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Spark Programming in Python for Beginners with Apache Spark 3
Spark Programming in Python for Beginners with Apache Spark 3

Spark Programming in Python for Beginners with Apache Spark 3: Learn Data Engineering using Spark Structured API

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€37.99
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Video Feb 2022 6hrs 35mins 1st Edition
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Profile Icon ScholarNest
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€37.99
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (1 Ratings)
Video Feb 2022 6hrs 35mins 1st Edition
Video
€37.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€37.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Build your own data engineering solutions using Spark structured API in Python
  • Gain an in-depth understanding of the Apache Hadoop architecture, ecosystem, and practices
  • Learn to apply Spark programming basics

Description

If you are looking to expand your knowledge in data engineering or want to level up your portfolio by adding Spark programming to your skillset, then you are in the right place. This course will help you understand Spark programming and apply that knowledge to build data engineering solutions. This course is example-driven and follows a working session-like approach. We will be taking a live coding approach and explaining all the concepts needed along the way. In this course, we will start with a quick introduction to Apache Spark, then set up our environment by installing and using Apache Spark. Next, we will learn about Spark execution model and architecture, and about Spark programming model and developer experience. Next, we will cover Spark structured API foundation and then move towards Spark data sources and sinks. Then we will cover Spark Dataframe and dataset transformations. We will also cover aggregations in Apache Spark and finally, we will cover Spark Dataframe joins. By the end of this course, you will be able to build data engineering solutions using Spark structured API in Python. All the resources for the course are available at https://github.com/PacktPublishing/Spark-Programming-in-Python-for-Beginners-with-Apache-Spark-3

Who is this book for?

This course is designed for software engineers willing to develop a data engineering pipeline and application using Apache Spark; for data architects and data engineers who are responsible for designing and building the organization’s data-centric infrastructure, for managers and architects who do not directly work with Spark implementation but work with the people who implement Apache Spark at the ground level. This course does not require any prior knowledge of Apache Spark or Hadoop; only programming knowledge using Python programming language is required.

What you will learn

  • Learn Apache Spark Foundation and Spark architecture
  • Learn data engineering and data processing in Spark
  • Work with data sources and sinks
  • Work with data frames and Spark SQL
  • Use PyCharm IDE for Spark development and debugging
  • Learn unit testing, managing application logs, and cluster deployment

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 18, 2022
Length: 6hrs 35mins
Edition : 1st
Language : English
ISBN-13 : 9781803246161
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Product Details

Publication date : Feb 18, 2022
Length: 6hrs 35mins
Edition : 1st
Language : English
ISBN-13 : 9781803246161
Category :
Languages :

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Table of Contents

10 Chapters
Apache Spark Introduction Chevron down icon Chevron up icon
Installing and Using Apache Spark Chevron down icon Chevron up icon
Spark Execution Model and Architecture Chevron down icon Chevron up icon
Spark Programming Model and Developer Experience Chevron down icon Chevron up icon
Spark Structured API Foundation Chevron down icon Chevron up icon
Spark Data Sources and Sinks Chevron down icon Chevron up icon
Spark Dataframe and Dataset Transformations Chevron down icon Chevron up icon
Aggregations in Apache Spark Chevron down icon Chevron up icon
Spark Dataframe Joins Chevron down icon Chevron up icon
Keep Learning Chevron down icon Chevron up icon

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Inaccurate information, JAVA_HOME is a missing parameter that needs to be defined in windows
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