**Performance Optimization Strategies:**

**Indexing for Analytics:**

- Index all ORDER BY columns used in window functions

- Composite indexes for PARTITION BY + ORDER BY combinations

- Consider covering indexes for frequently accessed columns

- Example: CREATE INDEX idx_sales_date_amount ON sales(date, amount);

**Query Structure:**

- Use CTEs to break complex calculations into logical steps

- Avoid deeply nested window functions

- Pre-filter data with WHERE clauses before analytics

- Consider materialized views for frequently accessed complex calculations

**Memory Management:**

- Statistical functions require full dataset scan

- PERCENTILE_CONT needs to sort entire partition

- Monitor work_mem settings for large datasets

- Consider partitioning large tables by date/category

**Execution Plan Analysis:**

- Use EXPLAIN ANALYZE to identify bottlenecks

- Look for expensive Sort operations

- WindowAgg nodes show window function processing

- Hash Aggregate indicates grouping operations

**Best Practices:**

- Limit data range with date filters when possible

- Use appropriate precision for PERCENTILE_CONT

- Cache results in materialized views for dashboards

- Test performance with production-sized datasets

**Example Optimization:**

```sql

-- Slow: No indexes, full table scan

SELECT CORR(sales, marketing_spend) FROM monthly_data;

-- Fast: With proper index

CREATE INDEX idx_monthly_sales_marketing ON monthly_data(sales, marketing_spend);

SELECT CORR(sales, marketing_spend) FROM monthly_data;

-- Optimal: Pre-filtered with materialized view

CREATE MATERIALIZED VIEW recent_correlations AS

SELECT

department,

CORR(sales, marketing_spend) as sales_marketing_corr,

STDDEV(sales) as sales_volatility

FROM monthly_data