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snowflake-best-practices

Snowflake best practices for cloud data warehouse design, query optimization, and cost management

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Snowflake Best Practices

Warehouse Design

Sizing (CRITICAL)

  • Start small (XS or S), scale up as needed
  • Enable auto-scaling for concurrency
  • Enable auto-suspend (1 minute idle)
  • Separate warehouses for different workloads

Multi-Cluster Warehouses

  • Use for high concurrency (many users)
  • Set min/max clusters based on load
  • Scaling policy: Standard (default) or Economy

Query Optimization

Clustering Keys (CRITICAL)

  • Define clustering keys for frequently filtered columns
  • Improves micro-partition pruning
  • Monitor clustering depth
  • Automatic clustering: ALTER TABLE ... CLUSTER BY (...)

Result Caching

  • 24-hour cache for identical queries
  • Use SHOW PARAMETERS to check cache status
  • Bypass cache with query hint: /*+ NO_RESULT_CACHE */

Materialized Views

  • For repeated aggregations
  • Automatically refreshed on base table changes
  • Cost: storage + refresh compute

Data Loading

COPY INTO (CRITICAL)

  • Batch load from stages (S3/GCS/Azure)
  • File size: 100-250MB compressed (optimal)
  • Use pattern matching for multiple files

Snowpipe

  • Continuous ingestion
  • Event-driven (S3 notifications)
  • Serverless compute

Cost Optimization

Resource Monitors

  • Set credit quotas per warehouse
  • Alerts and suspend actions
  • Track consumption with WAREHOUSE_METERING_HISTORY

Storage

  • Use zero-copy cloning for dev/test
  • Time travel retention: 1 day (standard), 90 days (enterprise)
  • Fail-safe: 7 days (not configurable)

References

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