PySpark for Beginners: Take your first steps in developing large-scale distributed data processing applications using Apache Spark and Python

Drabas

€103.99

VideoJun 20181hr 34mins1st Edition

Drabas

€103.99

VideoJun 20181hr 34mins1st Edition

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Key benefits

Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0.
Develop and deploy efficient, scalable real-time Spark solutions.
Take your understanding of using Spark with Python to the next level with this jump start guide.

Description

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This course will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this course, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/PySpark-for-Beginners

Who is this book for?

If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this course is for you. A firm understanding of Python is expected to get the best out of the book. Familiarity with Spark would be useful, but is not mandatory.

What you will learn

Learn about Apache Spark and the Spark 2.0 architecture
Build and interact with Spark DataFrames using Spark SQL
Read, transform, and understand data and use it to train machine learning models
Build machine learning models with MLlib and ML

Product Details

Publication date, Length, Edition, Language, ISBN-13

Last updated date :Apr 11, 2025

Publication date :Jun 28, 2018

Length:1hr 34mins

Edition :1st

Language :English

ISBN-13 :9781789538762

Category :

Programming

Languages :

Python

Concepts :

Application Development

Tools :

Apache Spark

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Contact Details

Payment Processing...

Completed

Billing Address

Product Details

Last updated date :Apr 11, 2025

Publication date :Jun 28, 2018

Length:1hr 34mins

Edition :1st

Language :English

ISBN-13 :9781789538762

Category :

Programming

Languages :

Python

Concepts :

Application Development

Tools :

Apache Spark

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About the author

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.

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PySpark for Beginners: Take your first steps in developing large-scale distributed data processing applications using Apache Spark and Python

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