A thin wrapper around pyhive for creating a DBAPI connection to an interactive Databricks cluster.
Install using pip install databricks-dbapi
The connect() function returns a pyhive Hive connection object, which internally wraps a thrift connection.
Using a Databricks API token (recommended):
import os
from databricks_dbapi import databricks
token = os.environ["DATABRICKS_TOKEN"]
host = os.environ["DATABRICKS_HOST"]
# host = <account_name>.cloud.databricks.com
cluster = os.environ["DATABRICKS_CLUSTER"]
connection = databricks.connect(
host=host,
cluster=cluster,
token=token,
)
cursor = connection.cursor()
cursor.execute("SELECT * FROM some_table LIMIT 100")
print(cursor.fetchone())
print(cursor.fetchall())Using your username and password (not recommended):
import os
from databricks_dbapi import databricks
user = os.environ["DATABRICKS_USER"]
password = os.environ["DATABRICKS_PASSWORD"]
host = os.environ["DATABRICKS_HOST"]
# host = <account_name>.cloud.databricks.com
cluster = os.environ["DATABRICKS_CLUSTER"]
connection = databricks.connect(
host=host,
cluster=cluster,
user=user,
password=password
)
cursor = connection.cursor()
cursor.execute("SELECT * FROM some_table LIMIT 100")
print(cursor.fetchone())
print(cursor.fetchall())The pyhive connection also provides async functionality:
import os
from databricks_dbapi import databricks
from TCLIService.ttypes import TOperationState
token = os.environ["DATABRICKS_TOKEN"]
host = os.environ["DATABRICKS_HOST"]
# host = <account_name>.cloud.databricks.com
cluster = os.environ["DATABRICKS_CLUSTER"]
connection = databricks.connect(
host=host,
cluster=cluster,
token=token,
)
cursor = connection.cursor()
cursor.execute("SELECT * FROM some_table LIMIT 100", async_=True)
status = cursor.poll().operationState
while status in (TOperationState.INITIALIZED_STATE, TOperationState.RUNNING_STATE):
logs = cursor.fetch_logs()
for message in logs:
print(message)
# If needed, an asynchronous query can be cancelled at any time with:
# cursor.cancel()
status = cursor.poll().operationState
print(cursor.fetchall())
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