snowflake-load-scale

# Snowflake Load & Scale ## Overview Load testing, scaling strategies, and capacity planning for Snowflake workloads using warehouse sizing, multi-cluster configuration, and concurrent query simulation. ## Scaling Model | Dimension | How to Scale | When | |-----------|-------------|------| | Single query speed | Scale UP (bigger warehouse) | Complex queries, large scans | | Concurrent queries | Scale OUT (multi-cluster) | Many users, dashboard refresh | | Data volume | Scale UP + clustering | Tables > 1TB | | Mixed workloads | Separate warehouses | ETL + analytics on same data | ## Instructions ### Step 1: Benchmark Current Performance ```sql -- Baseline metrics for critical queries -- Run each query 3 times and record results -- Disable result cache for accurate benchmarking ALTER SESSION SET USE_CACHED_RESULT = FALSE; -- Test query 1: Point lookup SELECT * FROM orders WHERE order_id = 12345; -- Test query 2: Aggregation SELECT DATE_TRUNC('month', order_date) AS month, COUNT(*) AS orders, SUM(amount) AS revenue FROM orders WHERE order_date >= '2025-01-01' GROUP BY month ORDER BY month; -- Test query 3: Join + filter SELECT c.name, SUM(o.amount) AS total_spend FROM customers c JOIN orders o ON c.id = o.customer_id WHERE o.order_date >= DATEADD(days, -90, CURRENT_DATE()) GROUP BY c.name ORDER BY total_spend DESC LIMIT 100; -- Record results SELECT query_id, query_text, warehouse_name, warehouse_size, total_elapsed_time / 1000 AS seconds, bytes_...