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.

What is the main task introduced in the final lecture?

• Writing a DataFrame into a Parquet file partitioned by year and month

• Merging multiple DataFrames into one

• Creating a new DataFrame from scratch

• Deleting unnecessary columns from a DataFrame

Which column is set to appear first in the rearranged DataFrame?

• Order Date

• Product

• City

• Order ID

What is the purpose of setting an output path before writing the DataFrame?

• To delete the existing DataFrame

• To change the format of the DataFrame

• To rename the DataFrame

• To specify where the DataFrame should be saved

Why is data partitioning beneficial when working with large datasets?

• It enhances data security

• It automatically corrects data errors

• It improves performance by allowing selective data access

• It reduces the file size

What happens to the data of each report year during partitioning?

• It is deleted if not needed

• It is stored in separate folders for each year

• It is encrypted for security

• It is merged into a single file

How does partitioning affect the DataFrame when querying specific data?

• It compresses the data for storage

• It requires reading the entire dataset

• It allows accessing only the relevant partitions

• It duplicates the data for faster access

What is the final step mentioned in the lecture after partitioning the data?

• Encrypting the data

• Merging the partitions

• Deleting temporary files

• Reviewing the partitioned folders