Apache Spark 3 for Data Engineering and Analytics with Python - Challenge Part 2 - Write Partitioned DataFrame to Parque

This final lecture covers writing a dataframe into a partitioned Parquet file. It begins with creating and arranging the dataframe columns, followed by writing the data into a Parquet file partitioned by year and month. The lecture explains the benefits of partitioning, such as improved performance when working with large datasets. The session concludes with a demonstration of how partitioning organizes data into separate folders for each year and month, enhancing data management and retrieval efficiency.

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