Book Image

Hands-On Data Analysis with Scala

By : Rajesh Gupta
Book Image

Hands-On Data Analysis with Scala

By: Rajesh Gupta

Overview of this book

Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights
Table of Contents (14 chapters)
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Section 1: Scala and Data Analysis Life Cycle
Section 2: Advanced Data Analysis and Machine Learning
Section 3: Real-Time Data Analysis and Scalability

Spark Datasets and DataFrames

In the previous section, we looked at Spark's core functionality using RDDs. RDDs are powerful constructs; however, there are still some low-level details that a Spark user has to understand and master before making use of it. Spark's Datasets and DataFrame constructs provide higher level APIs for working with data.

Spark's Dataset brings a declarative style of programming along with the functional programming style of RDD. Structured Query Language (SQL) is a very popular declarative language, and is extremely popular among people who do not have a strong background in functional programming. The Spark DataFrame is a special type of dataset that provides the concepts of the row and column, as seen in the tradition relational database (RDBS) work.

Let's explore the example we used earlier using RDD. We will use the dataset and...