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Spark Programming in Python for Beginners with Apache Spark 3 [Video]
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Access this title in our online reader
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-
Free ChapterApache Spark Introduction
-
Installing and Using Apache Spark
- Spark Development Environments
- Mac Users - Apache Spark in Local Mode Command Line REPL
- Windows Users - Apache Spark in Local Mode Command Line REPL
- Mac Users - Apache Spark in the IDE - PyCharm
- Windows Users - Apache Spark in the IDE - PyCharm
- Apache Spark in Cloud - Databricks Community and Notebooks
- Apache Spark in Anaconda - Jupyter Notebook
-
Spark Execution Model and Architecture
- Execution Methods - How to Run Spark Programs?
- Spark Distributed Processing Model - How Your Program Runs?
- Spark Execution Modes and Cluster Managers
- Summarizing Spark Execution Models - When to Use What?
- Working with PySpark Shell - Demo
- Installing Multi-Node Spark Cluster - Demo
- Working with Notebooks in Cluster - Demo
- Working with Spark Submit - Demo
- Section Summary
-
Spark Programming Model and Developer Experience
- Creating Spark Project Build Configuration
- Configuring Spark Project Application Logs
- Creating Spark Session
- Configuring Spark Session
- Data Frame Introduction
- Data Frame Partitions and Executors
- Spark Transformations and Actions
- Spark Jobs Stages and Task
- Understanding your Execution Plan
- Unit Testing Spark Application
- Rounding off Summary
-
Spark Structured API Foundation
-
Spark Data Sources and Sinks
-
Spark Dataframe and Dataset Transformations
-
Aggregations in Apache Spark
-
Spark Dataframe Joins
-
Keep Learning
About this video
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
- Publication date:
- February 2022
- Publisher
- Packt
- Duration
- 6 hours 35 minutes
- ISBN
- 9781803246161
Download code from GitHub