Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 39 of 313

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

Databricks Data Engineer Professional Question 39

Single answer

A data engineering team is working on a large-scale e-commerce dataset containing billions of transaction records. The dataset includes the following columns: transaction_id, customer_id, transaction_date, product_category, and amount. The team needs to optimize the dataset for query performance by partitioning it. Queries will primarily filter data by transaction_date and product_category. Which partitioning strategy should the team use?

  1. A

    Partition by transaction_date only.

  2. B

    Partition by product_category only.

  3. C

    Partition by transaction_date and product_category.

  4. D

    Partition by customer_id.

Show answer and explanation

Correct answer: C

Explanation

Partitioning data should align with the most common query patterns to minimize the amount of data read during query execution. In this scenario, queries primarily filter data by transaction_date and product_category, so partitioning by both columns ensures efficient filtering and avoids unnecessary data scanning.

  • A. Incorrect.

    Partitioning by transaction_date only will improve query performance for filters on transaction_date, but it will not optimize for queries that also filter on product_category.

  • B. Incorrect.

    Partitioning by product_category only will improve query performance for filters on product_category, but it will not optimize for queries that also filter on transaction_date.

  • C. Correct.

    Partitioning by both transaction_date and product_category allows the queries to filter data efficiently based on the most common filtering patterns, improving overall performance.

  • D. Incorrect.

    Partitioning by customer_id is not suitable for this scenario because the queries do not filter data based on customer_id.

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