The author of the "Complete Guide to Open Source Big Data Stack" book creates a private cloud and installs Apache Brooklyn, Mesos, Kafka, and Zeppelin. Each chapter introduces a different piece of the big data stack, with examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. The book is for developers, architects, IT project managers, database administrators, and others interested in Hadoop or big data, and those experiencing problems with data size.

Format: Paperback / softback
Length: 365 pages
Publication date: 19 January 2018
Publisher: APress

Complete Guide to Open Source Big Data Stack

In this comprehensive guide, you will embark on a journey to create a robust and scalable open-source big data stack using cutting-edge technologies. You will utilize the power of Apache, a leading open-source software foundation, to assemble a comprehensive solution that caters to your big data needs.

To begin, you will set up a private cloud infrastructure using Apache CloudStack, a powerful cloud management platform. This will provide you with the necessary resources and flexibility to deploy and manage your big data applications.

Next, you will delve into the core components of the open-source big data stack. You will start with Apache Brooklyn, a versatile platform for deploying and managing applications in a distributed environment. You will explore its features, such as containerization, service discovery, and orchestration, and learn how to deploy and manage applications on a cluster.

Continuing the journey, you will delve into Apache Mesos, a distributed task scheduler that enables efficient resource allocation and workload management across clusters. You will learn how to install Mesos, configure it, and deploy applications using frameworks like Apache Spark and Apache Hadoop.

Furthermore, you will explore Apache Kafka, a high-performance streaming platform that enables real-time data processing and storage. You will learn how to set up Kafka clusters, create topics, and consume and produce data from applications.

To enhance your big data capabilities, you will also examine Apache Zeppelin, an interactive data visualization and analytics platform. You will learn how to install Zeppelin, create interactive notebooks, and perform data analysis and visualization using powerful libraries like Apache Spark and Matplotlib.

Throughout the guide, you will learn by example, step by step, and chapter by chapter, as a real big data stack is created. The book focuses on Apache-based systems and provides detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more.

Whether you are a developer, architect, IT project manager, database administrator, or anyone else charged with developing or supporting a big data system, this guide is designed to help you navigate the complexities of open-source big data technologies. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.

By the end of this guide, you will have gained a deep understanding of the open-source big data stack and the tools and technologies that power it. You will be equipped with the knowledge and skills to build and deploy scalable and reliable big data solutions that can meet the demands of your organization.

So, why wait? Start your journey to open-source big data mastery today and unlock the full potential of your data!

Weight: 742g
Dimension: 179 x 254 x 22 (mm)
ISBN-13: 9781484221488
Edition number: 1st ed.