Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Big Data Analytics with Hadoop 3
Top Free Python Books 🌠 - 100% Free or Open Source!
  • Title Big Data Analytics with Hadoop 3
  • Author(s) Sridhar Alla
  • Publisher: Packt Publishing; 1st edition (May 31, 2018); eBook (Free Edition)
  • Permission: Free eBook by the Publisher (Packt)
  • Paperback: 482 pages
  • eBook HTML
  • Language: English
  • ISBN-10/ASIN: 1788628845/B07DGKXDLK
  • ISBN-13: 978-1788628846
  • Share This:  

Book Description

Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples.

Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data.

As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.

By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.

  • Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud
  • Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink
  • Exploit big data using Hadoop 3 with real-world examples
About the Authors
  • N/A
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Hadoop Illuminated (Mark Kerzner, et al)

    This book aims to make Hadoop knowledge accessible to a wider audience, not just to the highly technical. It book introduces you to Hadoop and to concepts such as 'MapReduce', etc., which will help you get acquainted with the technology.

  • Hadoop with Python (Zachary Radtka, et al)

    This book takes you through the basic concepts behind Hadoop, MapReduce, Pig, and Spark. Then, through multiple examples and use cases, you'll learn how to work with these technologies by applying various Python tools.

  • Hadoop for Windows Succinctly (Dave Vickers)

    This book provides a thorough guide to using Hadoop directly on Windows operating systems. From a conceptual overview to practical examples, Hadoop for Windows Succinctly is a valuable resource for developers.

  • Hadoop Succinctly (Elton Stoneman)

    This booky explains how Hadoop works, what goes on in the cluster, demonstrates how to move data in and out of Hadoop, and how to query it efficiently. It also walks through a Java MapReduce example, illustrates it in Python and .NET, too.

  • Understanding Big Data: Analytics for Hadoop and Streaming Data

    In this book, the three defining characteristics of Big Data - volume, variety, and velocity, are discussed. Industry use cases are also included in this practical guide, to deliver a robust, secure, highly available, enterprise-class Big Data platform.

  • Knowledge Graphs and Big Data Processing (Valentina Janev, et al)

    Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.

  • Big Data in Context: Legal, Social and Technological Insights

    This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.

  • Modelling and Simulation for Big Data Applications

    Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations.

Book Categories
:
Other Categories
Resources and Links