Databricks-DA-Assoc Executing Queries with Databricks SQL Practice Question
Which of the following describes the purpose of 'Data Skipping' in Databricks SQL when querying Delta tables?
⚠ Common exam trap
Candidates often confuse Data Skipping with full table indexing or caching, incorrectly believing that the engine loads all data into memory before filtering, rather than pruning files based on stats.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
It uses min/max statistics to skip irrelevant files
Data Skipping is a performance optimization where the Delta engine uses file-level statistics (min/max values) to prune files that do not contain data relevant to the query's filter conditions. By avoiding the I/O of reading irrelevant data files, the engine significantly speeds up queries. This is a primary benefit of the Delta format and is automatically handled by the engine during the planning phase of a SQL query.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It deletes old data files to save storage space
Why it's wrong here
Deleting old data files is the function of the VACUUM command. Data Skipping is a read-time optimization technique, not a data-cleaning or maintenance operation. It focuses on reducing the amount of data read, not the amount of data stored on the physical disk or cloud storage.
- ✓
It uses min/max statistics to skip irrelevant files
Why this is correct
Data Skipping leverages min/max statistics stored in the Delta transaction log to identify which files contain data that falls outside the range of the query's filters. Files that cannot possibly contain matching records are skipped, reducing the total I/O load and dramatically increasing query performance for large datasets.
- ✗
It caches frequently used tables in the browser
Why it's wrong here
Caching in the browser is not a function of the Delta engine. Data Skipping occurs on the cluster nodes during the query execution process, ensuring that the engine only fetches required data blocks from storage. It is a backend optimization, not a client-side or browser-based caching mechanism.
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It allows queries to run without reading any files
Why it's wrong here
While Data Skipping reduces the number of files read, it is impossible for a query to return results without reading any files, unless the query itself is a trivial constant expression. A query must always read at least some data to satisfy the user's request for specific records.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
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