Book Image

Big Data Analytics with Hadoop 3

By : Sridhar Alla
Book Image

Big Data Analytics with Hadoop 3

By: Sridhar Alla

Overview of this book

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.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
4
Scientific Computing and Big Data Analysis with Python and Hadoop
Index

Cloud deployment models


A Cloud deployment model represents a specific type of Cloud environment, primarily distinguished by ownership, size, and access.

The following sections describe the four common Cloud deployment models:

  • Public Cloud
  • Community Cloud
  • Private Cloud
  • Hybrid Cloud

Public Clouds

A public Cloud is a publicly accessible Cloud environment owned by a third-party Cloud provider. The IT resources on public Clouds are usually provisioned using the previously described Cloud delivery models and are generally offered to Cloud consumers at a cost or are commercialized using other avenues (such as advertisements).

The Cloud provider is responsible for the creation and ongoing maintenance of the public Cloud and its IT resources. Many of the scenarios and architectures explored in upcoming chapters involve public Clouds and the relationship between the providers and consumers of IT resources using public Clouds.

Community Clouds

A community Cloud is similar to a public Cloud except that its access...