If you use DROP SCHEMA without the CASCADE option, you must delete all tables in the schema before you can delete it. Sql('DROP SCHEMA inventory_schema CASCADE') Sql('DROP SCHEMA ')įor example, to delete a schema named inventory_schema and its tables: library(SparkR) spark.sql('DROP SCHEMA ')įor example, to delete a schema named inventory_schema and its tables: spark.sql('DROP SCHEMA inventory_schema CASCADE') Run the following SQL command in a notebook. DROP SCHEMA įor example, to delete a schema named inventory_schema and its tables: DROP SCHEMA inventory_schema CASCADE įor parameter descriptions, see DROP SCHEMA. Run the following SQL command in a notebook or Databricks SQL editor. On the Delete Database dialog, click Delete.In the detail pane, click the three-dot menu in the upper right corner and select Delete.In the Catalog pane, on the left, click the schema (database) that you want to delete.Log in to a workspace that is linked to the metastore.You must delete all tables in the schema before you can delete it. To delete (or drop) a schema (database), you can use Catalog Explorer or a SQL command. You can retrieve a list of schema IDs by using databricks_schemas. You can also create a schema by using the Databricks Terraform provider and databricks_schema. See Unity Catalog privileges and securable objects. You can optionally omit the USE CATALOG statement and replace with. Spark SQL properties and values to set for the schema.įor parameter descriptions, see CREATE SCHEMA. : Optional description or other comment.You can use the path that is defined in the external location configuration or a subpath (in other words, 'abfss://us-east-1/finance' or 'abfss://us-east-1/finance/product'). This path must be defined in an external location configuration, and you must have the CREATE MANAGED STORAGE privilege on the external location configuration. Provide a storage location path if you want managed tables in this schema to be stored in a location that is different than the catalog’s or metastore’s root storage location. Available only if you are using Databricks SQL or a cluster running Databricks Runtime 11.3 or above. : The name of the parent catalog for the schema.Run the following SQL commands in a notebook or Databricks SQL editor. See Manage external locations and storage credentials.Īssign permissions for your catalog. The path that you specify must be defined in an external location configuration, and you must have the CREATE MANAGED STORAGE privilege on that external location. Specify a location here only if you do not want managed tables in this schema to be stored in the default root storage location that was configured for the metastore or the managed storage location specified for the catalog (if any). This option appears only if you are using Databricks SQL or a cluster running Databricks Runtime 11.3 or above. (Optional) Specify the location where data for managed tables in the schema will be stored. Give the schema a name and add any comment that would help users understand the purpose of the schema. In the detail pane, click Create database. In the Catalog pane on the left, click the catalog you want to create the schema in. Log in to a workspace that is linked to the metastore. To create a schema (database), you can use Catalog Explorer or SQL commands. The compute resource that you use to run the notebook or Databricks SQL to create the catalog must be using a Unity Catalog compliant access mode. You must have a Unity Catalog metastore linked to the workspace where you perform the schema creation. Your Azure Databricks account must be on the Premium plan. If you are a metastore admin, you can grant these privileges to yourself.Īll users have the USE CATALOG permission on the main catalog by default. Either a metastore admin or the owner of the catalog can grant you these privileges. You must have the USE CATALOG and CREATE SCHEMA data permissions on the schema’s parent catalog. A schema contains tables, views, and functions. This article shows how to create and manage schemas (databases) in Unity Catalog.

Omnigraffle database schema