Book Image

Learning Spark SQL

By : Aurobindo Sarkar
Book Image

Learning Spark SQL

By: Aurobindo Sarkar

Overview of this book

In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introducing machine learning applications


Machine learning, predictive analytics, and related science topics are becoming increasingly popular for solving real-world problems across varied business domains.

Today, machine learning applications are driving mission-critical business decision-making in many organizations. These applications include recommendation engines, targeted advertising, speech recognition, fraud detection, image recognition and categorization, and so on.

In the next section, we will introduce the key components of the Spark ML pipeline API.

Understanding Spark ML pipelines and their components

The machine learning pipeline API was introduced in Apache Spark 1.2. Spark MLlib provides an API for developers to create and execute complex ML workflows. The Pipeline API lets developers quickly assemble distributed machine learning pipelines as the API been standardized applying different learning algorithms. Additionally, we can also combine multiple machine learning algorithms...