Parquet Explained in Depth with PySpark | Internals, Columnar Format, Footers

Lets explore everything about the Parquet file format — one of the most powerful and efficient data storage formats used in modern data engineering. You’ll learn what makes Parquet special, how it works internally, and how to use it effectively in Spark using PySpark on Databricks. All code and data files are available on the below path: https://github.com/databeli/pyspark_c... PowerPoint Presentaion useed in the complete playlist(27 slides) https://topmate.io/narender_kumar_91/... What you’ll learn: What is Parquet format and how it evolved Why Parquet is better than CSV and other formats Row vs Columnar storage explained How Parquet stores data internally using row groups and footers Reading and writing Parquet files using Spark DataFrames By the end of this video, you’ll have a complete understanding of Parquet’s structure, performance advantages, and how to read and write Parquet files efficiently in PySpark and Databricks. #parquet #columnarformat #pyspark #pysparktutorial #databricks #databrickstutorial