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

Goals and benefits

Similar to wholesalers, public Cloud providers base their business model on mass acquisition of IT resources, which are made available to Cloud consumers for attractive prices. This helps organizations to access powerful infrastructure without any infrastructure costs.

The most common economic rationale for investing in Cloud-based IT resources is to reduce initial IT investments, such as hardware, software purchases, and ownership costs. A cloud's measured usage characteristic represents a feature set that allows measured operational expenditures (directly related to business performance) to replace anticipated capital expenditures. This is also referred to as proportional cost.

The reduction of costs allow enterprises to start small, to increase IT resource allocation as needed. Moreover, lower initial expenses allow for capital to be redirected to core business investments. Opportunities to decrease costs are derived from the deployment and operation of large-scale data...