Which of the following likely explains these smaller file sizes?

A production workload incrementally applies updates from an external Change Data Capture feed to a Delta Lake table as an always-on Structured Stream job. When data was initially migrated for this table, OPTIMIZE was executed and most data files were resized to 1 GB. Auto Optimize and Auto Compaction were both turned on for the streaming production job. Recent review of data files shows that most data files are under 64 MB, although each partition in the table contains at least 1 GB of data and the total table size is over 10 TB.

Which of the following likely explains these smaller file sizes?
A . Databricks has autotuned to a smaller target file size to reduce duration of MERGE operations
B . Z-order indices calculated on the table are preventing file compaction
C . Bloom filler indices calculated on the table are preventing file compaction
D . Databricks has autotuned to a smaller target file size based on the overall size of data in the table
E . Databricks has autotuned to a smaller target file size based on the amount of data in each partition

View Answer

Answer: A

Explanation:

This is the correct answer because Databricks has a feature called Auto Optimize, which automatically optimizes the layout of Delta Lake tables by coalescing small files into larger ones and sorting data within each file by a specified column. However, Auto Optimize also considers the trade-off between file size and merge performance, and may choose a smaller target file size to reduce the duration of merge operations, especially for streaming workloads that frequently update existing records. Therefore, it is possible that Auto Optimize has autotuned to a smaller target file size based on the characteristics of the streaming production job.

Verified Reference: [Databricks Certified Data Engineer Professional], under “Delta Lake” section; Databricks Documentation, under “Auto Optimize” section. https://docs.databricks.com/en/delta/tune-file-size.html#autotune-table ‘Autotune file size based on workload’