Course Outline
Introduction
Overview of Apache Spark Features and Architecture
- Apache Spark modules: Spark SQL, Spark Streaming, MLlib, GraphX
- RDD, Dataframes, drive-workers, DAG, etc.
Setting up Apache Spark on .NET
- Preparing the Java VM
- Running .NET for Apache Spark using .NET Core
Getting Started
- Creating a sample .NET console application
- Adding the Spark driver
- Initializing a SparkSession
- Executing the application
Preparing Data
- Building a data preparation pipeline
- Performing ETL (Extract, Transform, and Load)
Machine Learning
- Building a machine learning model
- Preparing the data
- Training a model
Real-time Processing
- Processed streaming data in real-time
- Case study: monitoring sensor data
Interactive Query
- Working with Spark SQL
- Analyzing structured data
Visualizing Results
- Plotting results
- Using third-party tools to visualize results
Troubleshooting
Summary and Conclusion
Requirements
- .NET programming experience using C# or F#
Audience
- Developers
Testimonials (5)
A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution
Rafał - Nordea
Course - Apache Spark MLlib
The trainer was very helpful answering any questions we had and let us share our screen to show the errors we were having which was great.
chithra - Public Health Wales NHS Trust
Course - Advanced Blazor
Just the overall exposure. Very helpful.
Travis - Beckman Coulter
Course - Introduction to Blazor
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
This is one of the best hands-on with exercises programming courses I have ever taken.