Databricks Data Engineer Associate exam dumps

Databricks Data Engineer Associate practice question 139 of 532

Databricks Certified Data Engineer Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Associate Question 139

Select 3

You are working on a Databricks project where you need to validate that the customer_id column in a Delta table is unique across all rows. Which of the following approaches can effectively help you ensure the uniqueness of the customer_id column?

  1. A

    Use a SQL query with the COUNT function and GROUP BY customer_id to identify duplicate values.

  2. B

    Create a Delta table constraint using the PRIMARY KEY keyword on the customer_id column.

  3. C

    Leverage the DISTINCT keyword in a SQL query to check if the total number of distinct customer_id values matches the total number of rows in the table.

  4. D

    Write a PySpark job to compute the count of each customer_id using groupBy and filter for counts greater than 1.

  5. E

    Enable Z-Ordering on the customer_id column to ensure uniqueness.

Show answer and explanation

Correct answers: A, C, D

Explanation

To validate the uniqueness of a primary key such as customer_id in a Delta table, you need to programmatically or analytically identify duplicates. Approaches like using SQL queries with COUNT and GROUP BY, leveraging DISTINCT, or writing a PySpark job allow you to detect duplicates effectively. Direct primary key constraints are not supported in Delta Lake, and features like Z-Ordering are unrelated to data validation.

  • A. Correct.

    Correct: Using a SQL query with COUNT and GROUP BY can help you identify duplicates by grouping the customer_id values and checking for counts greater than 1.

  • B. Incorrect.

    Incorrect: Delta Lake does not currently support PRIMARY KEY constraints directly as of October 2023.

  • C. Correct.

    Correct: Using the DISTINCT keyword and comparing the count of distinct values to the total number of rows is a valid way to check for uniqueness.

  • D. Correct.

    Correct: A PySpark job can programmatically check for duplicates by grouping on customer_id and filtering for counts greater than 1, making it an effective approach.

  • E. Incorrect.

    Incorrect: Z-Ordering is a performance optimization feature in Delta Lake for improving query efficiency and does not enforce or ensure uniqueness.

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