Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 58 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 58

Single answer

You are designing a data lakehouse architecture for a retail company. They store transactional sales data in a Delta table with billions of rows and frequently query it by region and date. What is the best approach to partition the Delta table to optimize query performance?

  1. A

    Partition the table by both region and date to create a hierarchical directory structure.

  2. B

    Partition the table by region only, as it is a categorical column with a manageable number of unique values.

  3. C

    Partition the table by date only, as it is a column frequently queried in time-based filters.

  4. D

    Do not partition the table at all and rely on Delta Lake's data skipping and indexing capabilities.

Show answer and explanation

Correct answer: C

Explanation

Partitioning is a critical strategy for optimizing query performance on large datasets in Delta Lake. Selecting appropriate partition columns involves balancing the column's cardinality and query patterns. In this scenario, partitioning by date improves query efficiency because it is a common filter and likely has lower cardinality compared to region. Partitioning by both columns or not partitioning at all would result in inefficiencies either due to small file proliferation or excessive scanning. Partitioning only by region is suboptimal since it does not align with the primary query pattern.

  • A. Incorrect.

    Partitioning by both region and date can lead to an excessively large number of small files if both columns have high cardinality, making it inefficient.

  • B. Incorrect.

    Partitioning by region only is not optimal, as queries on date would require scanning all partitions for the required date range, leading to increased query time.

  • C. Correct.

    Partitioning by date only is the best choice because date is frequently filtered in queries, and it is typically a column with lower cardinality compared to region. This ensures better query performance while avoiding the creation of too many small files.

  • D. Incorrect.

    Not partitioning at all would result in poor query performance for large datasets since filters on date and region would require scanning the entire table.

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