--explain analyze
with 
status(status, status_id, probability_pc) as (VALUES
	('Закрыта неуспешно',7,0),('Закрыта успешно',6,100),('Договор подписан',5,100),('Договор на подписании',15,90),('Договор на согласовании',12,70),
	('Тестирование',8,50),('Отправлено ТКП',10,20),('Внутреннее согласование',37,10),('Проработка решения',4,10),('Сбор потребностей',1,0)
),
begin_of_scale (dt) as (values ('2025-01-01'::timestamp)), -- этот изыск не дает видимого ускорения
end_of_scale (dt) as (values ('2025-12-02'::timestamp)), -- этот изыск не дает видимого ускорения
dayscale as (
	SELECT dd::date as dt
	, DATE_PART('days', DATE_TRUNC('month', dd) + '1 MONTH'::INTERVAL - '1 DAY'::INTERVAL) monthdays 
	FROM begin_of_scale, end_of_scale, generate_series( 
	 begin_of_scale.dt
	,end_of_scale.dt
	,'1 day'::interval) dd
),
line as (
	select siv.__id as siv_uid, siv.discount, siv.type as line_pricing_model_id
	,siv.hash as line_key, siv.user_description, siv.is_actual as siv_is_actual
	,siv.version::numeric as line_version
	, GREATEST(siv.date_nop,d."_plannedDueDate")::date as dt_from
	, COALESCE(siv.date_end::date, end_of_scale.dt) as dt_to
	,siv.is_easy as is_simple, siv.cnt as quantity -- maybe should mutliply
	, a.__id as agreement_uid, a.contract_uid, a.is_actual as agreement_is_actual, a.deal_uid, a.index as agreement_version
	,d."_plannedDueDate", d.__name as deal, d.__status_status as deal_status_id
	,c.__name as contract
	,s.probability_pc
	,(select sum(p.price*p.cnt*(100-p.discount)/100) from elma.service_parametrs p where(p.__id = ANY (siv.params))) as cost
	from elma.deals_services siv
	join elma.additional_agreements a on (a.__id = ANY(siv.additional_agreement)) 
	join elma.deals d on (d.__id = ANY(siv.deal)) 
	join elma.aggrements c on (a.contract_uid = c.__id)
	join status s on (d.__status_status=s.status_id)
	cross join end_of_scale
)

select dayscale.dt
,sum (o.cost/dayscale.monthdays*o.probability_pc/100) as sum_unbounded
,sum(o.cost*o.probability_pc/100) as sum_working
,sum(o.cost_base*(100-COALESCE(o.probability_pc,0))) as sum_base
,(
	COALESCE(sum(o.cost*o.probability_pc/100),0)	
	+
	COALESCE(sum(o.cost_base*(100-COALESCE(o.probability_pc,0))),0)
	) as sum_bounded
,max(o.dt_from) as max_dt_from, max(o.dt_from_base) as max_dt_from_base, max(o.probability_pc) as max_probability_pc
,count(*)

from dayscale
LEFT OUTER JOIN (
SELECT t.*,
b.discount as discount_base, b.quantity as quantity_base, b.dt_from as dt_from_base, b.dt_to as dt_to_base, b.cost as cost_base

FROM line t 

LEFT OUTER JOIN line b on (t.line_key=b.line_key AND b.siv_uid=(
		select siv_uid 
 		FROM line where siv_is_actual AND probability_pc=100 AND agreement_is_actual AND deal_status_id in (5,6)		 
		AND ((t.agreement_version > b.agreement_version) OR (t.agreement_version = b.agreement_version AND t.line_version > b.line_version))
		ORDER BY agreement_version desc, line_version desc
		LIMIT 1
	)
) 
where 1=1
AND t.line_pricing_model_id in (1)

--AND t.line_key in ('0a61f9e4-520b-4f0a-aac0-c1d42c037e1b','0bde160d-52d0-4d55-b4e0-05f45cfd739e','08485a0c-a913-4332-bb36-e40dec27d12e','1809bb31-4d37-424b-ba2b-26b9a873af7f')
) o 
on (o.dt_from = dayscale.dt) 
group by dayscale.dt
order by dayscale.dt