You have an Azure Databricks workspace that contains a Delta Lake dimension table named Table1. Table1 is a Type 2 slowly changing dimension (SCD) table. You need to apply updates from a source…

The correct answer is D. MERGE. When applying updates to a Type 2 slowly changing dimension (SCD) table in Azure Databricks, the best option is to use the MERGE operation in Apache Spark SQL. This operation allows you to combine the data from the source table with the data in the destination table, and then…

Submitted by hans_de· Mar 30, 2026Develop data processing

Question

You have an Azure Databricks workspace that contains a Delta Lake dimension table named Table1. Table1 is a Type 2 slowly changing dimension (SCD) table. You need to apply updates from a source table to Table1. Which Apache Spark SQL operation should you use?

Options

ACREATE
BUPDATE
CALTER
DMERGE

How the community answered

(59 responses)

A
2% (1)
B
10% (6)
C
5% (3)
D
83% (49)

Explanation

When applying updates to a Type 2 slowly changing dimension (SCD) table in Azure Databricks, the best option is to use the MERGE operation in Apache Spark SQL. This operation allows you to combine the data from the source table with the data in the destination table, and then update or insert the appropriate records. The MERGE operation provides a powerful and flexible way to handle updates for SCD tables, as it can handle both updates and inserts in a single operation. Additionally, this operation can be performed on Delta Lake tables, which can easily handle the ACID transactions needed for handling SCD updates.

Topics

#Delta Lake#SCD Type 2#MERGE operation#Azure Databricks

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