Snowflake Development
Category: Engineering Domain: Data Warehouse
Overview
The Snowflake Development skill provides tools for analyzing and optimizing Snowflake SQL queries, recommending warehouse sizing, and enforcing Snowflake-specific best practices. Helps data engineers reduce costs and improve query performance.
Clarify First
Before analyzing or sizing, confirm these inputs. If any is unknown or vague, ASK — do not assume:
- Action — analyze / optimize / warehouse-sizing (
--action; selects the workflow) - SQL file or query — the specific query(ies) to optimize (
--file; the subject of the analysis) - Workload type & data volume — ETL / BI / ad-hoc and the GB scale (
--workload/--data-volume; drives the warehouse recommendation)
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Quick Start
# Analyze a Snowflake SQL file for optimization opportunities
python scripts/snowflake_query_helper.py --file queries.sql --action analyze
# Get warehouse sizing recommendations
python scripts/snowflake_query_helper.py --action warehouse-sizing --workload "etl" --data-volume "500GB"
# Optimize a specific query
python scripts/snowflake_query_helper.py --file slow_query.sql --action optimize
Tools Overview
| Tool | Purpose | Key Flags |
|---|---|---|
snowflake_query_helper.py | Analyze, optimize Snowflake SQL and recommend warehouse sizes | --file, --action, --workload, --data-volume |
Workflows
Query Performance Optimization
- Collect slow queries from query history
- Run analyzer to identify optimization opportunities
- Apply recommended changes
- Compare before/after execution plans
Warehouse Right-Sizing
- Identify workload type (ETL, BI, ad-hoc, etc.)
- Run warehouse-sizing with data volume
- Review recommendations
- Implement multi-cluster settings if applicable
Reference Documentation
- Snowflake Best Practices - Query patterns, warehouse management, cost optimization
Common Patterns
Cost Reduction
- Right-size warehouses (don't use XL for small queries)
- Set auto-suspend to 60 seconds for ad-hoc warehouses
- Use materialized views for frequently accessed aggregations
- Partition large tables with clustering keys
- Avoid SELECT * in production queries