Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 34 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 34

Select 3

You are tasked with creating a Delta table on Databricks to support analytical queries using the Databricks SQL service. The table will store large amounts of customer transaction data, which will be queried frequently by analysts. Which of the following steps should you take to optimize the Delta table for Databricks SQL?

  1. A

    Define an appropriate Z-ordering on columns frequently used in WHERE clauses.

  2. B

    Enable Auto Optimize and Auto Compaction on the Delta table.

  3. C

    Partition the Delta table by a column with high cardinality, such as a unique transaction ID.

  4. D

    Use the OPTIMIZE command to compact small files into larger ones.

  5. E

    Store the Delta table in a storage location with a high replication factor.

Show answer and explanation

Correct answers: A, B, D

Explanation

To optimize Delta tables for Databricks SQL, techniques such as Z-ordering on frequently filtered columns, enabling Auto Optimize/Auto Compaction, and using the OPTIMIZE command for file compaction are critical. These methods improve query performance by reducing data access latency and maintaining efficient storage. Partitioning should be used carefully, and high-cardinality columns should generally be avoided as partition keys.

  • A. Correct.

    Z-ordering helps optimize query performance in Databricks SQL by clustering data on frequently filtered columns, allowing for faster data retrieval.

  • B. Correct.

    Auto Optimize and Auto Compaction ensure that the Delta table maintains smaller, more performant files without user intervention, which is beneficial for analytical workloads.

  • C. Incorrect.

    Partitioning by a high-cardinality column, such as a unique transaction ID, is inefficient because it creates too many small files, which negatively impacts query performance.

  • D. Correct.

    The OPTIMIZE command compacts small files into larger ones, reducing the overhead of managing metadata and improving query performance.

  • E. Incorrect.

    While storage location reliability is important, the replication factor is not directly related to optimizing a Delta table for Databricks SQL.

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