Materialized views play a crucial role in optimizing query performance and reducing data processing costs. Hereโs why they are created in the __databricks_internal
catalog:
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What Are Materialized Views?
- Materialized views are Unity Catalog managed tables within Databricks SQL.
- They allow users to precompute results based on the latest data in source tables.
- Unlike traditional views, materialized views store the actual data, not just the query definition.
- The results returned by materialized views reflect the state of data when the view was last refreshed, rather than updating results every time the view is queried.
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Use Cases and Benefits:
- Performance Optimization: Materialized views are especially useful for complex queries or aggregations that are performed frequently.
- Cost Reduction: By precomputing slow queries and commonly used computations, materialized views reduce costs.
- Query Latency Improvement: Storing pre-computed results avoids the need to repeatedly execute complex queries, resulting in faster response times.
- Data Transformations: Materialized views simplify data transformations, such as cleaning, enriching, and denormalizing base tables.
- Incremental Computation: In some cases, materialized views can incrementally compute changes from base tables, further reducing costs.
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Delta Live Tables Integration:
- When you create a materialized view in a Databricks SQL warehouse, a Delta Live Tables pipeline is automatically set up to process refreshes.
- You can monitor refresh status through the Delta Live Tables UI, API, or CLI.
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Requirements:
- To create and refresh materialized views, you need a Unity Catalog-enabled Databricks SQL warehouse.
- Ensure youโve accepted the serverless terms of use, and your workspace is in a serverless-enabled region.
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Limitations:
- Be aware of limitations when using materialized views with Databricks SQL.
In summary, materialized views provide a powerful way to optimize data processing workloads, improve query performance, and enhance the end-user experience. Theyโre a valuable addition to your DLT Pipeline! ๐
For more detailed information, you can refer to the official Databricks documentation on materialized views1.