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

Using Python to visualize data

Python provides many extensive capabilities of analysis of big data as well as the plotting and visualization of data.


Analyzing and Visualizing Big Data using Python is covered in Chapter 4, Scientific Computing and Big Data Analysis with Python and Hadoop.

Here is one such example of using Python, involving a single column:

d8 = pd.DataFrame(df, columns=['Quantity'])[0:100]

Here, only the first 100 elements are selected to make the graph less crowded and illustrate the example better.

Now, you'll have:

Suppose that you want multiple columns to show up. Look at the following code:

d8 = pd.DataFrame(df, columns=['Quantity', 'UnitPrice'])[0:100]

Just remember that it will not plot qualitative data columns such as Description but only things that can be graphed, such as Quantity and UnitPrice.