Packt+ | Advance your knowledge in tech

0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Apache Spark 2.x Cookbook

You're reading from Apache Spark 2.x Cookbook Over 70 cloud-ready recipes for distributed Big Data processing and analytics

Product type Paperback

Published in May 2017

Publisher

ISBN-13 9781787127265

Length 294 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Big Data

Author (1):

Rishi Yadav

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Apache Spark FREE CHAPTER

2. Developing Applications with Spark

3. Spark SQL

4. Working with External Data Sources

5. Spark Streaming

6. Getting Started with Machine Learning

7. Supervised Learning with MLlib — Regression

8. Supervised Learning with MLlib — Classification

9. Unsupervised Learning

10. Recommendations Using Collaborative Filtering

11. Graph Processing Using GraphX and GraphFrames

12. Optimizations and Performance Tuning

Understanding the cost function

The cost function or loss function is a very important function in machine learning algorithms. Most algorithms have some form of cost function, and the goal is to minimize this. Parameters, which affect cost functions, such as stepSize, are called hyperparameters; they need to be set by hand. Therefore, understanding the whole concept of the cost function is very important.

In this recipe, we are going to analyze the cost function in linear regression. Linear regression is a simple algorithm to understand, and it will help you understand the role of cost functions for even complex algorithms.

Let's go back to linear regression. The goal is to find the best-fitting line so that the mean square of the error would be minimum. Here, we are referring to an error as the difference between the value as per the best-fitting line and the actual value of the response variable of the training dataset.

For a simple case of a single predicate variable, the best-fitting line...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €18.99/month. Cancel anytime

Authors (1)

Yadav

Yadav

Rishi Yadav has 19 years of experience in designing and developing enterprise applications. He is an open source software expert and advises American companies on big data and public cloud trends. Rishi was honored as one of Silicon Valley's 40 under 40 in 2014. He earned his bachelor's degree from the prestigious Indian Institute of Technology, Delhi, in 1998. About 12 years ago, Rishi started InfoObjects, a company that helps data-driven businesses gain new insights into data. InfoObjects combines the power of open source and big data to solve business challenges for its clients and has a special focus on Apache Spark. The company has been on the Inc. 5000 list of the fastest growing companies for 6 years in a row. InfoObjects has also been named the best place to work in the Bay Area in 2014 and 2015. Rishi is an open source contributor and active blogger. This book is dedicated to my parents, Ganesh and Bhagwati Yadav; I would not be where I am without their unconditional support, trust, and providing me the freedom to choose a path of my own. Special thanks go to my life partner, Anjali, for providing immense support and putting up with my long, arduous hours (yet again).Our 9-year-old son, Vedant, and niece, Kashmira, were the unrelenting force behind keeping me and the book on track. Big thanks to InfoObjects' CTO and my business partner, Sudhir Jangir, for providing valuable feedback and also contributing with recipes on enterprise security, a topic he is passionate about; to our SVP, Bart Hickenlooper, for taking the charge in leading the company to the next level; to Tanmoy Chowdhury and Neeraj Gupta for their valuable advice; to Yogesh Chandani, Animesh Chauhan, and Katie Nelson for running operations skillfully so that I could focus on this book; and to our internal review team (especially Rakesh Chandran) for ironing out the kinks. I would also like to thank Marcel Izumi for, as always, providing creative visuals. I cannot miss thanking our dog, Sparky, for giving me company on my long nights out. Last but not least, special thanks to our valuable clients, partners, and employees, who have made InfoObjects the best place to work at and, needless to say, an immensely successful organization.

See other products by Yadav

Other recommended products

Related to this chapter

Learning Spark SQL

Learning Spark SQL

In the past year, Apache Spark has been increasingly adopted for development of distributed applications. Spark SQL APIs provides 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. Understanding the design and implementation best practices for Spark SQL API based applications before you start your project will help you avoid these problems and ensure that your project is a success. Learning Spark SQL gives an insight into the engineering practices used to design and build real-world Spark-based applications. The hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL.

Sep 2017 15h 4m

Learning Spark SQL

Learning Spark SQL

In the past year, Apache Spark has been increasingly adopted for development of distributed applications. Spark SQL APIs provides 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. Understanding the design and implementation best practices for Spark SQL API based applications before you start your project will help you avoid these problems and ensure that your project is a success. Learning Spark SQL gives an insight into the engineering practices used to design and build real-world Spark-based applications. The hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL.

Sep 2017 15h 4m

Learning Spark SQL

Learning Spark SQL

In the past year, Apache Spark has been increasingly adopted for development of distributed applications. Spark SQL APIs provides 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. Understanding the design and implementation best practices for Spark SQL API based applications before you start your project will help you avoid these problems and ensure that your project is a success. Learning Spark SQL gives an insight into the engineering practices used to design and build real-world Spark-based applications. The hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL.

Sep 2017 15h 4m

Learning Spark SQL

Learning Spark SQL

In the past year, Apache Spark has been increasingly adopted for development of distributed applications. Spark SQL APIs provides 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. Understanding the design and implementation best practices for Spark SQL API based applications before you start your project will help you avoid these problems and ensure that your project is a success. Learning Spark SQL gives an insight into the engineering practices used to design and build real-world Spark-based applications. The hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL.

Sep 2017 15h 4m

Apache Spark Quick Start Guide

Apache Spark Quick Start Guide

Apache Spark is a ?exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases.

Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala

This book will help you perform effective data analysis with Scala using practical examples. You will come across different challenges and their effective solutions for a variety of data processing tasks - be it data exploration, data manipulation, or real-time data analysis using Apache Spark.

May 2019 9h 56m

Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala

This book will help you perform effective data analysis with Scala using practical examples. You will come across different challenges and their effective solutions for a variety of data processing tasks - be it data exploration, data manipulation, or real-time data analysis using Apache Spark.

May 2019 9h 56m

Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala

This book will help you perform effective data analysis with Scala using practical examples. You will come across different challenges and their effective solutions for a variety of data processing tasks - be it data exploration, data manipulation, or real-time data analysis using Apache Spark.

May 2019 9h 56m

Scala and Spark for Big Data Analytics

Scala and Spark for Big Data Analytics

Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you'll learn how to leverage the power of both Scala and Spark to make sense of big data.

Jul 2017 26h 32m

Scala and Spark for Big Data Analytics

Scala and Spark for Big Data Analytics

Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you'll learn how to leverage the power of both Scala and Spark to make sense of big data.

Jul 2017 26h 32m

Scala and Spark for Big Data Analytics

Scala and Spark for Big Data Analytics

Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you'll learn how to leverage the power of both Scala and Spark to make sense of big data.

Jul 2017 26h 32m

Scala and Spark for Big Data Analytics

Scala and Spark for Big Data Analytics

Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you'll learn how to leverage the power of both Scala and Spark to make sense of big data.

Jul 2017 26h 32m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.