Manage lakehouse in Microsoft Fabric with REST API

Article
09/05/2024

The Microsoft Fabric Rest API provides service endpoint for the CRUD operation of a Fabric item. The following actions are available for the Lakehouse:

Action	Description
Create	Creates a lakehouse inside a workspace. A SQL analytics endpoint also gets provisioned along with the lakehouse.
Update	Updates the name of a lakehouse and the SQL analytics endpoint.
Delete	Deletes lakehouse and the associated SQL analytics endpoint.
Get properties	Gets the properties of a lakehouse and the SQL analytics endpoint.
List tables	List tables in the lakehouse.
Table load	Creates delta tables from CSV and parquet files and folders.
Table maintenance	Apply bin-compaction, V-Order, and removal of unreferenced and old files.

Prerequisites

To use the Fabric REST API, you first need to get a Microsoft Entra token for Fabric service. Then use that token in the authorization header of the API call.
Microsoft Fabric Rest API defines a unified endpoint for operations. The endpoint is https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items. The placeholders {workspaceId} and {lakehouseId} should be replaced with the appropriate values when issuing the commands exemplified in this article.

Lakehouse CRUD

Use the following API to perform creation, modifications, and removal of the lakehouse inside a workspace.

Create a lakehouse

Request:

POST https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items 
{ 
    "displayName": "demo", 
    "type": "Lakehouse" 
}

Response:

{
    "id": "56c6dedf-2640-43cb-a412-84faad8ad648", 
    "type": "Lakehouse", 
    "displayName": "demo", 
    "description": "", 
    "workspaceId": "fc67689a-442e-4d14-b3f8-085076f2f92f" 
}

Update a lakehouse

Update the description and rename the Lakehouse.

Request:

PATCH https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/dc39f96a-47d7-4c2d-9358-740f50c0aa31 
{ 
    "displayName": "newname", 
    "description": "Item's New description" 
}

Response:

{ 
    "id": "56c6dedf-2640-43cb-a412-84faad8ad648", 
    "type": "Lakehouse", 
    "displayName": "newname", 
    "description": "", 
    "workspaceId": "fc67689a-442e-4d14-b3f8-085076f2f92f" 
}

Get lakehouse properties

Request:

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}

Response:

{ 
    "id": "daaa77c7-9ef4-41fc-ad3c-f192604424f5", 
    "type": "Lakehouse", 
    "displayName": "demo", 
    "description": "", 
    "workspaceId": "bee6c118-c2aa-4900-9311-51546433bbb8", 
    "properties": { 
        "oneLakeTablesPath": "https://onelake.dfs.fabric.microsoft.com/{workspaceId}/{lakehouseId}/Tables", 
        "oneLakeFilesPath": "https://onelake.dfs.fabric.microsoft.com/{workspaceId}/{lakehouseId}/Files", 
        "sqlEndpointProperties": { 
            "connectionString": "A1bC2dE3fH4iJ5kL6mN7oP8qR9-C2dE3fH4iJ5kL6mN7oP8qR9sT0uV-datawarehouse.pbidedicated.windows.net", 
            "id": "0dfbd45a-2c4b-4f91-920a-0bb367826479", 
            "provisioningStatus": "Success" 
        } 
    } 
}

Delete a lakehouse

When you delete a lakehouse, the object metadata and data are deleted. Shortcut references are deleted, but the data is preserved at the target.

Request:

DELETE https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{lakehouseId}

Response: Empty

List tables in a Lakehouse

Request:

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/tables

Response:

{ 
    "continuationToken": null, 
    "continuationUri": null, 
    "data": [ 
        { 
            "type": "Managed", 
            "name": "demo1", 
            "location": "abfss://c522396d-7ac8-435d-8d77-442c3ff21295@onelake.dfs.fabric.microsoft.com/{workspaceId}/Tables/demo1", 
            "format": "delta" 
        } 
    ] 
}

The list tables API supports pagination. Provide maxResults per page as a parameter to the request and the API responds with the continuation URI that can be used to get the next page of results.

Pagination example

Request:

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/tables?maxResults=1

Response:

{ 
    "continuationToken": "+RID:~HTsuAOseYicH-GcAAAAAAA==#RT:1#TRC:1#ISV:2#IEO:65567#QCF:8#FPC:AgKfAZ8BnwEEAAe8eoA=", 
    "continuationUri": "https://api.fabric.microsoft.com:443/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/tables?continuationToken=%2BRID%3A~HTsuAOseYicH-GcAAAAAAA%3D%3D%23RT%3A1%23TRC%3A1%23ISV%3A2%23IEO%3A65567%23QCF%3A8%23FPC%3AAgKfAZ8BnwEEAAe8eoA%3D", 
    "data": [ 
        { 
            "type": "Managed", 
            "name": "nyctaxismall", 
            "location": "abfss://bee6c118-c2aa-4900-9311-51546433bbb8@onelake.dfs.fabric.microsoft.com/daaa77c7-9ef4-41fc-ad3c-f192604424f5/Tables/nyctaxismall", 
            "format": "delta" 
        } 
    ] 
}

Load to tables

This API surfaces the capabilities of the Load to Tables lakehouse feature. With this API, it's possible to load CSV and parquet files to new or existing delta lake tables in the lakehouse.

This API is asynchronous, so three steps are required:

Upload files and folders to Lakehouse's Files section using OneLake APIs.
Submit load to tables API request.
Track the status of the operation until completion.

The Following sections assume the files were already uploaded.

Load to tables API request

The mode parameter supports overwrite and append operations. pathType parameter specified if loading individual files or all files from specified folder. Both CSV and parquet are supported as the file format parameter.

This example uploads a CSV file named demo.csv into an existing table named demo.

Request:

POST https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/tables/demo/load 
{ 
    "relativePath": "Files/demo.csv", 
    "pathType": "File", 
    "mode": "overwrite", 
    "formatOptions": 
    { 
        "header": true, 
        "delimiter": ",", 
        "format": "CSV" 
    } 
}

The response header contains the URI to poll the status of the asynchronous operations. The URI is in the Location variable of the response header.

The Location variable contains an URI as following: https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/operations/32ad6d2a-82bb-420d-bb57-4620c8860373. The guid 32ad6d2a-82bb-420d-bb57-4620c8860373 is the operation ID to query the status of running load to tables operations as described in the next section.

Monitoring Load to tables operations

After capturing the operationId from the response of the load to tables API request, execute the following request:

Request:

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/lakehouses/{lakehouseId}/operations/{operationId}

Response:

{ 
    "Status": 3, 
    "CreatedTimeUtc": "", 
    "LastUpdatedTimeUtc": "", 
    "PercentComplete": 100, 
    "Error": null 
}

Possible operation status for load to tables:

1 - Operation not started
2 - Running
3 - Success
4 - Failed

Table maintenance

This API surfaces the capabilities of the Lakehouse table maintenance feature. With this API, it's possible to apply bin-compaction, V-Order, and unreferenced old files cleanup.

This API is asynchronous, so two steps are required:

Submit table maintenance API request.
Track the status of the operation until completion.

Table maintenance API request

This example executes a table maintenance job that applies V-Order to a table, while also applying Z-Order to the tipAmount column and executing the VACUUM operation with a retention of seven days and one hour.

Request:

POST https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{lakehouseId}/jobs/instances?jobType=TableMaintenance
{
    "executionData": {
        "tableName": "{table_name}",
        "optimizeSettings": {
            "vOrder": true,
            "zOrderBy": [
                "tipAmount"
            ]
        },
        "vacuumSettings": {
            "retentionPeriod": "7.01:00:00"
        }
    }
}

The response header contains the URI to poll the status of the asynchronous operations. The URI is in the Location variable of the response header.

The Location variable contains an URI as following: https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{lakehouseId}/jobs/instances/f2d65699-dd22-4889-980c-15226deb0e1b. The guid f2d65699-dd22-4889-980c-15226deb0e1b is the operation ID to query the status of running table maintenance operations as described in the next section.

Monitoring table maintenance operations

After capturing operationId from the response of the load to tables API request, execute the following request:

Request:

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{lakehouseId}/jobs/instances/{operationId}

Response:

{
    "parameters": {
        "workspaceId": "{workspaceId}",
        "itemId": "{lakehouseId}",
        "jobInstanceId": "{operationId}"
    },
    "responses": {
        "200": {
            "body": {
                "id": "{operationId}",
                "itemId": "431e8d7b-4a95-4c02-8ccd-6faef5ba1bd7",
                "jobType": "DefaultJob",
                "invokeType": "Manual",
                "status": "Completed",
                "rootActivityId": "8c2ee553-53a4-7edb-1042-0d8189a9e0ca",
                "startTimeUtc": "2023-04-22T06:35:00.7812154",
                "endTimeUtc": "2023-04-22T06:35:00.8033333",
                "failureReason": null
            }
        }
    }
}

Possible operation status for table maintenance:

NotStarted - Job not started
InProgress - Job in progress
Completed - Job completed
Failed - Job failed
Canceled - Job canceled
Deduped - An instance of the same job type is already running and this job instance is skipped

Load to Tables Lakehouse feature.
Use table maintenance feature to manage delta tables in Fabric.
Delta Lake table optimization and V-Order.

Share via

Manage lakehouse in Microsoft Fabric with REST API

Prerequisites

Lakehouse CRUD

Create a lakehouse

Update a lakehouse

Get lakehouse properties

Delete a lakehouse

List tables in a Lakehouse

Load to tables

Load to tables API request

Monitoring Load to tables operations

Table maintenance

Table maintenance API request

Monitoring table maintenance operations

Feedback

Additional resources

Share via

Manage lakehouse in Microsoft Fabric with REST API

Prerequisites

Lakehouse CRUD

Create a lakehouse

Update a lakehouse

Get lakehouse properties

Delete a lakehouse

List tables in a Lakehouse

Pagination example

Load to tables

Load to tables API request

Monitoring Load to tables operations

Table maintenance

Table maintenance API request

Monitoring table maintenance operations

Related content

Feedback

Additional resources