Snowpark Connect for Apache Spark in Action
On-Demand
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Unlock the full potential of Snowflake with our ongoing Power Up Series, your fast track to mastering the platform's most transformative features.
Tired of managing Spark clusters, dealing with version conflicts, moving data between platforms and wrestling with infrastructure overhead? We'll show you how Snowpark Connect for Apache Spark lets you run your existing Spark workloads directly on Snowflake's platform.
Built on Spark Connect, this feature allows Apache Spark clients like PySpark to seamlessly connect to the Snowflake platform. You can execute all your modern Apache Spark DataFrame, Spark SQL, and user-defined function (UDF) code directly against your data (in Snowflake, Iceberg Tables, or external storage) using Snowpark execution.
In this session, you will:
Understand how Snowpark Connect leverages Spark Connect to bridge your Apache Spark applications with the Snowflake engine
Watch live demos of Apache Spark code — including DataFrames, SQL, and UDFs — running directly on Snowflake’s managed compute
Learn about the compatibility tooling in the SMA to find the best workloads and how to connect your existing Apache Spark DataFrame applications to Snowflake
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