Packt+ | Advance your knowledge in tech

0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Mastering Spark for Data Science

You're reading from Mastering Spark for Data Science Lightning fast and scalable data science solutions

Product type Paperback

Published in Mar 2017

Publisher Packt

ISBN-13 9781785882142

Length 560 pages

Edition 1st Edition

Tools

Apache Spark

Concepts

Data Science

Authors (5):

David George

Matthew Hallett

Antoine Amend

Andrew Morgan

Albert Bifet

+1 more

View More author details

Table of Contents (15) Chapters

Preface

1. The Big Data Science Ecosystem

2. Data Acquisition FREE CHAPTER

3. Input Formats and Schema

4. Exploratory Data Analysis

5. Spark for Geographic Analysis

6. Scraping Link-Based External Data

7. Building Communities

8. Building a Recommendation System

9. News Dictionary and Real-Time Tagging System

10. Story De-duplication and Mutation

11. Anomaly Detection on Sentiment Analysis

12. TrendCalculus

13. Secure Data

14. Scalable Algorithms

News index dashboard

Since we were able to enrich the content found at input URLs with valuable information, the natural next step is to start visualizing our data. Although the different techniques of Exploratory Data Analysis have been thoroughly discussed within Chapter 4, Exploratory Data Analysis, we believe it is worth wrapping up what we have covered so far using a simple dashboard in Kibana. From around 50,000 articles, we were able to fetch and analyze on January 10-11, we filter any record mentioning David Bowie as a NLP entity and containing the word death. Because all our text content is properly indexed in Elasticsearch, we can pull 209 matching articles with their content in just a few seconds.

Figure 5: News Index Dashboard

We can quickly get the top ten persons mentioned alongside David Bowie, including his stage name Ziggy Stardust, his son Duncan Jones, his former producer Tony Visconti, or the British prime minister David Cameron. Thanks to the GeoLookup service we built...

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 $19.99/month. Cancel anytime

Authors (5)

Morgan

Morgan

Andrew Morgan is a specialist in data strategy and its execution, and has deep experience in the supporting technologies, system architecture, and data science that bring it to life. With over 20 years of experience in the data industry, he has worked designing systems for some of its most prestigious players and their global clients often on large, complex and international projects. In 2013, he founded ByteSumo Ltd, a data science and big data engineering consultancy, and he now works with clients in Europe and the USA. Andrew is an active data scientist, and the inventor of the TrendCalculus algorithm. It was developed as part of his ongoing research project investigating long-range predictions based on machine learning the patterns found in drifting cultural, geopolitical and economic trends. He also sits on the Hadoop Summit EU data science selection committee, and has spoken at many conferences on a variety of data topics. He also enjoys participating in the Data Science and Big Data communities where he lives in London.

See other products by Morgan

Bifet

Bifet

See other products by Bifet

Hallett

Hallett

Matthew Hallett is a Software Engineer and Computer Scientist with over 15 years of industry experience. He is an expert Object Oriented programmer and systems engineer with extensive knowledge of low level programming paradigms and, for the last 8 years, has developed an expertise in Hadoop and distributed programming within mission critical environments, comprising multithousandnode data centres. With consultancy experience in distributed algorithms and the implementation of distributed computing architectures, in a variety of languages, Matthew is currently a Consultant Data Engineer in the Data Science & Engineering team at a top four audit firm.

See other products by Hallett

Amend

Amend

Antoine Amend is a data scientist passionate about big data engineering and scalable computing. The books theme of torturing astronomical amounts of unstructured data to gain new insights mainly comes from his background in theoretical physics. Graduating in 2008 with a Msc. in Astrophysics, he worked for a large consultancy business in Switzerland before discovering the concept of big data at the early stages of Hadoop. He has embraced big data technologies ever since, and is now working as the Head of Data Science for cyber security at Barclays Bank. By combining a scientific approach with core IT skills, Antoine qualified two years running for the Big Data World Championships finals held in Austin TX. He Placed in the top 12 in both 2014 and 2015 edition (over 2000+ competitors) where he additionally won the Innovation Award using the methodologies and technologies explained in this book.

See other products by Amend

George

George

David George is a distinguished distributed computing expert with 15+ years of data systems experience, mainly with globally recognized IT consultancies and brands. Working with core Hadoop technologies since the early days, he has delivered implementations at the largest scale. David always takes a pragmatic approach to software design and values elegance in simplicity. Today he continues to work as a lead engineer, designing scalable applications for financial sector customers with some of the toughest requirements. His latest projects focus on the adoption of advanced AI techniques for increasing levels of automation across knowledge-based industries.

See other products by George

Other recommended products

Related to this chapter

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.

Apache Spark 2.x for Java Developers

Apache Spark 2.x for Java Developers

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.

Jul 2017 11h 40m

Apache Spark 2.x for Java Developers

Apache Spark 2.x for Java Developers

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.

Jul 2017 11h 40m

Apache Spark 2.x for Java Developers

Apache Spark 2.x for Java Developers

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.

Jul 2017 11h 40m

Apache Spark 2.x for Java Developers

Apache Spark 2.x for Java Developers

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.

Jul 2017 11h 40m

Apache Spark 2.x Cookbook

Apache Spark 2.x Cookbook

Apache Spark has become the hottest platform and sought after skill set when it comes to the fields of Big Data, Analytics and Data Science. Apache Spark 2.x comes with series of new improvements in the areas of performance, scalability, operational and production readiness for structured processing of massive datasets. This book brings in a systematic way of getting a practical hands on to using its improved programming APIs, expanded SQL functionalities and implement distributed machine learning applications with Spark ML. Through the course of chapters, you will have explored the power of Spark DataFrames/Datasets, harness MLLib for Data mining, analyze complex problems with iterative or multi-stage Spark scripts and other associated toolsets such as Spark SQL, Spark Streaming and GraphX .

May 2017 9h 48m

Apache Spark 2.x Cookbook

Apache Spark 2.x Cookbook

Apache Spark has become the hottest platform and sought after skill set when it comes to the fields of Big Data, Analytics and Data Science. Apache Spark 2.x comes with series of new improvements in the areas of performance, scalability, operational and production readiness for structured processing of massive datasets. This book brings in a systematic way of getting a practical hands on to using its improved programming APIs, expanded SQL functionalities and implement distributed machine learning applications with Spark ML. Through the course of chapters, you will have explored the power of Spark DataFrames/Datasets, harness MLLib for Data mining, analyze complex problems with iterative or multi-stage Spark scripts and other associated toolsets such as Spark SQL, Spark Streaming and GraphX .

May 2017 9h 48m

Apache Spark 2.x Cookbook

Apache Spark 2.x Cookbook

Apache Spark has become the hottest platform and sought after skill set when it comes to the fields of Big Data, Analytics and Data Science. Apache Spark 2.x comes with series of new improvements in the areas of performance, scalability, operational and production readiness for structured processing of massive datasets. This book brings in a systematic way of getting a practical hands on to using its improved programming APIs, expanded SQL functionalities and implement distributed machine learning applications with Spark ML. Through the course of chapters, you will have explored the power of Spark DataFrames/Datasets, harness MLLib for Data mining, analyze complex problems with iterative or multi-stage Spark scripts and other associated toolsets such as Spark SQL, Spark Streaming and GraphX .

May 2017 9h 48m

Mastering Apache Spark 2.x

Mastering Apache Spark 2.x

Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and more. This book will familiarize you with the newest features in Apache Spark 2.x, and take you through an exciting journey of complex Big Data processing, analytics, streaming analytics as well as advanced machine learning with Apache Spark. During the course of the book, you will leverage different functionalities and modules of Apache Spark such as Spark SQL, Spark MLlib, Spark Streaming, SparkML and more, to build efficient data processing solutions. By the end of this book, you will have all the necessary knowledge to use Apache Spark effectively in your day to day tasks.

Jul 2017 11h 48m

Mastering Apache Spark 2.x

Mastering Apache Spark 2.x

Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and more. This book will familiarize you with the newest features in Apache Spark 2.x, and take you through an exciting journey of complex Big Data processing, analytics, streaming analytics as well as advanced machine learning with Apache Spark. During the course of the book, you will leverage different functionalities and modules of Apache Spark such as Spark SQL, Spark MLlib, Spark Streaming, SparkML and more, to build efficient data processing solutions. By the end of this book, you will have all the necessary knowledge to use Apache Spark effectively in your day to day tasks.

Jul 2017 11h 48m

Learning Apache Spark 2

Learning Apache Spark 2

Apache Spark is one of the most popular Big Data processing frameworks today, delivering speed, accuracy and real-time results – all in one solution. With this book, you will delve into the world of Apache Spark and learn about the new features introduced in Spark 2, along with the architecture and the associated concepts. A comprehensive guide to Apache Spark 2 for beginners, this book covers everything you need to know to get up and running with Big Data processing, machine learning and stream processing with Apache Spark, and allows you to easily understand each of these concepts through real-world examples.

Mar 2017 11h 52m

Learning Apache Spark 2

Learning Apache Spark 2

Apache Spark is one of the most popular Big Data processing frameworks today, delivering speed, accuracy and real-time results – all in one solution. With this book, you will delve into the world of Apache Spark and learn about the new features introduced in Spark 2, along with the architecture and the associated concepts. A comprehensive guide to Apache Spark 2 for beginners, this book covers everything you need to know to get up and running with Big Data processing, machine learning and stream processing with Apache Spark, and allows you to easily understand each of these concepts through real-world examples.

Mar 2017 11h 52m

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

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

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

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

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

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