Course Outline
Introduction
- Apache Spark vs Hadoop MapReduce
Overview of Apache Spark Features and Architecture
Choosing a Programming Language
Setting up Apache Spark
Creating a Sample Application
Choosing the Data Set
Running Data Analysis on the Data
Processing of Structured Data with Spark SQL
Processing Streaming Data with Spark Streaming
Integrating Apache Spark with 3rd Part Machine Learning Tools
Using Apache Spark for Graph Processing
Optimizing Apache Spark
Troubleshooting
Summary and Conclusion
Requirements
- Experience with the Linux command line
- A general understanding of data processing
- Programming experience with Java, Scala, Python, or R
Audience
- Developers
Testimonials (2)
Commitment and willingness to explain secondary topics.
Marek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Course - Apache Spark Fundamentals
Machine Translated
The trainer's practical experience, not coloring the discussed solution, but also not introducing a negative connotation. I feel that the trainer is preparing me for real and practical use of the tool - these valuable details are usually not found in books.
Krzysztof Miodek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Course - Apache Spark Fundamentals
Machine Translated