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Snowflake Spark Connect Python Client

pip install snowflake-spark-connect

Usage

from snowflake.sparkconnect import SparkSession

spark = SparkSession.builder.getOrCreate()

spark.sql("SELECT 1").show()
spark.stop()

getOrCreate() starts a Spark Connect session in Snowflake, returning once the session is ready for us.

Builder options

Authentication

Use exactly one of the following authentication options when creating a session to customize the connection.

Method What it does
(nothing) getOrCreate() returns the default connection in the environment
.snowpark_session(session) Use an existing Snowpark session object
.connection("prod") Named profile from ~/.snowflake/connections.toml
.remote(account=..., ...) Snowflake connection parameters (see below)

Once a Spark Connect session is established, token refresh happens in the background to ensure the session stays authenticated.

Session lifetime

Option Meaning
.idlettl(timedelta(...)) Stop the Spark server after this much idle time
.sessionttl(timedelta(...)) Hard cap on total session lifetime
.tokenttl(timedelta(...)) Lifetime of each Spark Connect JWT used for authentication
spark_idlettl / spark_sessionttl / spark_tokenttl inside .remote(...) Same TTLs, passed as Snowflake kwargs

Database and schema

Spark Connect sessions must be started with a database and schema. .database(name) and .schema(name) on the builder can be used to specify a database and schema combination to use; an exception is raised if only one is provided. When neither is set, the user's personal database USER$<current user>.PUBLIC is used by default.

Option Meaning
.database(name) Use this Snowflake database for the Spark Connect server
.schema(name) Use this Snowflake schema for the Spark Connect server

Explicit .database(...) and .schema(...) values always override database/schema from a connection, configuration, or supplied/active Snowpark session.

.remote(**kwargs) Snowflake parameters

These are the same parameters as snowpark-python.

Spark-specific kwargs:

Parameter Notes
spark_idlettl / spark_sessionttl / spark_tokenttl Same as .idlettl() / .sessionttl() / .tokenttl()

Metadata

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