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Support Databricks in SQLDatabase #4702

Merged
merged 14 commits into from
May 19, 2023
2 changes: 1 addition & 1 deletion docs/modules/chains/examples/sqlite.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@
}
},
"source": [
"Under the hood, LangChain uses SQLAlchemy to connect to SQL databases. The `SQLDatabaseChain` can therefore be used with any SQL dialect supported by SQLAlchemy, such as MS SQL, MySQL, MariaDB, PostgreSQL, Oracle SQL, and SQLite. Please refer to the SQLAlchemy documentation for more information about requirements for connecting to your database. For example, a connection to MySQL requires an appropriate connector such as PyMySQL. A URI for a MySQL connection might look like: `mysql+pymysql://user:pass@some_mysql_db_address/db_name`\n",
"Under the hood, LangChain uses SQLAlchemy to connect to SQL databases. The `SQLDatabaseChain` can therefore be used with any SQL dialect supported by SQLAlchemy, such as MS SQL, MySQL, MariaDB, PostgreSQL, Oracle SQL, Databricks and SQLite. Please refer to the SQLAlchemy documentation for more information about requirements for connecting to your database. For example, a connection to MySQL requires an appropriate connector such as PyMySQL. A URI for a MySQL connection might look like: `mysql+pymysql://user:pass@some_mysql_db_address/db_name`. To connect to Databricks, it is recommended to use the handy method `SQLDatabase.from_databricks(catalog, schema, host, api_token, (warehouse_id|cluster_id))`.\n",
"\n",
"This demonstration uses SQLite and the example Chinook database.\n",
"To set it up, follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the `.db` file in a notebooks folder at the root of this repository."
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101 changes: 101 additions & 0 deletions langchain/sql_database.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,8 @@
from sqlalchemy.exc import ProgrammingError, SQLAlchemyError
from sqlalchemy.schema import CreateTable

from langchain import utils


def _format_index(index: sqlalchemy.engine.interfaces.ReflectedIndex) -> str:
return (
Expand Down Expand Up @@ -110,6 +112,105 @@ def from_uri(
_engine_args = engine_args or {}
return cls(create_engine(database_uri, **_engine_args), **kwargs)

@classmethod
def from_databricks(
cls,
catalog: str,
schema: str,
host: Optional[str] = None,
api_token: Optional[str] = None,
warehouse_id: Optional[str] = None,
cluster_id: Optional[str] = None,
engine_args: Optional[dict] = None,
**kwargs: Any,
) -> SQLDatabase:
"""
Class method to create an SQLDatabase instance from a Databricks connection.
This method requires the 'databricks-sql-connector' package. If not installed,
it can be added using `pip install databricks-sql-connector`.

Args:
catalog (str): The catalog name in the Databricks database.
schema (str): The schema name in the catalog.
host (Optional[str]): The Databricks workspace hostname, excluding
'https://' part. If not provided, it attempts to fetch from the
environment variable 'DATABRICKS_HOST'. If still unavailable and if
running in a Databricks notebook, it defaults to the current workspace
hostname. Defaults to None.
api_token (Optional[str]): The Databricks personal access token for
accessing the Databricks SQL warehouse or the cluster. If not provided,
it attempts to fetch from 'DATABRICKS_API_TOKEN'. If still unavailable
and running in a Databricks notebook, a temporary token for the current
user is generated. Defaults to None.
warehouse_id (Optional[str]): The warehouse ID in the Databricks SQL. If
provided, the method configures the connection to use this warehouse.
Cannot be used with 'cluster_id'. Defaults to None.
cluster_id (Optional[str]): The cluster ID in the Databricks Runtime. If
provided, the method configures the connection to use this cluster.
Cannot be used with 'warehouse_id'. If running in a Databricks notebook
and both 'warehouse_id' and 'cluster_id' are None, it uses the ID of the
cluster the notebook is attached to. Defaults to None.
engine_args (Optional[dict]): The arguments to be used when connecting
Databricks. Defaults to None.
**kwargs (Any): Additional keyword arguments for the `from_uri` method.

Returns:
SQLDatabase: An instance of SQLDatabase configured with the provided
Databricks connection details.

Raises:
ValueError: If 'databricks-sql-connector' is not found, or if both
'warehouse_id' and 'cluster_id' are provided, or if neither
'warehouse_id' nor 'cluster_id' are provided and it's not executing
inside a Databricks notebook.
"""
try:
from databricks import sql # noqa: F401
except ImportError:
raise ValueError(
"databricks-sql-connector package not found, please install with"
" `pip install databricks-sql-connector`"
)
context = None
try:
from dbruntime.databricks_repl_context import get_context

context = get_context()
except ImportError:
pass

default_host = context.browserHostName if context else None
if host is None:
host = utils.get_from_env("host", "DATABRICKS_HOST", default_host)

default_api_token = context.apiToken if context else None
if api_token is None:
api_token = utils.get_from_env(
"api_token", "DATABRICKS_API_TOKEN", default_api_token
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)

if warehouse_id is None and cluster_id is None:
if context:
cluster_id = context.clusterId
else:
raise ValueError(
"Need to provide either 'warehouse_id' or 'cluster_id'."
)

if warehouse_id and cluster_id:
raise ValueError("Can't have both 'warehouse_id' or 'cluster_id'.")

if warehouse_id:
http_path = f"/sql/1.0/warehouses/{warehouse_id}"
else:
http_path = f"/sql/protocolv1/o/0/{cluster_id}"

uri = (
f"databricks://token:{api_token}@{host}?"
f"http_path={http_path}&catalog={catalog}&schema={schema}"
)
return cls.from_uri(database_uri=uri, engine_args=engine_args, **kwargs)

@property
def dialect(self) -> str:
"""Return string representation of dialect to use."""
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