Exam DP-203 topic 1 question 36 discussion

HOTSPOT -
You plan to develop a dataset named Purchases by using Azure Databricks. Purchases will contain the following columns:
✑ ProductID
✑ ItemPrice
✑ LineTotal
✑ Quantity
✑ StoreID
✑ Minute
✑ Month
✑ Hour

Year -

✑ Day
You need to store the data to support hourly incremental load pipelines that will vary for each Store ID. 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.
Hot Area:

Suggested Answer:
Box 1: partitionBy -
We should overwrite at the partition level.
Example:
df.write.partitionBy("y","m","d")
.mode(SaveMode.Append)
.parquet("/data/hive/warehouse/db_name.db/" + tableName)
Box 2: ("StoreID", "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