How can we partition a dataset by year, month, and region to create a standardized directory layout on object storage?
partitionBy('year', 'month', 'region') writes files into nested subdirectories enabling fine-grained partition pruning during reads.
Structuring global event logs and sales transactions for rapid regional and temporal slice queries.
df_partitioned = df.withColumn("year", year("event_date")).withColumn("month", month("event_date"))
df_partitioned.write.partitionBy("year", "month", "region").mode("append").parquet("s3://lakehouse/silver/events/")Practice typing production-grade PySpark code for Multi-Level Hive-Style Partitioning.