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* Relaxed force_new constraint on catalog attribute in databricks_pipeline resource to allow changing the default catalog for existing pipelines
Pipelines will still be recreated when switching between `storage` and `catalog` modes,
but changing the catalog value in an existing catalog-based pipeline no longer requires
recreation.
Resolves#4692
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### New Features and Improvements
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* Improve `databricks_service_principals` data source ([#5164](https://github.com/databricks/terraform-provider-databricks/pull/5164))
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* Improve `databricks_service_principals` data source ([#5164](https://github.com/databricks/terraform-provider-databricks/pull/5164)).
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* Relaxed `force_new` constraint on `catalog` attribute in `databricks_pipeline` resource to allow changing the default catalog for existing pipelines ([#5180](https://github.com/databricks/terraform-provider-databricks/issues/5180)).
*`name` - A user-friendly name for this pipeline. The name can be used to identify pipeline jobs in the UI.
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*`catalog` - The name of catalog in Unity Catalog. *Change of this parameter forces recreation of the pipeline.* (Conflicts with `storage`).
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*`catalog` - The name of default catalog in Unity Catalog. *Change of this parameter forces recreation of the pipeline if you switch from `storage` to `catalog` or vice versa. If pipeline was already created with `catalog` set, the value could be changed.* (Conflicts with `storage`).
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*`schema` - (Optional, String, Conflicts with `target`) The default schema (database) where tables are read from or published to. The presence of this attribute implies that the pipeline is in direct publishing mode.
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*`storage` - A location on cloud storage where output data and metadata required for pipeline execution are stored. By default, tables are stored in a subdirectory of this location. *Change of this parameter forces recreation of the pipeline.* (Conflicts with `catalog`).
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*`target` - (Optional, String, Conflicts with `schema`) The name of a database (in either the Hive metastore or in a UC catalog) for persisting pipeline output data. Configuring the target setting allows you to view and query the pipeline output data from the Databricks UI.
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