Real-Time Analytics on Your Lakehouse

-- Real-time revenue by product category (1-minute granularity)
CREATE PIPELINE revenue_by_category AS
SELECT
  product_category,
  window_start as minute,
  SUM(order_total) as revenue,
  COUNT(DISTINCT user_id) as unique_customers,
  COUNT(*) as order_count,
  AVG(order_total) as avg_order_value
FROM TABLE(
  TUMBLE(
    TABLE orders,
    DESCRIPTOR(order_time),
    INTERVAL '1' MINUTE
  )
)
GROUP BY product_category, window_start, window_end
INTO iceberg.analytics.revenue_by_category_1min;

-- Active users in the last 5 minutes (continuously updated)
CREATE PIPELINE active_users AS
SELECT
  window_end as calculated_at,
  COUNT(DISTINCT user_id) as active_users,
  COUNT(*) as total_events
FROM TABLE(
  HOP(
    TABLE page_views,
    DESCRIPTOR(event_time),
    INTERVAL '1' MINUTE,
    INTERVAL '5' MINUTE
  )
)
GROUP BY window_start, window_end
INTO iceberg.analytics.active_users_5min;