Discover OneLake schemas and individual tables

These helpers expose the read-only OneLake Delta table metadata API for Lakehouses and Warehouses. The schema helpers follow every metadata page. The singular table helpers retrieve one table's full column metadata without listing every table in every schema.

Usage

fabric_lakehouse_schemas(
  lakehouse,
  workspace = NULL,
  page_size = NULL,
  tenant_id = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id = Sys.getenv("FABRICQUERYR_CLIENT_ID", unset =
    "04b07795-8ddb-461a-bbee-02f9e1bf7b46"),
  token = NULL,
  auth_args = list(),
  api_base = .fabric_api_base,
  table_api_base = .fabric_onelake_table_base,
  storage_token = NULL
)

fabric_warehouse_schemas(
  warehouse,
  workspace = NULL,
  page_size = NULL,
  tenant_id = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id = Sys.getenv("FABRICQUERYR_CLIENT_ID", unset =
    "04b07795-8ddb-461a-bbee-02f9e1bf7b46"),
  token = NULL,
  auth_args = list(),
  api_base = .fabric_api_base,
  table_api_base = .fabric_onelake_table_base,
  storage_token = NULL
)

fabric_lakehouse_table(
  lakehouse,
  table,
  workspace = NULL,
  schema = NULL,
  tenant_id = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id = Sys.getenv("FABRICQUERYR_CLIENT_ID", unset =
    "04b07795-8ddb-461a-bbee-02f9e1bf7b46"),
  token = NULL,
  auth_args = list(),
  api_base = .fabric_api_base,
  table_api_base = .fabric_onelake_table_base,
  storage_token = NULL,
  enrich_fabric = FALSE
)

fabric_warehouse_table(
  warehouse,
  table,
  workspace = NULL,
  schema = NULL,
  tenant_id = Sys.getenv("FABRICQUERYR_TENANT_ID"),
  client_id = Sys.getenv("FABRICQUERYR_CLIENT_ID", unset =
    "04b07795-8ddb-461a-bbee-02f9e1bf7b46"),
  token = NULL,
  auth_args = list(),
  api_base = .fabric_api_base,
  table_api_base = .fabric_onelake_table_base,
  storage_token = NULL
)

Arguments

lakehouse

Lakehouse GUID, exact display name, or one Lakehouse object returned by fabric_lakehouses().

workspace

Workspace GUID, exact display name, or discovered workspace. Omit it when the item object contains workspaceId.

page_size

Optional maximum schemas requested per metadata page, from 1 to 100. All continuation tokens are followed.

tenant_id

Entra tenant ID. Defaults to FABRICQUERYR_TENANT_ID.

client_id

Entra application ID. Defaults to FABRICQUERYR_CLIENT_ID, then the Azure CLI application ID.

token

Optional access token or audience-aware token-provider function.

auth_args

Additional sign-in options passed to fabric_credential().

api_base

Fabric REST API base used when an item name or GUID must be resolved. Most users should keep the default.

table_api_base

OneLake Delta table API base URL. Most users should keep the default.

storage_token

Optional separate Azure Storage token or token-provider function. Supply it when token is fixed and Fabric item lookup is needed.

warehouse

Warehouse GUID, exact display name, or one Warehouse object returned by fabric_warehouses().

table

Table name, or a record containing a name, table, or displayName field. A record can also supply schema.

schema

Schema containing table. Defaults to the Lakehouse default schema when available, otherwise "dbo".

enrich_fabric

For fabric_lakehouse_table(), also list the Fabric table inventory to enrich the result. Defaults to FALSE, so a complete discovered item needs only a Storage token. Setting TRUE requires both Fabric and Storage audiences; use an audience-aware provider or supply token and storage_token separately.

Value

The schema functions return a tibble with name, catalog, full_name, comment, owner, schema_id, timestamps, and the unmodified metadata record in raw. The table functions return one row with the same columns as fabric_lakehouse_tables() or fabric_warehouse_tables().

Permissions

The OneLake table API uses the Azure Storage token audience and requires permission to read the item's tables through OneLake.

References

Explore tables with OneLake catalog APIs

OneLake table APIs for Delta

Examples

if (FALSE) { # \dontrun{
workspace <- fabric_workspaces()[[1L]]
lakehouse <- fabric_lakehouses(workspace)[[1L]]

schemas <- fabric_lakehouse_schemas(lakehouse)
orders <- fabric_lakehouse_table(lakehouse, "orders", schema = "dbo")
} # }