Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Learning PySpark

You're reading from Learning PySpark Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781786463708

Length 274 pages

Edition 1st Edition

Languages

Python

Tools

Apache Spark

Concepts

Data Processing

Authors (2):

Denny Lee

Tomasz Drabas

View More author details

Table of Contents (13) Chapters

Preface

1. Understanding Spark

2. Resilient Distributed Datasets FREE CHAPTER

3. DataFrames

4. Prepare Data for Modeling

5. Introducing MLlib

6. Introducing the ML Package

7. GraphFrames

8. TensorFrames

9. Polyglot Persistence with Blaze

10. Structured Streaming

11. Packaging Spark Applications

Index

A quick primer on global aggregations

As noted in the previous section, so far, our script has performed a point in time streaming word count. The following diagram denotes the lines DStream and its micro-batches as per how our script had executed in the previous section:

A quick primer on global aggregations

At the 1 second mark, our Python Spark Streaming script returned the value of {(blue, 5), (green, 3)}, at the 2 second mark it returned {(gohawks, 1)}, and at the 4 second mark, it returned {(green, 2)}. But what if you had wanted the aggregate word count over a specific time window?

The following figure represents us calculating a stateful aggregation:

A quick primer on global aggregations

In this case, we have a time window between 0-5 seconds. Note, that in our script we have not got the specified time window: each second, we calculate the cumulative sum of the words. Therefore, at the 2 second mark, the output is not just the green and blue from the 1 second mark, but it also includes the gohawks from the 2 second mark: {(blue, 5), (green, 3), (gohawks, 1...

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 (2)

Drabas

Drabas

Tomasz Drabas is a Data Scientist working for Microsoft and currently residing in the Seattle area. He has over 12 years' international experience in data analytics and data science in numerous fields: advanced technology, airlines, telecommunications, finance, and consulting. Tomasz started his career in 2003 with LOT Polish Airlines in Warsaw, Poland while finishing his Master's degree in strategy management. In 2007, he moved to Sydney to pursue a doctoral degree in operations research at the University of New South Wales, School of Aviation; his research crossed boundaries between discrete choice modeling and airline operations research. During his time in Sydney, he worked as a Data Analyst for Beyond Analysis Australia and as a Senior Data Analyst/Data Scientist for Vodafone Hutchison Australia among others. He has also published scientific papers, attended international conferences, and served as a reviewer for scientific journals. In 2015 he relocated to Seattle to begin his work for Microsoft. While there, he has worked on numerous projects involving solving problems in high-dimensional feature space.

See other products by Drabas

Lee

Lee

Joanna Lee has more than 8 years of experience in game development. She has designed and programmed various video games. She first started working with Unreals game engine in 2005 and is very excited to be able to author a book about the newest Unreal Engine 4. She has also worked with many other engines as well as reviewed books and videos on Cry Engine 4.

See other products by Lee

Other recommended products

Related to this chapter

PySpark Cookbook

PySpark Cookbook

This cookbook presents recipes on leveraging the power of Python and putting it to use in the Apache Spark ecosystem. By the end of this book, you will be able to solve any problem associated with building effective, data-intensive applications and performing machine learning and structured streaming using PySpark.

Jun 2018 11h 0m

PySpark Cookbook

PySpark Cookbook

This cookbook presents recipes on leveraging the power of Python and putting it to use in the Apache Spark ecosystem. By the end of this book, you will be able to solve any problem associated with building effective, data-intensive applications and performing machine learning and structured streaming using PySpark.

Jun 2018 11h 0m

PySpark Cookbook

PySpark Cookbook

This cookbook presents recipes on leveraging the power of Python and putting it to use in the Apache Spark ecosystem. By the end of this book, you will be able to solve any problem associated with building effective, data-intensive applications and performing machine learning and structured streaming using PySpark.

Jun 2018 11h 0m

Big Data Processing with Apache Spark

Big Data Processing with Apache Spark

Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This book shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You'll learn all about the core concepts and tools within the Spark ecosystem, like Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.

Oct 2018 4h 44m

Big Data Processing with Apache Spark

Big Data Processing with Apache Spark

Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This book shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You'll learn all about the core concepts and tools within the Spark ecosystem, like Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.

Oct 2018 4h 44m

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.

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

Hands-On Big Data Analytics with PySpark

Hands-On Big Data Analytics with PySpark

In this book, you'll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.

Hands-On Big Data Analytics with PySpark

Hands-On Big Data Analytics with PySpark

In this book, you'll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.

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