Data Engineering simplified with Snowpark for Python on Snowflake
summary
Snowpark for Python runs native DataFrame operations in Snowflake, converts the DAG to optimized SQL and executes it 100% pushdown and parallel execution across cluster nodes; server-side runtimes spawn per call to run third‑party libraries (code is bundled with cloudpickle-packaged model and staged), dependencies come from 1300+ Anaconda packages, training can run as a Python stored procedure next to terabytes of data, models land in an internal stage and score via SQL-callable UDFs used by a Streamlit dashboard.
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chapters (9)
- 0:00Introduction
- 5:37What is Snowpark
- 8:53Snowpark for Python
- 13:45Client vs server execution
- 19:00Data frame API
- 20:03Live demo: ad spend
- 27:26Scaling model training
- 28:29Deploying models
- 29:55Q&A
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