The Databricks SQL Connector for Python allows you to develop Python applications that connect to Databricks clusters and SQL warehouses. It is a Thrift-based client with no dependencies on ODBC or JDBC. It conforms to the Python DB API 2.0 specification and exposes a SQLAlchemy dialect for use with tools like pandas and alembic which use SQLAlchemy to execute DDL. Use pip install databricks-sql-connector[sqlalchemy] to install with SQLAlchemy's dependencies. pip install databricks-sql-connector[alembic] will install alembic's dependencies.
This connector uses Arrow as the data-exchange format, and supports APIs to directly fetch Arrow tables. Arrow tables are wrapped in the ArrowQueue class to provide a natural API to get several rows at a time.
You are welcome to file an issue here for general use cases. You can also contact Databricks Support here.
Python 3.8 or above is required.
For the latest documentation, see
Install the library with pip install databricks-sql-connector
export DATABRICKS_HOST=********.databricks.com
export DATABRICKS_HTTP_PATH=/sql/1.0/endpoints/****************Example usage:
import os
from databricks import sql
host = os.getenv("DATABRICKS_HOST")
http_path = os.getenv("DATABRICKS_HTTP_PATH")
connection = sql.connect(
server_hostname=host,
http_path=http_path)
cursor = connection.cursor()
cursor.execute('SELECT :param `p`, * FROM RANGE(10)', {"param": "foo"})
result = cursor.fetchall()
for row in result:
print(row)
cursor.close()
connection.close()In the above example:
server-hostnameis the Databricks instance host name.http-pathis the HTTP Path either to a Databricks SQL endpoint (e.g. /sql/1.0/endpoints/1234567890abcdef), or to a Databricks Runtime interactive cluster (e.g. /sql/protocolv1/o/1234567890123456/1234-123456-slid123)
Note: This example uses Databricks OAuth U2M to authenticate the target Databricks user account and needs to open the browser for authentication. So it can only run on the user's machine.
See CONTRIBUTING.md