Databricks

Databricks Data Connector Documentation

Databricks as a connector for federated SQL query against Databricks using Spark Connect or directly from Delta Lake tables.

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_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

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.

Azure Blob

Note

One of the following auth values must be provided for Azure Blob:

• databricks_azure_storage_account_key,

• databricks_azure_storage_client_id and azure_storage_client_secret, or

• databricks_azure_storage_sas_key.

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}

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

Memory Considerations

When using the Databricks (mode: delta_lake) Data connector without acceleration, data is loaded into memory during query execution. Ensure sufficient memory is available, including overhead for queries and the runtime, especially with concurrent queries.

Memory limitations can be mitigated by storing acceleration data on disk, which is supported by duckdb and sqlite accelerators by specifying mode: file.

• The Databricks Connector (mode: spark_connect) does not yet support streaming query results from Spark.