Databricks Machine Learning Professional Question 154
Single answerYou are working on a machine learning project where you store model predictions in a Delta table. Analysts frequently query the table to retrieve predictions for specific time ranges. However, these queries are taking a long time to execute. What can you do to optimize the query performance for these time-based lookups?
- A
Use Z-ordering on the timestamp column to optimize data layout for time-based queries.
- B
Increase the number of partitions in the Delta table to distribute data across more files.
- C
Enable Delta Lake's Auto Optimize feature to automatically manage data layout.
- D
Cluster the data by the prediction values to improve query performance.
Show answer and explanation
Correct answer: A
Explanation
Z-ordering is a technique in Delta Lake that optimizes the layout of data files based on the values of one or more columns. When you Z-order a table by a specific column, such as a timestamp column, related data is colocated in the same file or set of files. This reduces the amount of data read during queries that filter by the Z-ordered column, improving query performance. In contrast, approaches like increasing partitions or enabling Auto Optimize do not specifically target time-based query optimization.
- A. Correct.
Z-ordering is a data layout optimization technique in Delta Lake that reorganizes data files based on the values of a specified column, such as a timestamp column. This reduces the amount of data scanned during time-based queries, significantly improving query performance.
- B. Incorrect.
Increasing the number of partitions can help with parallelism but may not directly improve query performance for time-based lookups. It could also lead to small files, which can negatively impact performance.
- C. Incorrect.
While Delta Lake's Auto Optimize feature can help with managing small files and optimizing data layout in general, it does not specifically address query performance for time-based lookups.
- D. Incorrect.
Clustering the data by prediction values is not ideal for optimizing time-based queries. Z-ordering on the timestamp column is a more effective approach in this scenario.