w.schemas: Schemas

class databricks.sdk.service.catalog.SchemasAPI

A schema (also called a database) is the second layer of Unity Catalog’s three-level namespace. A schema organizes tables, views and functions. To access (or list) a table or view in a schema, users must have the USE_SCHEMA data permission on the schema and its parent catalog, and they must have the SELECT permission on the table or view.

create(name: str, catalog_name: str [, comment: Optional[str], properties: Optional[Dict[str, str]], storage_root: Optional[str]]) → SchemaInfo

Usage:

import time

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

created_catalog = w.catalogs.create(name=f'sdk-{time.time_ns()}')

created_schema = w.schemas.create(name=f'sdk-{time.time_ns()}', catalog_name=created_catalog.name)

# cleanup
w.catalogs.delete(name=created_catalog.name, force=True)
w.schemas.delete(full_name=created_schema.full_name)

Create a schema.

Creates a new schema for catalog in the Metatastore. The caller must be a metastore admin, or have the CREATE_SCHEMA privilege in the parent catalog.

Parameters:

  • name – str Name of schema, relative to parent catalog.

  • catalog_name – str Name of parent catalog.

  • comment – str (optional) User-provided free-form text description.

  • properties – Dict[str,str] (optional) A map of key-value properties attached to the securable.

  • storage_root – str (optional) Storage root URL for managed tables within schema.

Returns:

SchemaInfo

delete(full_name: str)

Delete a schema.

Deletes the specified schema from the parent catalog. The caller must be the owner of the schema or an owner of the parent catalog.

Parameters:

full_name – str Full name of the schema.

get(full_name: str [, include_browse: Optional[bool]]) → SchemaInfo

Usage:

import time

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

new_catalog = w.catalogs.create(name=f'sdk-{time.time_ns()}')

created = w.schemas.create(name=f'sdk-{time.time_ns()}', catalog_name=new_catalog.name)

_ = w.schemas.get(full_name=created.full_name)

# cleanup
w.catalogs.delete(name=new_catalog.name, force=True)
w.schemas.delete(full_name=created.full_name)

Get a schema.

Gets the specified schema within the metastore. The caller must be a metastore admin, the owner of the schema, or a user that has the USE_SCHEMA privilege on the schema.

Parameters:

  • full_name – str Full name of the schema.

  • include_browse – bool (optional) Whether to include schemas in the response for which the principal can only access selective metadata for

Returns:

SchemaInfo

list(catalog_name: str [, include_browse: Optional[bool], max_results: Optional[int], page_token: Optional[str]]) → Iterator[SchemaInfo]

Usage:

import time

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

new_catalog = w.catalogs.create(name=f'sdk-{time.time_ns()}')

all = w.schemas.list(catalog_name=new_catalog.name)

# cleanup
w.catalogs.delete(name=new_catalog.name, force=True)

List schemas.

Gets an array of schemas for a catalog in the metastore. If the caller is the metastore admin or the owner of the parent catalog, all schemas for the catalog will be retrieved. Otherwise, only schemas owned by the caller (or for which the caller has the USE_SCHEMA privilege) will be retrieved. There is no guarantee of a specific ordering of the elements in the array.

Parameters:

  • catalog_name – str Parent catalog for schemas of interest.

  • include_browse – bool (optional) Whether to include schemas in the response for which the principal can only access selective metadata for

  • max_results – int (optional) Maximum number of schemas to return. If not set, all the schemas are returned (not recommended). - when set to a value greater than 0, the page length is the minimum of this value and a server configured value; - when set to 0, the page length is set to a server configured value (recommended); - when set to a value less than 0, an invalid parameter error is returned;

  • page_token – str (optional) Opaque pagination token to go to next page based on previous query.

Returns:

Iterator over SchemaInfo

update(full_name: str [, comment: Optional[str], enable_predictive_optimization: Optional[EnablePredictiveOptimization], new_name: Optional[str], owner: Optional[str], properties: Optional[Dict[str, str]]]) → SchemaInfo

Usage:

import time

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

new_catalog = w.catalogs.create(name=f'sdk-{time.time_ns()}')

created = w.schemas.create(name=f'sdk-{time.time_ns()}', catalog_name=new_catalog.name)

_ = w.schemas.update(full_name=created.full_name, comment=f'sdk-{time.time_ns()}')

# cleanup
w.catalogs.delete(name=new_catalog.name, force=True)
w.schemas.delete(full_name=created.full_name)

Update a schema.

Updates a schema for a catalog. The caller must be the owner of the schema or a metastore admin. If the caller is a metastore admin, only the __owner__ field can be changed in the update. If the __name__ field must be updated, the caller must be a metastore admin or have the CREATE_SCHEMA privilege on the parent catalog.

Parameters:

  • full_name – str Full name of the schema.

  • comment – str (optional) User-provided free-form text description.

  • enable_predictive_optimization – EnablePredictiveOptimization (optional) Whether predictive optimization should be enabled for this object and objects under it.

  • new_name – str (optional) New name for the schema.

  • owner – str (optional) Username of current owner of schema.

  • properties – Dict[str,str] (optional) A map of key-value properties attached to the securable.

Returns:

SchemaInfo