Databricks Machine Learning Professional exam dumps

Databricks Machine Learning Professional practice question 10 of 280

Databricks Certified Machine Learning Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Professional Question 10

Select 2

You are working on a machine learning project in Databricks that involves incremental training of a model using new data arriving daily. You decide to store the training data in a Delta table for efficient reads and writes. Which of the following steps is necessary to correctly update the Delta table and prepare the data for training?

  1. A

    Use the MERGE operation to upsert new data into the Delta table.

  2. B

    Run the VACUUM command to delete old files before reading from the Delta table.

  3. C

    Use the spark.read.format('delta') method to read the Delta table for training.

  4. D

    Use the spark.write.format('delta').mode('overwrite') method to append new data to the Delta table.

  5. E

    Enable Delta Lake time travel to retrieve previous versions of the training data.

Show answer and explanation

Correct answers: A, C

Explanation

To maintain the consistency and efficiency of the Delta table in an incremental training setup, the MERGE operation is the recommended approach to update the Delta table with new data. Additionally, the spark.read.format('delta') method is the standard way to read the Delta table into a DataFrame for training. Other options, like VACUUM, mode('overwrite'), and time travel, serve different purposes and are not directly relevant to the given scenario.

  • A. Correct.

    Correct. The MERGE operation is the appropriate way to upsert (insert or update) new data into a Delta table, ensuring that the table remains consistent and avoids duplicate records.

  • B. Incorrect.

    Incorrect. While the VACUUM command is used to clean up old files, it is not a required step for updating the Delta table or preparing data for training. Additionally, running VACUUM could delete files necessary for time travel if not configured carefully.

  • C. Correct.

    Correct. Using spark.read.format('delta') is the correct way to read a Delta table into a DataFrame, which can then be used for training the machine learning model.

  • D. Incorrect.

    Incorrect. The mode('overwrite') option is used to completely overwrite the Delta table, which is not suitable for appending or updating new data in an incremental training scenario.

  • E. Incorrect.

    Incorrect. While Delta Lake time travel is a powerful feature, enabling it is not required for updating the Delta table or preparing data for training. It is primarily used for querying historical versions of the data.

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