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Databricks​

Databricks now offer a native DB API 2.0 driver, databricks-sql-connector, that can be used with the sqlalchemy-databricks dialect. You can install both with:

pip install "superset[databricks]"

To use the Hive connector you need the following information from your cluster:

  • Server hostname
  • Port
  • HTTP path

These can be found under "Configuration" -> "Advanced Options" -> "JDBC/ODBC".

You also need an access token from "Settings" -> "User Settings" -> "Access Tokens".

Once you have all this information, add a database of type "Databricks Native Connector" and use the following SQLAlchemy URI:

databricks+connector://token:{access_token}@{server_hostname}:{port}/{database_name}

You also need to add the following configuration to "Other" -> "Engine Parameters", with your HTTP path:

{
    "connect_args": {"http_path": "sql/protocolv1/o/****"},
    "http_headers": [["User-Agent", "Apache Superset"]]
}

The User-Agent header is optional, but helps Databricks identify traffic from Superset. If you need to use a different header please reach out to Databricks and let them know.

Older driver​

Originally Superset used databricks-dbapi to connect to Databricks. You might want to try it if you're having problems with the official Databricks connector:

pip install "databricks-dbapi[sqlalchemy]"

There are two ways to connect to Databricks when using databricks-dbapi: using a Hive connector or an ODBC connector. Both ways work similarly, but only ODBC can be used to connect to SQL endpoints.

Hive​

To connect to a Hive cluster add a database of type "Databricks Interactive Cluster" in Superset, and use the following SQLAlchemy URI:

databricks+pyhive://token:{access_token}@{server_hostname}:{port}/{database_name}

You also need to add the following configuration to "Other" -> "Engine Parameters", with your HTTP path:

{"connect_args": {"http_path": "sql/protocolv1/o/****"}}

ODBC​

For ODBC you first need to install the ODBC drivers for your platform.

For a regular connection use this as the SQLAlchemy URI after selecting either "Databricks Interactive Cluster" or "Databricks SQL Endpoint" for the database, depending on your use case:

databricks+pyodbc://token:{access_token}@{server_hostname}:{port}/{database_name}

And for the connection arguments:

{"connect_args": {"http_path": "sql/protocolv1/o/****", "driver_path": "/path/to/odbc/driver"}}

The driver path should be:

  • /Library/simba/spark/lib/libsparkodbc_sbu.dylib (Mac OS)
  • /opt/simba/spark/lib/64/libsparkodbc_sb64.so (Linux)

For a connection to a SQL endpoint you need to use the HTTP path from the endpoint:

{"connect_args": {"http_path": "/sql/1.0/endpoints/****", "driver_path": "/path/to/odbc/driver"}}