Snowpark Connect for Spark enables developers to run their Spark workloads directly to Snowflake using the Spark Connect protocol. This approach decouples the client and server, allowing Spark code to run remotely against Snowflake's compute engine without managing a Spark cluster. It offers a streamlined way to integrate Snowflake's governance, security, and scalability into Spark-based workflows, supporting a familiar PySpark experience with pushdown optimizations into Snowflake.

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Credits

Author: Snowflake, Inc

License

Apache License, Version 2.0

Requires

Python <3.13, >=3.10

Provides Extra

jdk iceberg

Tags

snowflake snowpark connect spark

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This release

1.40.0 This release

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Yanked reason: Critical: Version 1.0.0 contains a bug that may overwrite additional stage folders when the overwrite path does not end with trailing forward slash. Example: Providing the path as /test-bucket instead of /test-bucket/ will also overwrite /test-bucket-1, /test-bucket-2, etc. instead of only /test-bucket.

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Yanked reason: Version 0.30.0 has been yanked (removed from indexing) due to a critical bug that can cause failure of server spin up. Action Required: Please upgrade to 0.30.1 or newer version. Do not install or use this yanked version. We apologize for the inconvenience.

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