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Also known as event stream processing (ESP), real-time data streaming, and complex event processing (CEP), stream processing is the continuous processing of real-time data directly as it is produced or received. Kafka Streams is a client library providing organizations with a particularly efficient framework for processing streaming data. It offers a streamlined method for creating applications and microservices that must process data in real-time to be effective. Apache Kafka Stream can be defined as an open-source client library that is used for building applications and micro-services. Here, the input and the output data is stored in Kafka Clusters. It integrates the intelligibility of designing and deploying standard Scala and Java applications with the benefits of Kafka server-side cluster te chnology.
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But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. Book Description: Kafka Streams is a library designed to allow for easy stream processing of data flowing into a Kafka cluster. Stream processing has become one of the biggest needs for companies over the last few years as quick data insight becomes more and more important but current solutions can be complex and large, requiring additional tools to perform lookups and aggregations.
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Why Kafka Streams? There are the following properties that describe the use of Kafka Streams: Kafka Streams are highly scalable as well as elastic in nature. Can be deployed to containers, cloud, bare metals, etc.
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However, in this book, we will be referring it as stream processing. In the next chapter, I will talk about some popular industry use cases of stream processing.
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Kafka Stream’s transformations contain operations such as `filter`, `map`, `flatMap`, etc. and have similarities to functional combinators found in languages such as Scala.
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Every stream task in a Kafka Streams application may embed one or more local state stores that can be accessed via APIs to store and query data required for 20 Jun 2018 In the previous blog we tried a simple Kafka Streams application for of Kafka transactions so far is in this book (ebook available, Chapter 12: 3 Jul 2017 ➇ Kicking off the Kafka Stream thread(s). This is a trivial example, but the code shown here is representative of what you'll see in Kafka Streams a.