Consider a scenario where you need to update multiple records in a Spark table using Type 1 strategy. Describe the steps you would take to ensure that the updates are efficient and minimize the impact on the overall performance of the Spark cluster. Include considerations for data partitioning, caching, and the use of DataFrame APIs.

Simulated

Use the insertInto method to directly insert new records without considering partitioning or caching.

8.9%

Partition the data based on a key, cache the DataFrame before performing updates, and use the withColumn method to update specific records.

70.5%

Perform a full table scan and update records one by one using a loop.

2.7%

Use the merge operation without partitioning or caching the DataFrame.

17.8%

Databricks Certified Data Engineer - Professional