Exam Certified Data Engineer Professional topic 1 question 22 discussion

Delta Lake's Auto Compaction feature is designed to improve the efficiency of data storage by reducing the number of small files in a Delta table. After data is written to a Delta table, an asynchronous job can be triggered to evaluate the file sizes. If it determines that there are a significant number of small files, it will automatically run the OPTIMIZE command, which coalesces these small files into larger ones, typically aiming for files around 1 GB in size for optimal performance. E is incorrect because the statement is similar to A but with an incorrect default file size target.

Delta Lake Auto Compaction is a feature that automatically detects opportunities to optimize small files. When a write operation is completed, an asynchronous job assesses whether the resulting files can be compacted into larger files (the default target size is 128 MB). If compaction is needed, the system executes an OPTIMIZE job in the background to improve file size and query performance. This feature reduces the overhead of managing small files manually and improves storage and query efficiency. It aligns with Delta Lake's goal of simplifying and optimizing data lake performance.

I think it is E because they are just asking us to generally describe the feature - here's some info I gleaned from a DB Academy video: ○ Compact small files on write with auto-optimize (tries to achieve file size of 128 MB) ○ Auto-Compact launches a new job after execution of first Spark job (i.e. async), where it will try to compress files closer to 128 MB

typo in databricks documentation about sync job, but default size is explicitly mentioned as 128

Table property: delta.autoOptimize.autoCompact B. correct, although https://docs.databricks.com/en/delta/tune-file-size.html#auto-compaction-for-delta-lake-on-databricks does not mention OPTIMIZE, it is best option A., E. wrong, auto compaction runs synchronously C. wrong, it describes Table setting: delta.autoOptimize.optimizeWrite D. wrong, not related to file compaction

There appears to be a typo in databricks documentation

Enable auto compaction. By default will use 128 MB as the target file size.

If you go through this docs - then one thing is clear that it is not async job, so we have to eliminate A & C. D is wrong. It has no special job wrt the partition. Also file size 0f 128 MB is legacy config, latest one is dynamic. So we are left with B

https://docs.databricks.com/en/delta/tune-file-size.html

Auto compaction is synchronous job.

A and E are wrong because auto compaction is synchronous operation! I vote for B As per documentation - "Auto compaction occurs after a write to a table has succeeded and runs synchronously on the cluster that has performed the write. Auto compaction only compacts files that haven’t been compacted previously." https://docs.delta.io/latest/optimizations-oss.html

E. An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an OPTIMIZE job is executed toward a default of 128 MB. https://community.databricks.com/t5/data-engineering/what-is-the-difference-between-optimize-and-auto-optimize/td-p/21189

E is the answer. Enable the settings uses the 128 MB as the target file size https://learn.microsoft.com/en-us/azure/databricks/delta/tune-file-size

default file size is 128MB in auto compaction

E is correct as the default file size is 128MB in auto compaction, not 1GB as normal OPTIMIZE statement.

128MB is the default.

Question is more on auto compaction hence the answer is E, as default size or auto compaction is 128 mb