You are working with DoorDash order and delivery-request data. Write SQL to answer the questions below. Tables: 1. `orders` - `order_id` BIGINT, primary key - `customer_id` BIGINT - `merchant_id` BIGINT - `dasher_id` BIGINT, nullable until assigned - `created_at_utc` TIMESTAMP, when the order was placed - `delivered_at_utc` TIMESTAMP, when the order was delivered; null if not delivered - `order_status` VARCHAR, values include `completed`, `cancelled`, and `refunded` 2. `delivery_requests` - `request_id` BIGINT, primary key - `order_id` BIGINT, foreign key to `orders.order_id` - `dasher_id` BIGINT, Dasher who received the offer - `requested_at_utc` TIMESTAMP, when the offer/request was sent - `offer_amount_cents` INTEGER, guaranteed offer amount shown to the Dasher - `request_status` VARCHAR, values include `accepted`, `declined`, `expired`, and `cancelled` Relationship and assumptions: - One order can have zero or more delivery requests. - Requests for the same order should be ordered by `requested_at_utc`, breaking ties by `request_id`. - Analyze completed orders whose `created_at_utc` falls in a parameterized window `[start_ts_utc, end_ts_utc)`. - All timestamps are stored in UTC. If a business-day filter is needed, convert to the `America/Los_Angeles` timezone before filtering. - Parameters: `late_threshold_minutes` and `request_threshold`. Questions: 1. Calculate the percentage of completed orders that were late, where a late order is defined as an order whose delivery time is more than `late_threshold_minutes` after `created_at_utc`. - Required output columns: `total_completed_orders`, `late_orders`, `pct_late_orders`. 2. Calculate the percentage of completed orders that had at least `request_threshold` delivery requests. Also calculate the average number of delivery requests per completed order. - Include completed orders with zero requests in the denominator. - Required output columns: `total_completed_orders`, `orders_with_at_least_threshold_requests`, `pct_orders_with_at_least_threshold_requests`, `avg_requests_per_order`. 3. Calculate the percentage of completed orders that had at least one offer increase. An offer increase occurs when a request's `offer_amount_cents` is greater than the immediately previous request's `offer_amount_cents` for the same order. - Also calculate the average percentage offer increase across positive increase events, defined as `(current_offer_amount_cents - previous_offer_amount_cents) / previous_offer_amount_cents`. - Exclude transitions where the previous offer amount is null or zero from the percentage-increase calculation. - Required output columns: `total_completed_orders`, `orders_with_offer_increase`, `pct_orders_with_offer_increase`, `avg_pct_offer_increase`. Return one query or a set of queries that produces these outputs.