semantic-view-optimization-setup

Downloading a semantic model YAML for optimization requires a fully-qualified semantic view name, Snowflake access, and a Python environment managed via uv. The process uses helper scripts to retrieve the YAML and extract components into a timestamped directory.

A semantic view optimization session is a structured workflow for auditing and debugging semantic models. It begins by downloading the YAML and extracting verified queries, custom instructions, and relationships to establish a reproducible starting point for analysis.

You set up a reproducible audit directory by running a setup process that creates a dedicated folder named semantic_view_optimization_TIMESTAMP. This directory stores the downloaded YAML and extracted components, ensuring consistent starting conditions for debugging.

Yes, you need a Python environment managed via uv to run the required helper scripts, download_semantic_view_yaml.py and semantic_view_get.py. These scripts coordinate the extraction of verified queries, tables, and relationships from the semantic model.

Yes, you can retrieve custom instructions and relationships by executing the semantic_view_get.py helper script. This script extracts these specific components alongside tables and verified queries from the downloaded semantic model YAML for downstream workflows.

You should start a new semantic view optimization run when initiating audits, debug workflows, or performance reviews. It prepares a fresh timestamped directory with the current YAML and extracted components to ensure your analysis reflects the latest model state.