加入子查询时,我的别名附近的语法不正确?
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我的代码如下。我收到错误“关键字'otb'附近的语法不正确”(第48行)和“关键字'otb_ly'附近的语法不正确”
我不知道这意味着什么!因为加入我的两个子查询(我将其命名为otb和otb_ly)对我来说是有意义的。
子查询本身就可以正常工作。
declare @snapLY table (hotel_id tinyint, import_date date)
insert into @snapLY select hotel_id, max(import_date) from [UKRMC].[dbo].[block_res]
where import_date <= convert(date, DATEADD(day, 1, DATEADD(year, -1, GETDATE()) ) )
group by hotel_id
select otb.sita,
otb.month_TY,
otb.year_TY,
otb.Market_segment,
otb.rn_TY as OTB_rn_TY,
otb.rev_TY as OTB_rev_TY
--otb_ly.rev_LY as OTB_rev_LY,
--otb_ly.rn_LY as OTB_rn_LY
(
select contacts.sita,
data.hotel_id,
data.month_TY
,data.year_TY
,Market_segment = seg.SEG
,rn_TY = ISNULL(datatwo.rn_TY,0)
,rev_TY = ISNULL(datatwo.rev_TY, 0)
from (
SELECT hotel_id, datename(month, DATEARRIVED) as month_TY, datename(year, DATEARRIVED) year_TY
FROM [UKRMC].[dbo].[revenue] rev
JOIN [UKRMC].[dbo].[contacts] contacts on rev.hotel_id = contacts.ID
WHERE DATEARRIVED BETWEEN DATEADD(MONTH, DATEDIFF(MONTH, '19000101', GETDATE()), '19000101') -- first day of the month
AND DATEADD(MONTH, 5, DATEADD(DAY,-DAY(DATEADD(MONTH, 1, GETDATE())), DATEADD(MONTH, 1, GETDATE()))) -- 6 months later
and sita not like '%GLARR%'
group by hotel_id, datename(month, DATEARRIVED), datename(year, DATEARRIVED)
) data
cross join (
select SEG
from [UKRMC].[dbo].[Segmentation]
where SEG in ('RAC', 'BIT', 'BIQ', 'CBI', 'TOF', 'QOF', 'BAO', 'FIT', 'LYO', 'RER', 'OTH', 'NRG', 'XXX', 'CRW', 'BGR', 'BGO', 'LGR', 'LGS')
) seg
left join (
SELECT hotel_id, market_segment, datename(month, DATEARRIVED) month_TY, datename(year, DATEARRIVED) year_TY, sum(AMTROOM) as rev_TY, sum(STAYDAYS) as rn_TY
FROM [UKRMC].[dbo].[revenue] revtwo
WHERE DATEARRIVED BETWEEN DATEADD(MONTH, DATEDIFF(MONTH, '19000101', GETDATE()), '19000101') -- first day of the month
AND DATEADD(MONTH, 5, DATEADD(DAY,-DAY(DATEADD(MONTH, 1, GETDATE())), DATEADD(MONTH, 1, GETDATE()))) -- 6 months later
AND hotel_id != 61 --not GLARR, id taken from contacts table
GROUP BY hotel_id, datename(month, DATEARRIVED), datename(year, DATEARRIVED), market_segment
) datatwo on data.hotel_id = datatwo.hotel_id and seg.SEG = datatwo.market_segment and data.month_TY = datatwo.month_TY and data.year_TY = datatwo.year_TY
join [UKRMC].[dbo].[contacts] contacts on contacts.id = data.hotel_id
) otb
LEFT JOIN
(
SELECT sita, market_seg, month_LY, year_LY, sum(rev_LY) as rev_LY, sum(rn_LY) as rn_LY
FROM (
SELECT block.hotel_id, SITA
,datename(month,stay_date) as month_LY
,datename(year, stay_date) as year_LY
,sum(rev_room) as rev_LY
,sum(quantity) as rn_LY
,market_seg
FROM [UKRMC].[dbo].[block_res] block
JOIN @snapLY spit on block.hotel_id = spit.hotel_id and block.import_date = spit.import_date
JOIN [UKRMC].[dbo].[Contacts] contacts on block.hotel_id = contacts.ID
WHERE stay_date >= DATEADD(year, -1, DATEADD(MONTH, DATEDIFF(MONTH, '19000101', GETDATE()), '19000101'))
--stay_date >= DATEADD(year, -1, getdate())
and stay_date <= DATEADD(year, -1, DATEADD(MONTH, 5, DATEADD(DAY,-DAY(DATEADD(MONTH, 1, GETDATE())), DATEADD(MONTH, 1, GETDATE()))))
group by sita, market_seg, block.hotel_id, datename(month,stay_date),datename(year, stay_date)
UNION ALL
SELECT revenue.HOTEL_ID, SITA
,datename(month,DATEARRIVED) as month_LY
,datename(year,DATEARRIVED) as year_LY
,sum(AMTROOM) as rev_LY
,sum(STAYDAYS) as rn_LY
,market_segment
FROM [UKRMC].[dbo].[revenue] revenue
JOIN [UKRMC].[dbo].[Contacts] contacts on revenue.HOTEL_ID = contacts.ID
JOIN @snapLY spit on revenue.HOTEL_ID = spit.hotel_id
WHERE DATEARRIVED between DATEADD(year, -1, DATEADD(MONTH, DATEDIFF(MONTH, '19000101', GETDATE()), '19000101'))
and DATEADD(day, -1, DATEADD(year, -1, getdate()))
and DATEARRIVED < spit.import_date
GROUP BY sita, revenue.HOTEL_ID, datename(month,DATEARRIVED), datename(year,DATEARRIVED), market_segment
) union_LY
GROUP BY sita, market_seg, hotel_id, month_LY, year_LY
) otb_ly
on otb.sita = otb_ly.sita and otb.Market_segment = otb_ly.market_seg and otb.month_LY = otb_ly.month_LY and otb.year_LY = otb_ly.year_LY
答案
你错过了第14行的FROM
:
...
--otb_ly.rn_LY as OTB_rn_LY
FROM
(
...
老实说,这个问题需要大量的返工......这真的很难理解。
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