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Monitor and Optimize an Analytics SolutionmediumMultiple ChoiceObjective-mapped

DP-700 Monitor and Optimize an Analytics Solution Practice Question

You are monitoring a Microsoft Fabric Lakehouse. You observe that queries against a specific Delta table are performing poorly. You identify that the table contains a large number of small files. Which command should you run to optimize the file layout?

⚠ Common exam trap

Test-takers often confuse metadata maintenance commands like V-ORDER or standard vacuum operations with the specific file compaction utility needed for small files.

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

OPTIMIZE table_name

Optimizing file layouts is crucial for performance in Delta Lake, as small files induce metadata overhead and increase read latency. The OPTIMIZE command consolidates these small files into larger, more efficient Parquet files, significantly improving scan performance. This maintenance task is essential in streaming-heavy environments where micro-batching frequently creates tiny data fragments that degrade analytics performance over time.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ALTER TABLE REFRESH

    Why it's wrong here

    The REFRESH command is typically used to update metadata caches or resolve schema drift issues. It does not perform physical compaction of data files or reorganize the underlying Parquet files to improve read performance for downstream analytics queries.

  • VACUUM

    Why it's wrong here

    The VACUUM command is intended to remove stale data files that are no longer referenced by the Delta log and are older than the retention threshold. While it manages storage costs, it does not consolidate small files into larger, optimized files.

  • OPTIMIZE table_name

    Why this is correct

    Running OPTIMIZE reorganizes the data by compacting small files into larger, optimally sized Parquet files. This process improves read performance by reducing the number of files the engine must scan, which is the standard procedure for mitigating small file issues in Lakehouses.

  • ANALYZE TABLE

    Why it's wrong here

    The ANALYZE command collects table statistics, such as column distributions and counts, which the query optimizer uses to generate efficient execution plans. It does not physically rewrite or consolidate the actual data files stored in the underlying Delta storage.

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Last reviewed September 2026 · checked against the official Microsoft exam blueprint

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