In which of the following scenarios should a data engineer use the MERGE INTO command instead of the INSERT INTO command?

The MERGE INTO command is used to perform upserts, which are a combination of insertions and

updates, based on a source table into a target Delta table1. The MERGE INTO command can handle

scenarios where the target table cannot contain duplicate records, such as when there is a primary

key or a unique constraint on the target table. The MERGE INTO command can match the source and

target rows based on a merge condition and perform different actions depending on whether the

rows are matched or not. For example, the MERGE INTO command can update the existing target

rows with the new source values, insert the new source rows that do not exist in the target table, or

delete the target rows that do not exist in the source table1.

The INSERT INTO command is used to append new rows to an existing table or create a new table

from a query result2. The INSERT INTO command does not perform any updates or deletions on the

existing target table rows. The INSERT INTO command can handle scenarios where the location of the

data needs to be changed, such as when the data needs to be moved from one table to another, or

when the data needs to be partitioned by a certain column2. The INSERT INTO command can also

handle scenarios where the target table is an external table, such as when the data is stored in an

external storage system like Amazon S3 or Azure Blob Storage3. The INSERT INTO command can also

handle scenarios where the source table can be deleted, such as when the source table is a

temporary table or a view4. The INSERT INTO command can also handle scenarios where the source

is not a Delta table, such as when the source is a Parquet, CSV, JSON, or Avro file5.

Reference:

1: MERGE INTO | Databricks on AWS

2: [INSERT INTO | Databricks on AWS]

3: [External tables | Databricks on AWS]

4: [Temporary views | Databricks on AWS]

5: [Data sources | Databricks on AWS]