You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:

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You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:

• ProductID

• ItemPrice

• lineTotal

• Quantity

• StorelD

• Minute

• Month

• Hour

• Year

• Day

You 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 rode? To answer, select the appropriate options In the answer area. NOTE: Each correct selection is worth one point.

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Suggested Answer:

Explanation:

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")