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.
Benefits:
Enhanced Understanding: Gain a clear understanding of the workspace's current state and the objects that require attention during migration.
Improved Planning: Make informed decisions about the migration strategy and resource allocation based on the inventory data.
Reduced Risk: Identify potential issues and dependencies early on, minimizing the risk of migration failures.
Increased Efficiency: Streamline the migration process by automating data collection and analysis.
Use Cases:
Pre-Migration Assessment: Evaluate the workspace's readiness for Unity Catalog migration and identify areas that need adjustments.
Migration Planning: Develop a detailed migration plan based on the inventory data and insights.
Post-Migration Validation: Verify the successful migration of all workspace objects and ensure data integrity.
Key Features:
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:
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:
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.
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.
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