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Big Data Analytics with Java

You're reading from   Big Data Analytics with Java Data analysis, visualization & machine learning techniques

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787288980
Length 418 pages
Edition 1st Edition
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Author (1):
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RAJAT MEHTA RAJAT MEHTA
Author Profile Icon RAJAT MEHTA
RAJAT MEHTA
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Table of Contents (15) Chapters Close

Preface 1. Big Data Analytics with Java FREE CHAPTER 2. First Steps in Data Analysis 3. Data Visualization 4. Basics of Machine Learning 5. Regression on Big Data 6. Naive Bayes and Sentiment Analysis 7. Decision Trees 8. Ensembling on Big Data 9. Recommendation Systems 10. Clustering and Customer Segmentation on Big Data 11. Massive Graphs on Big Data 12. Real-Time Analytics on Big Data 13. Deep Learning Using Big Data Index

Basic analysis of data with Spark SQL

Spark SQL is a spark module for structured data processing. Almost all the developers know SQL. Spark SQL provides an SQL interface to your Spark data (RDDs). Using Spark SQL you can fire SQL queries or SQL-like queries on your big data set and fetch data in objects called dataframes.

A dataframe is like a relational database table. It has columns in it and we can apply functions to these columns such as groupBy, and so on. It is very easy to learn and use.

In the next section, we will cover a few examples on how we can use the dataframe and run regular analysis tasks.

Building SparkConf and context

This is just boilerplate code and is the entry point for the usage of our Spark SQL code. Every spark program will start with this boiler plate code for initialization. In this code we build the Spark configuration and then apply the configuration parameters (like application name and master location) and also build the SparkSession object. This SparkSession...

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