28 lines
1.2 KiB
SQL
28 lines
1.2 KiB
SQL
--explain analyze
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select dayscale.dt
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,sum (c.cost/dayscale.monthdays), count(*)
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--,w.line_key, w.dt_from, w.dt_to, w.line_version, w.agreement_version, w.deal_status_id, w.contract, w.probability_pc
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from
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elma.mv_dt dayscale
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left outer join (SELECT *,
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coalesce((LEAD(dt_from) OVER (PARTITION BY line_key ORDER BY dt_from, agreement_version,line_version)), (select max(dt) from elma.mv_dt)) dt_next
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FROM
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(
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SELECT *,
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MIN(dt_from) OVER (PARTITION BY line_key ORDER BY agreement_version desc,line_version desc) running_min_dt
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FROM elma.mv_line where siv_is_actual
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) t
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WHERE t.dt_from=t.running_min_dt) w on (dayscale.dt >=w.dt_from AND dayscale.dt <w.dt_next)
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join elma.mv_component c on (w.siv_uid=c.siv_uid)
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left outer join elma.mv_line b on
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(w.line_key = b.line_key AND dayscale.dt >= b.dt_from
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AND b.agreement_version = (select max(agreement_version) from elma.mv_line i where i.line_key = w.line_key AND dayscale.dt >= i.dt_from AND (w.agreement_version>i.agreement_version OR w.agreement_version IS NULL)))
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where dayscale.dt between '2025-01-01' AND '2025-03-10'
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--AND w.line_key='20241009T112450304'
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--AND b.deal_status_id IN ('5','6')
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group by dayscale.dt
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order by dayscale.dt
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