Partitioning vs Bucketing | Interview Question | PySpark #pyspark #bigdata #pwc #interview

Partitioning and bucketing are techniques used to optimize data storage and improve query performance in PySpark. The choice between them depends on the specific use case and the nature of the queries that will be executed on the data. Sample Data: date product amount region 01-01-2024 Product_0 0 Region_0 02-01-2024 Product_1 10 Region_1 03-01-2024 Product_2 20 Region_2 04-01-2024 Product_1 30 Region_0 05-01-2024 Product_4 40 Region_1 06-01-2024 Product_0 50 Region_2 07-01-2024 Product_1 60 Region_0 08-01-2024 Product_2 70 Region_1 09-01-2024 Product_2 80 Region_2 10-01-2024 Product_4 90 Region_0 Check out this video and do let me know your doubts we can connect on linkedIn :   / priyam-jain-0946ab199   PWC interview Question:    • Question 11: PWC Interview Questions part ...      • Question 10: PWC Interview Questions | dat...   Deloitte interview Question:    • Question 9: Deloitte Interview Questions |...   Do subscribe @pysparkpulse for more such Questions. #pyspark #spark #bigdata #bigdataengineer #dataengineering #dataengineer #deloitte #pwc #mnc