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After the initial Spark work, the Databricks-specific features were
becoming more entwined in the code. There have been requests for
additional Databricks-specific features such as CloudFetch, Entra
authentication, and LZ4 compression to name a few.
This PR moves the Databricks-specific code out of the Spark driver and
into its own driver. It leverages the Thrift and Spark libraries that
exist in the Apache driver but teases out the Databricks capabilities
from the Spark capabilities. It does so by exposing the internals of the
Apache driver so that the Databricks driver can leverage the same
underlying libraries while still being able to offer differentiating
features and raises the branding of the driver from under the
Apache/Spark umbrella to the same level as BigQuery, FlightSQL, and
Snowflake.
---------
Co-authored-by: David Coe <>
Co-authored-by: Bruce Irschick <[email protected]>
Copy file name to clipboardExpand all lines: csharp/src/Drivers/Apache/Spark/README.md
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@@ -26,7 +26,7 @@ but can also be passed in the call to `AdbcDatabase.Connect`.
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| Property | Description | Default |
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| :--- | :--- | :--- |
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|`adbc.spark.type`| (Required) Indicates the Spark server type. One of `databricks`,`http` (future: `standard`) ||
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|`adbc.spark.type`| (Required) Indicates the Spark server type. Currently only`http` (future: `standard`) ||
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|`adbc.spark.auth_type`| An indicator of the intended type of authentication. Allowed values: `none`, `username_only`, `basic`, and `token`. This property is optional. The authentication type can be inferred from `token`, `username`, and `password`. If a `token` value is provided, token authentication is used. Otherwise, if both `username` and `password` values are provided, basic authentication is used. ||
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|`adbc.spark.host`| Host name for the data source. Do not include scheme or port number. Example: `sparkserver.region.cloudapp.azure.com`||
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|`adbc.spark.port`| The port number the data source listens on for a new connections. |`443`|
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The following table depicts how the Spark ADBC driver converts a Spark type to an Arrow type and a .NET type:
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### Spark on Databricks
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| Spark Type | Arrow Type | C# Type |
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| :--- | :---: | :---: |
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| ARRAY*| String | string |
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| BIGINT | Int64 | long |
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| BINARY | Binary | byte[]|
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| BOOLEAN | Boolean | bool |
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| CHAR | String | string |
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| DATE | Date32 | DateTime |
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| DECIMAL | Decimal128 | SqlDecimal |
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| DOUBLE | Double | double |
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| FLOAT | Float | float |
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| INT | Int32 | int |
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| INTERVAL_DAY_TIME+ | String | string |
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| INTERVAL_YEAR_MONTH+ | String | string |
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| MAP*| String | string |
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| NULL | Null | null |
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| SMALLINT | Int16 | short |
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| STRING | String | string |
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| STRUCT*| String | string |
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| TIMESTAMP | Timestamp | DateTimeOffset |
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| TINYINT | Int8 | sbyte |
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| UNION | String | string |
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| USER_DEFINED | String | string |
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| VARCHAR | String | string |
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### Apache Spark over HTTP (adbc.spark.data_type_conv = ?)
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| Spark Type | Arrow Type (`none`) | C# Type (`none`) | Arrow Type (`scalar`) | C# Type (`scalar`) |
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## Supported Variants
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### Spark on Databricks
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Support for Spark on Databricks is the most mature.
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The Spark ADBC driver supports token-based authentiation using the
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[Databricks personal access token](https://docs.databricks.com/en/dev-tools/auth/pat.html).
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Basic (username and password) authenication is not supported, at this time.
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