Practical real-time data processing and analytics: distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka
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 framework...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2017
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781787281202/?ar |
| Zusammenfassung: | 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 dep ... |
| Beschreibung: | Online resource; title from title page (Safari, viewed October 31, 2017) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 1787289869 9781787289864 9781787281202 |
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| spelling | Saxena, Shilpi VerfasserIn aut Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka Shilpi Saxena, Saurabh Gupta Birmingham, UK Packt Publishing 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title page (Safari, viewed October 31, 2017) 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 dep ... Spark (Electronic resource : Apache Software Foundation) Storm (Electronic resource) Big data Data mining Electronic data processing Distributed processing Management Données volumineuses Exploration de données (Informatique) Electronic data processing ; Distributed processing ; Management Gupta, Saurabh VerfasserIn aut |
| spellingShingle | Saxena, Shilpi Gupta, Saurabh Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka Spark (Electronic resource : Apache Software Foundation) Storm (Electronic resource) Big data Data mining Electronic data processing Distributed processing Management Données volumineuses Exploration de données (Informatique) Electronic data processing ; Distributed processing ; Management |
| title | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka |
| title_auth | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka |
| title_exact_search | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka |
| title_full | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka Shilpi Saxena, Saurabh Gupta |
| title_fullStr | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka Shilpi Saxena, Saurabh Gupta |
| title_full_unstemmed | Practical real-time data processing and analytics distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka Shilpi Saxena, Saurabh Gupta |
| title_short | Practical real-time data processing and analytics |
| title_sort | practical real time data processing and analytics distributed computing and event processing using apache spark flink storm and kafka |
| title_sub | distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka |
| topic | Spark (Electronic resource : Apache Software Foundation) Storm (Electronic resource) Big data Data mining Electronic data processing Distributed processing Management Données volumineuses Exploration de données (Informatique) Electronic data processing ; Distributed processing ; Management |
| topic_facet | Spark (Electronic resource : Apache Software Foundation) Storm (Electronic resource) Big data Data mining Electronic data processing Distributed processing Management Données volumineuses Exploration de données (Informatique) Electronic data processing ; Distributed processing ; Management |
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