Skip to main content

Use Pre-Computed Statistics

Leverage time-series aggregation tables for efficient analytics.

Anti-Pattern​

# BAD: Computing trends from raw events
query GetPriceHistory($termId: String!) {
  share_price_changes(
    where: { term_id: { _eq: $termId } }
    order_by: { created_at: asc }
  ) {
    created_at
    old_price
    new_price
  }
}
# Then computing daily aggregates in application code

Best Practice​

# GOOD: Using pre-computed daily statistics
query GetDailyPriceStats($termId: String!, $curveId: numeric!) {
  share_price_change_stats_daily(
    where: {
      term_id: { _eq: $termId }
      curve_id: { _eq: $curveId }
    }
    order_by: { bucket: desc }
    limit: 30
  ) {
    bucket
    first_share_price
    last_share_price
    difference
    change_count
  }
}

Available Tables​

  • share_price_change_stats_hourly/daily/weekly/monthly
  • signal_stats_hourly/daily/monthly

Benefits​

  1. Faster queries: Pre-aggregated data
  2. Less computation: Done server-side
  3. Smaller payloads: Aggregated vs raw data
  4. Better UX: Faster dashboard loading