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.
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 3.7 or above is required.
For the latest documentation, see
Install the library with pip install databricks-sql-connector
Note: Don't hard-code authentication secrets into your Python. Use environment variables
export DATABRICKS_HOST=********.databricks.com
export DATABRICKS_HTTP_PATH=/sql/1.0/endpoints/****************
export DATABRICKS_TOKEN=dapi********************************
Example usage:
import os
from databricks import sql
host = os.getenv("DATABRICKS_HOST")
http_path = os.getenv("DATABRICKS_HTTP_PATH")
access_token = os.getenv("DATABRICKS_TOKEN")
connection = sql.connect(
server_hostname=host,
http_path=http_path,
access_token=access_token)
cursor = connection.cursor()
cursor.execute('SELECT * FROM RANGE(10)')
result = cursor.fetchall()
for row in result:
print(row)
cursor.close()
connection.close()
In the above example:
server-hostname
is the Databricks instance host name.http-path
is 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)personal-access-token
is the Databricks Personal Access Token for the account that will execute commands and queries
See CONTRIBUTING.md