Databricks Data Connector

Databricks Data Connector Documentation

Databricks as a connector for federated SQL query against Databricks using Spark Connect, directly from Delta Lake tables, or using the SQL Statement Execution API.

datasets:
  - from: databricks:spiceai.datasets.my_awesome_table # A reference to a table in the Databricks unity catalog
    name: my_delta_lake_table
    params:
      mode: delta_lake
      databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
      databricks_token: ${secrets:my_token}
      databricks_aws_access_key_id: ${secrets:aws_access_key_id}
      databricks_aws_secret_access_key: ${secrets:aws_secret_access_key}

Configuration

`from`

The from field for the Databricks connector takes the form databricks:catalog.schema.table where catalog.schema.table is the fully-qualified path to the table to read from.

`name`

The dataset name. This will be used as the table name within Spice.

Example:

datasets:
  - from: databricks:spiceai.datasets.my_awesome_table
    name: cool_dataset
    params: ...

SELECT COUNT(*) FROM cool_dataset;

+----------+
| count(*) |
+----------+
| 6001215  |
+----------+

`params`

Use the secret replacement syntax to reference a secret, e.g. ${secrets:my_token}.

Parameter Name	Description
`mode`	The execution mode for querying against Databricks. The default is `spark_connect`. Possible values: `spark_connect`: Use Spark Connect to query against Databricks. Requires a Spark cluster to be available. `delta_lake`: Query directly from Delta Tables. Requires the object store credentials to be provided.
`databricks_endpoint`	The endpoint of the Databricks instance. Required for both modes.
`databricks_sql_warehouse_id`	The ID of the SQL Warehouse in Databricks to use for the query. Only valid when `mode` is `sql_warehouse`.
`databricks_cluster_id`	The ID of the compute cluster in Databricks to use for the query. Only valid when `mode` is `spark_connect`.
`databricks_use_ssl`	If true, use a TLS connection to connect to the Databricks endpoint. Default is `true`.
`client_timeout`	Optional. Applicable only in `delta_lake` mode. Specifies timeout for object store operations. Default value is `30s` E.g. `client_timeout: 60s`
`databricks_token`	The Databricks API token to authenticate with the Unity Catalog API. Can't be used with `databricks_client_id` and `databricks_client_secret`.
`databricks_client_id`	The Databricks Service Principal Client ID. Can't be used with `databricks_token`.
`databricks_client_secret`	The Databricks Service Principal Client Secret. Can't be used with `databricks_token`.

Authentication

Personal access token

To learn more about how to set up personal access tokens, see Databricks PAT docs.

datasets:
  - from: databricks:spiceai.datasets.my_awesome_table
    name: my_awesome_table
    params:
      databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
      databricks_cluster_id: 1234-567890-abcde123
      databricks_token: ${secrets:DATABRICKS_TOKEN} # PAT

Databricks service principal

Spice supports the M2M (Machine to Machine) OAuth flow with service principal credentials by utilizing the databricks_client_id and databricks_client_secret parameters. The runtime will automatically refresh the token.

Ensure that you grant your service principal the "Data Reader" privilege preset for the catalog and "Can Attach" cluster permissions when using Spark Connect mode.

To Learn more about how to set up the service principal, see Databricks M2M OAuth docs.

datasets:
  - from: databricks:spiceai.datasets.my_awesome_table
    name: my_awesome_table
    params:
      databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
      databricks_cluster_id: 1234-567890-abcde123
      databricks_client_id: ${secrets:DATABRICKS_CLIENT_ID} # service principal client id
      databricks_client_secret: ${secrets:DATABRICKS_CLIENT_SECRET} # service principal client secret

Delta Lake object store parameters

Configure the connection to the object store when using mode: delta_lake. Use the secret replacement syntax to reference a secret, e.g. ${secrets:aws_access_key_id}.

AWS S3

Parameter Name	Description
`databricks_aws_region`	Optional. The AWS region for the S3 object store. E.g. `us-west-2`.
`databricks_aws_access_key_id`	The access key ID for the S3 object store.
`databricks_aws_secret_access_key`	The secret access key for the S3 object store.
`databricks_aws_endpoint`	Optional. The endpoint for the S3 object store. E.g. `s3.us-west-2.amazonaws.com`.
`databricks_aws_allow_http`	Optional. Enables insecure HTTP connections to `databricks_aws_endpoint`. Defaults to `false`.

Azure Blob

Parameter Name	Description
`databricks_azure_storage_account_name`	The Azure Storage account name.
`databricks_azure_storage_account_key`	The Azure Storage key for accessing the storage account.
`databricks_azure_storage_client_id`	The Service Principal client ID for accessing the storage account.
`databricks_azure_storage_client_secret`	The Service Principal client secret for accessing the storage account.
`databricks_azure_storage_sas_key`	The shared access signature key for accessing the storage account.
`databricks_azure_storage_endpoint`	Optional. The endpoint for the Azure Blob storage account.

Google Storage (GCS)

Parameter Name	Description
`google_service_account`	Filesystem path to the Google service account JSON key file.

Examples

Spark Connect

- from: databricks:spiceai.datasets.my_spark_table # A reference to a table in the Databricks unity catalog
  name: my_delta_lake_table
  params:
    mode: spark_connect
    databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
    databricks_cluster_id: 1234-567890-abcde123
    databricks_token: ${secrets:my_token}

SQL Warehouse

- from: databricks:spiceai.datasets.my_table # A reference to a table in the Databricks unity catalog
  name: my_table
  params:
    mode: sql_warehouse
    databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
    databricks_sql_warehouse_id: 2b4e24cff378fb24
    databricks_token: ${secrets:my_token}

Delta Lake (S3)

- from: databricks:spiceai.datasets.my_delta_table # A reference to a table in the Databricks unity catalog
  name: my_delta_lake_table
  params:
    mode: delta_lake
    databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
    databricks_token: ${secrets:my_token}
    databricks_aws_region: us-west-2 # Optional
    databricks_aws_access_key_id: ${secrets:aws_access_key_id}
    databricks_aws_secret_access_key: ${secrets:aws_secret_access_key}
    databricks_aws_endpoint: s3.us-west-2.amazonaws.com # Optional

Delta Lake (Azure Blobs)

- from: databricks:spiceai.datasets.my_adls_table # A reference to a table in the Databricks unity catalog
  name: my_delta_lake_table
  params:
    mode: delta_lake
    databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
    databricks_token: ${secrets:my_token}

    # Account Name + Key
    databricks_azure_storage_account_name: my_account
    databricks_azure_storage_account_key: ${secrets:my_key}

    # OR Service Principal + Secret
    databricks_azure_storage_client_id: my_client_id
    databricks_azure_storage_client_secret: ${secrets:my_secret}

    # OR SAS Key
    databricks_azure_storage_sas_key: my_sas_key

Delta Lake (GCP)

- from: databricks:spiceai.datasets.my_gcp_table # A reference to a table in the Databricks unity catalog
  name: my_delta_lake_table
  params:
    mode: delta_lake
    databricks_endpoint: dbc-a1b2345c-d6e7.cloud.databricks.com
    databricks_token: ${secrets:my_token}
    databricks_google_service_account_path: /path/to/service-account.json

Types

mode: delta_lake

The table below shows the Databricks (mode: delta_lake) data types supported, along with the type mapping to Apache Arrow types in Spice.

Databricks SQL Type	Arrow Type
`STRING`	`Utf8`
`BIGINT`	`Int64`
`INT`	`Int32`
`SMALLINT`	`Int16`
`TINYINT`	`Int8`
`FLOAT`	`Float32`
`DOUBLE`	`Float64`
`BOOLEAN`	`Boolean`
`BINARY`	`Binary`
`DATE`	`Date32`
`TIMESTAMP`	`Timestamp(Microsecond, Some("UTC"))`
`TIMESTAMP_NTZ`	`Timestamp(Microsecond, None)`
`DECIMAL`	`Decimal128`
`ARRAY`	`List`
`STRUCT`	`Struct`
`MAP`	`Map`

Limitations

Databricks connector (mode: delta_lake) does not support reading Delta tables with the V2Checkpoint feature enabled. To use the Databricks connector (mode: delta_lake) with such tables, drop the V2Checkpoint feature by executing the following command:
```
ALTER TABLE <table-name> DROP FEATURE v2Checkpoint [TRUNCATE HISTORY];
```
For more details on dropping Delta table features, refer to the official documentation: Drop Delta table features
When using mode: spark_connect, correlated scalar subqueries can only be used in filters, aggregations, projections, and UPDATE/MERGE/DELETE commands. Spark Docs