach you Kafka Streams, so you, too, can add stream processing to
your data flow.
Please remember, these chapters are still works in progress, and will definitely get more
polished by the time the book is complete. And feel free to join me on the Kafka Streams in
Action Author Forum
at Manning.com, to ask questions, offer feedback, and participate in
the conversation to shape this book.
—Bill Bejeck
©Manning Publications Co. We welcome reader comments about anything in the manuscript - other than typos and
other simple mistakes. These will be cleaned up during production of the book by copyeditors and proofreaders.
https://forums.manning.com/forums/kafka-streams-in-action
brief contents
PART 1: GETTING STARTED WITH KAFKA STREAMS
1 Welcome to Kafka Streams
2 Kafka Quickly
PART 2: KAFKA STREAMS DEVELOPMENT
3 Developing Kafka Streams
4 Streams and State
5 The KTable API
6 The Processor API
PART 3: ADMINISTERING KAFKA STREAMS
7 Performance Monitoring
8 Testing
PART 4: ADVANCED CONCEPTS WITH KAFKA STREAMS
9 Advanced Applications with Kafka Streams
10 Comparisons to Other Streaming Frameworks
APPENDIXES
A Transactions – Exactly Once Semantics in Kafka and Kafka Streams
B Configuration – How to Configure Your Kafka Streams Application
©Manning Publications Co. We welcome reader comments about anything in the manuscript - other than typos and
other simple mistakes. These will be cleaned up during production of the book by copyeditors and proofreaders.
https://forums.manning.com/forums/kafka-streams-in-action
1
In this chapter
If you take a look around at the modern programming landscape, it has exploded with
'Big Data' frameworks and technologies. Sure client side development has undergone
transformations of its own and mobile device applications have exploded as well. But no
matter how big the mobile device market gets or how client side technologies evolve,
there is one constant; we need to process more and more data every day. As the amount
of data grows, the need to analyze and leverage the benefit from that data grows at the
same rate.
But having the ability to process large quantities of data in bulk amounts (batch
processing) is not always enough. Increasingly, organizations are finding there is a need
to process data as it is available (stream processing). Kafka Streams, a cutting edge
approach to stream processing, is a library that allows you to perform per-event
processing of records. By per-event processing, I mean the ability to work on data as it
arrives. Per-event processing means you process each single record as soon as it is
available; there is no grouping data together in small batches, no 'micro-batching,'
required.
Welcome to Kafka Streams
The "Big Data" movement and how it changed the programming
landscape
The Need for Stream Processing
How Stream Processing works
Introducing Kafka Streams
What Problems Kafka Streams solves
1.1 The "Big Data" movement and how it changed the programming
landscape
©Manning Publications Co. We welcome reader comments about anything in the manuscript - other than typos and
other simple mistakes. These will be cleaned up during production of the book by copyeditors and proofreaders.
https://forums.manning.com/forums/kafka-streams-in-action
1
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