Real Time Streaming With Apache Kafka Spark And Storm
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Real Time Streaming With Apache Kafka Spark And Storm
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Author : Brindha Priyadarshini Jeyaraman
language : en
Publisher: BPB Publications
Release Date : 2021-08-20
Real Time Streaming With Apache Kafka Spark And Storm written by Brindha Priyadarshini Jeyaraman and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-20 with Computers categories.
Build a platform using Apache Kafka, Spark, and Storm to generate real-time data insights and view them through Dashboards. KEY FEATURES ● Extensive practical demonstration of Apache Kafka concepts, including producer and consumer examples. ● Includes graphical examples and explanations of implementing Kafka Producer and Kafka Consumer commands and methods. ● Covers integration and implementation of Spark-Kafka and Kafka-Storm architectures. DESCRIPTION Real-Time Streaming with Apache Kafka, Spark, and Storm is a book that provides an overview of the real-time streaming concepts and architectures of Apache Kafka, Storm, and Spark. The readers will learn how to build systems that can process data streams in real time using these technologies. They will be able to process a large amount of real-time data and perform analytics or generate insights as a result of this. The architecture of Kafka and its various components are described in detail. A Kafka Cluster installation and configuration will be demonstrated. The Kafka publisher-subscriber system will be implemented in the Eclipse IDE using the Command Line and Java. The book discusses the architecture of Apache Storm, the concepts of Spout and Bolt, as well as their applications in a Transaction Alert System. It also describes Spark's core concepts, applications, and the use of Spark to implement a microservice. To learn about the process of integrating Kafka and Storm, two approaches to Spark and Kafka integration will be discussed. This book will assist a software engineer to transition to a Big Data engineer and Big Data architect by providing knowledge of big data processing and the architectures of Kafka, Storm, and Spark Streaming. WHAT YOU WILL LEARN ● Creation of Kafka producers, consumers, and brokers using command line. ● End-to-end implementation of Kafka messaging system with Java in Eclipse. ● Perform installation and creation of a Storm Cluster and execute Storm Management commands. ● Implement Spouts, Bolts and a Topology in Storm for Transaction alert application system. ● Perform the implementation of a microservice using Spark in Scala IDE. ● Learn about the various approaches of integrating Kafka and Spark. ● Perform integration of Kafka and Storm using Java in the Eclipse IDE. WHO THIS BOOK IS FOR This book is intended for Software Developers, Data Scientists, and Big Data Architects who want to build software systems to process data streams in real time. To understand the concepts in this book, knowledge of any programming language such as Java, Python, etc. is needed. TABLE OF CONTENTS 1. Introduction to Kafka 2. Installing Kafka 3. Kafka Messaging 4. Kafka Producers 5. Kafka Consumers 6. Introduction to Storm 7. Installation and Configuration 8. Spouts and Bolts 9. Introduction to Spark 10. Spark Streaming 11. Kafka Integration with Storm 12. Kafka Integration with Spark
Stream Processing With Apache Spark
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Author : Gerard Maas
language : en
Publisher: O'Reilly Media
Release Date : 2019-06-05
Stream Processing With Apache Spark written by Gerard Maas and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with Computers categories.
Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams
Mastering Apache Storm
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Author : Ankit Jain
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-08-16
Mastering Apache Storm written by Ankit Jain and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-16 with Computers categories.
Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn Understand the core concepts of Apache Storm and real-time processing Follow the steps to deploy multiple nodes of Storm Cluster Create Trident topologies to support various message-processing semantics Make your cluster sharing effective using Storm scheduling Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You'll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we'll introduce you to Trident and you'll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.
Streaming Data
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Author : Andrew Psaltis
language : en
Publisher: Simon and Schuster
Release Date : 2017-05-31
Streaming Data written by Andrew Psaltis and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-31 with Computers categories.
Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Table of Contents PART 1 - A NEW HOLISTIC APPROACH Introducing streaming data Getting data from clients: data ingestion Transporting the data from collection tier: decoupling the data pipeline Analyzing streaming data Algorithms for data analysis Storing the analyzed or collected data Making the data available Consumer device capabilities and limitations accessing the data PART 2 - TAKING IT REAL WORLD Analyzing Meetup RSVPs in real time
Practical Real Time Data Processing And Analytics
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Author : Shilpi Saxena
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-28
Practical Real Time Data Processing And Analytics written by Shilpi Saxena and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-28 with Computers categories.
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.
Building Data Streaming Applications With Apache Kafka
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Author : Manish Kumar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-08-18
Building Data Streaming Applications With Apache Kafka written by Manish Kumar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-18 with Computers categories.
Design and administer fast, reliable enterprise messaging systems with Apache Kafka About This Book Build efficient real-time streaming applications in Apache Kafka to process data streams of data Master the core Kafka APIs to set up Apache Kafka clusters and start writing message producers and consumers A comprehensive guide to help you get a solid grasp of the Apache Kafka concepts in Apache Kafka with pracitcalpractical examples Who This Book Is For If you want to learn how to use Apache Kafka and the different tools in the Kafka ecosystem in the easiest possible manner, this book is for you. Some programming experience with Java is required to get the most out of this book What You Will Learn Learn the basics of Apache Kafka from scratch Use the basic building blocks of a streaming application Design effective streaming applications with Kafka using Spark, Storm &, and Heron Understand the importance of a low -latency , high- throughput, and fault-tolerant messaging system Make effective capacity planning while deploying your Kafka Application Understand and implement the best security practices In Detail 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. Style and approach A step-by –step, comprehensive guide filled with practical and real- world examples
Streaming Architecture
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Author : Ted Dunning
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-05-10
Streaming Architecture written by Ted Dunning and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-10 with Computers categories.
More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases. Ideal for developers and non-technical people alike, this book describes: Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layer New messaging technologies, including Apache Kafka and MapR Streams, with links to sample code Technology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache Apex How stream-based architectures are helpful to support microservices Specific use cases such as fraud detection and geo-distributed data streams Ted Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning. Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman.
Learning Storm
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Author : Ankit Jain
language : en
Publisher:
Release Date : 2014-08-15
Learning Storm written by Ankit Jain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-15 with Computers categories.
If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications.
Kafka Streams In Action
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Author : Bill Bejeck
language : en
Publisher: Simon and Schuster
Release Date : 2018-08-29
Kafka Streams In Action written by Bill Bejeck and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-29 with Computers categories.
Summary Kafka Streams in Action teaches you everything you need to know to implement stream processing on data flowing into your Kafka platform, allowing you to focus on getting more from your data without sacrificing time or effort. Foreword by Neha Narkhede, Cocreator of Apache Kafka Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Not all stream-based applications require a dedicated processing cluster. The lightweight Kafka Streams library provides exactly the power and simplicity you need for message handling in microservices and real-time event processing. With the Kafka Streams API, you filter and transform data streams with just Kafka and your application. About the Book Kafka Streams in Action teaches you to implement stream processing within the Kafka platform. In this easy-to-follow book, you'll explore real-world examples to collect, transform, and aggregate data, work with multiple processors, and handle real-time events. You'll even dive into streaming SQL with KSQL! Practical to the very end, it finishes with testing and operational aspects, such as monitoring and debugging. What's inside Using the KStreams API Filtering, transforming, and splitting data Working with the Processor API Integrating with external systems About the Reader Assumes some experience with distributed systems. No knowledge of Kafka or streaming applications required. About the Author Bill Bejeck is a Kafka Streams contributor and Confluent engineer with over 15 years of software development experience. Table of Contents PART 1 - GETTING STARTED WITH KAFKA STREAMS Welcome to Kafka Streams Kafka quicklyPART 2 - KAFKA STREAMS DEVELOPMENT Developing Kafka Streams Streams and state The KTable API The Processor APIPART 3 - ADMINISTERING KAFKA STREAMS Monitoring and performance Testing a Kafka Streams applicationPART 4 - ADVANCED CONCEPTS WITH KAFKA STREAMS Advanced applications with Kafka StreamsAPPENDIXES Appendix A - Additional configuration information Appendix B - Exactly once semantics
Kafka The Definitive Guide
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Author : Neha Narkhede
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-08-31
Kafka The Definitive Guide written by Neha Narkhede and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-31 with Computers categories.
Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems