HOTSPOTYou plan to develop a dataset named Purchases by using Azure Databricks. Purchases will contain the following columns:ProductIDItemPriceLineTotalQuantityStoreIDMinuteMonthHourYearDayYou need to store the data to support hourly incremental load pipelines that will vary for each StoreID. The solution must minimize storage costs.How should you complete the code? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.

Administering Relational Databases on Microsoft Azure (DP-300) Test 1

Solution:

Box 1: .partitionBy
Example:
df.write.partitionBy("y","m","d")
.mode(SaveMode.Append)
.parquet("/data/hive/warehouse/db_name.db/" + tableName)
Box 2: ("Year","Month","Day","Hour","StoreID")
Box 3: .parquet("/Purchases")
Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partitions-with-no-new-data