我在BigQuery中设计了一个视图，它引用了其他视图和Google表格 . 根据我的经验，在bigquery中查询google sheet会增加大约30秒的时间，即使它是单行，但我找不到任何文档来解释这一点 . 该视图由4个CTE组成，它们都引用其他视图和google工作表，视图中的SQL大约需要48秒才能运行 .
当我将SQL保存为视图，并执行Select * from视图时，查询无法完成，它运行大约10分钟，然后给出错误“执行期间遇到错误 . 重试可能会解决问题 . ”
我理解查询视图的视图是混乱的，但是我可以在编辑器中查询视图而没有问题（只需要一分钟），为什么将它保存为视图并查询更有问题？
这是查询：
#standardSQL
with spends as (SELECT y.course,cast(concat(cast(extract (YEAR from date)as string),"-",cast(extract(MONTH from date)as string),"-01")as date)as month,sum(spend) as spend fROM `project.dataset.view1` x
left join (select * from `project.dataset.table1`) as y
on x.account_id = y.id
group by 1,2),
forecasts as (select * from `project.dataset.google_sheet1`),
cds as (select course, sum(spend)/7 as current_daily_spend from (SELECT y.course,
case when date between DATE_SUB(current_date(), interval 7 DAY) and DATE_SUB(current_date(), interval 1 DAY) then sum(spend) else null end AS spend
fROM `project.dataset.view1` x
left join (select * from `project.dataset.table1`) as y
on x.account_id = y.id
group by date,y.course)
group by course),
yesterday as (select course, sum(spend) as yesterday_spend from (SELECT y.course,
case when date = DATE_SUB(current_date(), interval 1 DAY) then sum(spend) else null end AS spend
fROM `project.dataset.view1` x
left join (select * from `project.dataset.table1`) as y
on x.account_id = y.id
group by date,y.course)
group by course)
Select forecasts.*,spends.spend,cds.current_daily_spend,yesterday.yesterday_spend from forecasts
left join spends
on forecasts.month = spends.month and forecasts.course = spends.course
left join cds
on spends.course = cds.course
left join yesterday
on spends.course = yesterday.course