DP-750: Implementing Data Engineering Solutions Using Azure DatabricksDemo

By Microsoft · Question Mode

QuestionQ56

Prepare and process data

You have an Azure Databricks workspace enabled for Unity Catalog that contains a managed Delta table named Table1.

Table1 is written by batch jobs every hour and is frequently queried by filtering the CustomerId and EventDate columns. You expect Table1 to grow substantially over time. Its rows are frequently updated and deleted to support compliance requests.

You need to keep query performance consistent as Table1 grows while minimizing update and deletion effort. What should you include in the solution?

Select
To optimize query performance, implement:
To optimize updates and deletions:
Explanation

Liquid clustering improves data skipping for filters on clustering columns and is suited to large Unity Catalog managed Delta tables. Deletion vectors avoid immediately rewriting data files for row-level UPDATE and DELETE operations, reducing the work required for frequent compliance changes.

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