Transform Data Using PySpark
Transform Data Using PySpark
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 43m | 109 MB
Instructor: Pinal Dave
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 43m | 109 MB
Instructor: Pinal Dave
Master large-scale data manipulation and analysis with PySpark. This course covers essential techniques for handling data, creating efficient workflows, and using custom functions to streamline complex tasks.
What you'll learn
Efficient data manipulation is critical for processing large-scale datasets effectively. In this course, Transform Data Using PySpark, you’ll gain the ability to manipulate, clean, and analyze large datasets using PySpark.
First, you’ll explore how to read and write data using various formats with schema specifications. Next, you’ll discover how to perform advanced transformations, including grouping, joins, and window functions, as well as handle data cleaning tasks like managing missing, null, and duplicate values. Finally, you’ll learn how to create custom functions, including UDFs, UDTFs, and vectorized UDFs, to extend PySpark's functionality for specific analytical needs.
When you’re finished with this course, you’ll have the skills and knowledge of PySpark needed to create efficient and reusable workflows for any data-driven challenge.
Transform Data Using PySpark
