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Key benefits

Discover how to convert huge amounts of raw data into meaningful and actionable insights

Use Spark's unified analytics engine for end-to-end analytics, from data preparation to predictive analytics

Perform data ingestion, cleansing, and integration for ML, data analytics, and data visualization

Description

Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework. Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas. By the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems.

Who is this book for?

This book is for practicing data engineers, data scientists, data analysts, and data enthusiasts who are already using data analytics to explore distributed and scalable data analytics. Basic to intermediate knowledge of the disciplines of data engineering, data science, and SQL analytics is expected. General proficiency in using any programming language, especially Python, and working knowledge of performing data analytics using frameworks such as pandas and SQL will help you to get the most out of this book.

What you will learn

Understand the role of distributed computing in the world of big data

Gain an appreciation for Apache Spark as the de facto go-to for big data processing

Scale out your data analytics process using Apache Spark

Build data pipelines using data lakes, and perform data visualization with PySpark and Spark SQL

Leverage the cloud to build truly scalable and real-time data analytics applications

Explore the applications of data science and scalable machine learning with PySpark

Integrate your clean and curated data with BI and SQL analysis tools

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

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DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Machine Learning Engineering with Python

$54.99

Essential PySpark for Scalable Data Analytics

$48.99

$43.99

Total $ 147.97

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Amazon verified reviews

Anirudh Oct 29, 2021

I’ve recently been ramping up on the PySpark. As this was really helpful for me to understand some of the real time topics & knowledge on one of the topic "Building analytical data stores using clouddata lakes". Understanding the challenges on working on Integrating data using data virtualization techniques.I Particularly found the topic Real-time analytics systems architecture and the use cases very useful & the author explains how the traditional of BI moving to AI, advantages Modern advanced analytics and data science tools.

Amazon Verified review

Qiwei Lu Oct 31, 2021

I got this book because I have to use pyspark in databricks at this new project but I only had a vague concept of what is spark before. This book did a good job of explaining all the basic concepts to someone who has never worked with pyspark before. This book does not dig too deep into individual concept or use cases but I have managed to ask the right questions when I face a situation in my new project and that is indeed the goal of this book.

Anjana Oct 29, 2021

Python and Data Science are the concepts where most of the Techies are interested in and when it comes to me, I call myself a beginner with these concepts. This book has thrown light on each and every aspect precisely which is very essential and smooth for the reader to understand. Data Ingestion, Cleansing, Integration, Analytics and ML - The way the Author has elucidated piece by piece is exceptional. This book has helped me upgrade from a beginner to proficient in understanding the concepts and given more courage to dive-in and work on them. I would doubtlessly prescribe this book to each one interested in learning the concepts of Data Engineering, Data Science and Data analytics.

Shiblee Nooman Jan 13, 2022

It was an informative and well written book with plenty of examples. The writer did a great job explaining difficult topics in plain language.Highly recommended!

Ezam Aug 09, 2022

Pyspark is not as well documented online as Python and this book really help me kick off the learning curve

Essential PySpark for Scalable Data Analytics: A beginner's guide to harnessing the power and ease of PySpark 3

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