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
Scientific Computing and Big Data Analysis with Python and Hadoop

Cloud delivery models

A Cloud delivery model represents a specific, pre-packaged combination of IT resources offered by a Cloud provider. Three common Cloud delivery models have become widely established and formalized:

  • IaaS
  • PaaS
  • SaaS

Infrastructure as a Service

The IaaS delivery model represents a self-contained IT environment that comprises infrastructure-centric IT resources that can be accessed and managed using Cloud service-based interfaces and tools. This environment can include hardware, network, connectivity, operating systems, and other raw IT resources. In contrast to traditional hosting or outsourcing environments, with IaaS, IT resources are usually virtualized and packaged into bundles that simplify runtime scaling and customization of the infrastructure.

The general purpose of an IaaS environment is to provide Cloud consumers with a high level of control and responsibility over its configuration and utilization. The IT resources provided by IaaS are generally not preconfigured,...