Databricks Data Engineer Associate exam dumps

Databricks Data Engineer Associate practice question 478 of 532

Databricks Certified Data Engineer Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Associate Question 478

Select 3

In Databricks, how do metastores and catalogs differ in terms of their functionality and scope?

  1. A

    A metastore is a top-level container for managing metadata, while a catalog organizes data within the metastore.

  2. B

    Metastores are specific to a single workspace, while catalogs can span across multiple workspaces when using Unity Catalog.

  3. C

    A catalog is primarily used to store metadata about tables and views, while a metastore stores the actual data files.

  4. D

    Multiple metastores can coexist in a single workspace, but a catalog is unique to a metastore.

  5. E

    Metastores are tied to a cloud provider's storage layer, while catalogs abstract data organization independently of storage.

Show answer and explanation

Correct answers: A, B, D

Explanation

Metastores and catalogs serve different purposes in Databricks. The metastore is the top-level container responsible for metadata management, while catalogs are logical organizational layers within the metastore. Unity Catalog introduces multi-workspace capabilities for catalogs, whereas metastores remain tied to individual workspaces. Understanding their differences helps in designing scalable and governed data architectures in Databricks.

  • A. Correct.

    Correct: A metastore is the top-level container responsible for managing metadata about tables, views, and other objects, while a catalog is a logical organizational layer within the metastore.

  • B. Correct.

    Correct: Metastores are typically scoped to a single workspace in Databricks, but catalogs in Unity Catalog can span multiple workspaces to provide unified governance.

  • C. Incorrect.

    Incorrect: Catalogs do not store metadata about tables and views exclusively; they are part of the logical organization of the metadata managed by the metastore. The metastore does not store actual data files; it handles metadata.

  • D. Correct.

    Correct: Multiple metastores can exist within a Databricks workspace, particularly in cases where different teams or projects require isolation. However, each catalog is tied to a specific metastore.

  • E. Incorrect.

    Incorrect: While metastores are tied to a cloud provider's storage layer (e.g., AWS S3, Azure Data Lake), catalogs are not completely independent of storage. They are abstractions within the metastore but still rely on the underlying storage.

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