Databricks Data Engineer Associate Question 297
Single answerA data engineering team is working with a large Delta Lake table containing several terabytes of data. They frequently query the table using a specific column, region_id, to filter data for analytical workloads. How can Z-ordering benefit their Delta Lake table in this scenario?
- A
It reduces the storage size of the Delta Lake table by compressing the files.
- B
It improves query performance by colocating related data based on the specified column.
- C
It ensures that data is partitioned more effectively to reduce query latency.
- D
It optimizes the storage format to make the table compatible with different query engines.
Show answer and explanation
Correct answer: B
Explanation
Z-ordering in Delta Lake is an optimization technique that sorts and colocates related data within the same files based on the specified column(s). In this scenario, Z-ordering on the region_id column allows the system to skip irrelevant files during queries, significantly improving query performance for filter operations on region_id. It is especially beneficial for large tables with frequent queries on specific columns.
- A. Incorrect.
Z-ordering does not directly reduce the storage size; its main benefit is improving query performance by clustering data related to a specific column.
- B. Correct.
This is the correct answer. Z-ordering colocates data with similar values for a specified column, such as
region_id, within the same files. This improves data skipping and query performance. - C. Incorrect.
While partitioning can reduce query latency, Z-ordering is not a partitioning mechanism. It works within partitions to optimize data layout.
- D. Incorrect.
Z-ordering does not change the storage format or compatibility with query engines. Its primary benefit is to enhance query performance through data clustering.