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https://youtu.be/24c58V5cZTM?si=W2enL_u9-u_n3ex-

Purpose:

This feature performs a comprehensive inventory of a workspace to aid in the migration process to Unity Catalog. It analyzes various workspace objects, including tables, databases, functions, users, groups, grants, notebooks, files, jobs, DLT pipelines, external locations, and clusters, providing valuable insights into the complexity and potential challenges of the migration.

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  • Inventory of Workspace Objects:

    • Tables: Identifies managed, external, and tables requiring review, including details about location, owner, provider, and type.

    • Databases: Analyzes Hive databases, providing information about location, owner, comments, and potential table errors.

    • Functions: Inventories Hive functions, including class name, type, determinism, and version.

    • Users and Groups: Provides details on workspace users and groups, including entitlements and memberships.

    • Grants: Analyzes permission grants for tables within databases.

    • Notebooks and Files: Identifies notebooks and files within the workspace, excluding certain file types.

    • Jobs: Analyzes jobs and identifies the type of task (notebook, spark, python, etc.) and the object name associated with the task.

    • DLT Pipelines: Provides an overview of Delta Live Tables pipelines.

    • External Locations: Lists external locations used within the workspace.

    • Clusters: Provides information about cluster IDs, names, and Spark versions.

    • Models: Lists models in the model registry along with user and version information.

    Code Analysis:
    • Notebook Impact Assessment: Analyzes notebooks to identify references to Hive tables and DBFS, aiding in understanding the potential impact of migration on notebooks.

    • Statistical Analysis: Calculates mean, median, and mode for table references in notebooks.

  • Recommendations: Offers actionable recommendations based on the assessment findings, including:

  • The feature requires a Unity Catalog-enabled workspace and access to a specific catalog, schema, and volume for storing results.

  • The notebook utilizes the Databricks SDK for Python and leverages various Spark SQL functions for data analysis.
    • Upgrading cluster DBR versions

    • Addressing data in DBFS root

    • Migrating workspace permission grants

    • Evaluating workspace groups

    • Designing the Unity Catalog structure

    • Strategizing for external locations

    • Analyzing source code objects used in multiple jobs

    • Evaluating notebooks that reference tables and DBFS.

  • Reporting:

    • Delta Tables: Stores the inventory data in Delta tables within the specified Unity Catalog schema for further analysis.

    • CSV Files: Generates comprehensive CSV reports for each inventory category.

    • Notebook Impact Analysis Graph: Generates an interactive graph visualizing the distribution of table references in notebooks.

Additional Notes:

Conclusion:

The Unity Catalog Migration Assessment feature in the Blueprint Lakehouse Optimizer provides valuable insights and automation capabilities to facilitate a smooth and successful migration to Unity Catalog. By leveraging its comprehensive analysis and actionable recommendations, organizations can confidently navigate the complexities of migration and ensure a seamless transition to a more secure and governed data lakehouse environment.