BPB Online LLP
Real-Time Streaming with Apache Kafka, Spark, and Storm
Real-Time Streaming with Apache Kafka, Spark, and Storm
US$ 19.95
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Description
Contents
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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.
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
About the Authors
Brindha Priyadarshini Jeyaraman has more than 12+ years of work experience in Software Development and building Data analytics systems. She has completed her M.Tech in Knowledge Engineering with a gold medal from the National University of Singapore. She is an expert in understanding business problems, designing, and implementing solutions using Machine Learning. She has a strong software development background with extensive experience in implementing data analytics systems. She has worked on several Data Science projects in Transportation, E-commerce, Healthcare, Insurance, Banking and Finance Domains. She has completed her SCJP and SCWCD certifications.

LinkedIn Profile: https://www.linkedin.com/in/brindha-jeyaraman-75347922/

Language
English
ISBN
9789390684595
Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Errata
Table of Contents
1. Introduction to Kafka
Introduction
Structure
Objectives
Introduction to Apache Kafka
Kafka versus traditional message queues
Kafka architecture: producer, consumer, and broker
Kafka architecture: topics and partitions
Core API of Kafka
Advantages of using Kafka
Applications using Kafka
Conclusion
Questions
Answers
2. Installing Kafka
Introduction
Structure
Objectives
Installing JDK
Installing Zookeeper
Running Zookeeper
Configurable parameters in Zookeeper
Kafka installation
Running the Kafka server
Stopping the Kafka server
Conclusion
Questions
3. Kafka Messaging
Introduction
Structure
Objectives
Components in messaging
Kafka brokers and Kafka partitions
Kafa failover
Creation of a Kafka topic
Deleting a Kafka topic
Send and receive messages through a command line
Creating a producer
Creating a consumer
Creation of multiple brokers
Installing and using Eclipse and Maven
Installing IntelliJ IDE
Conclusion
Questions
Answers
4. Kafka Producers
Introduction
Structure
Objectives
API for a Kafka producer
Producer implementation in Java
Understanding the implementation of producer
Executing the producer
Three ways to send a Kafka message
Types of acknowledgments
Applications of a Kafka producer
Conclusion
Questions
Answers
5. Kafka Consumers
Introduction
Structure
Objectives
Kafka consumer
Consumer groups
Group coordination protocol
API for Kafka consumer
Consumer implementation in Java
Executing the consumer
Conclusion
Questions
6. Introduction to Storm
Introduction
Structure
Objectives
Introduction to Apache Storm
Comparison of Kafka and Storm
Comparison of Hadoop and Storm
Core components of Storm
Apache Storm architecture
Benefits of Storm
Applications of Storm
Conclusion
Questions
Answers
7. Installation and Configuration of Storm
Introduction
Structure
Objectives
Pre-requisites for Apache Storm
Storm Framework Installation
Set up a Storm Cluster
Storm Management Commands
Conclusion
Questions
Answers
8. Spouts and Bolts
Introduction
Structure
Objectives
Transaction "Alert Application"
Creating the Maven project
Spout Implementation
Bolt Implementation
Creating the Topology
Executing the Application
Conclusion
Questions
9. Introduction to Spark
Introduction
Structure
Objectives
Introduction to Apache Spark
Comparison of Spark and Hadoop
Comparison of Spark and Storm
Comparison of Spark and Kafka
Core concepts
Benefits and features of Spark
Spark Architecture
Applications of Spark
Conclusion
Questions
10. Spark Streaming
Introduction
Structure
Objectives
Core Concepts of Spark streaming
Execution of Spark Shell commands
Implementation of Spark using Eclipse
Implementing Microservice
Conclusion
Questions
Answers
11. Kafka Integration with Spark
Introduction
Structure
Objectives
Kafka and Spark integration
Approaches for integration
Structured Streaming integration of Kafka and Spark
Implementation of Kafka and Spark streaming
Conclusion
Questions
Answers
Key terms
12. Kafka Integration with Storm
Introduction
Structure
Objectives
Introduction to Kafka-Storm Integration
Creating a Maven project
Dependencies for Kafka and Storm
Implementation of Bolt
Creating the Topology
Executing the integration flow
Conclusion
Questions
Answers
Index
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