Apache PySpark by Example
- Offered byLinkedin Learning
Apache PySpark by Example at Linkedin Learning Overview
Apache PySpark by Example
at Linkedin Learning
Duration | 2 hours |
Total fee | ₹1,400 |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Apache PySpark by Example at Linkedin Learning Highlights
Apache PySpark by Example
at Linkedin Learning
- Earn a sharable certificate
Apache PySpark by Example at Linkedin Learning Course details
Apache PySpark by Example
at Linkedin Learning
Skills you will learn
More about this course
- This practical, hands-on course helps you get comfortable with PySpark, explaining what it has to offer and how it can enhance your data science work
- To begin, instructor Jonathan Fernandes digs into the Spark ecosystem, detailing its advantages over other data science platforms, APIs, and tool sets
- Next, he looks at the DataFrame API and how it's the platform's answer to many big data challenges. Finally, he goes over Resilient Distributed Datasets (RDDs), the building blocks of Spark
Apache PySpark by Example at Linkedin Learning Curriculum
Apache PySpark by Example
at Linkedin Learning
Introduction
Apache PySpark
What you should know
Introduction to Apache Spark
The Apache Spark ecosystem
Why Spark?
Spark origins and Databricks
Spark components
Partitions, transformations, lazy evaluations, and actions
Technical Setup
Set up the lab environment
Download a dataset
Importing
Working with the DataFrame API
The DataFrame API
Working with DataFrames
Schemas
Working with columns
Working with rows
Challenge
Solution
Functions
Built-in functions
Working with dates
User-defined functions
Working with joins
Challenge
Solution
Resilient Distributed Datasets (RDDs)
RDDs
Working with RDDs
Conclusion
Next steps
Apache PySpark by Example at Linkedin Learning Faculty details
Apache PySpark by Example
at Linkedin Learning
Jonathan Fernandes, Generative AI | Large Language Models | NLP
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