我一直在无奈地尝试获取以下SQL语句以返回查询结果,如果没有与查询匹配的行,则默认为0。
这是预期的结果:
vol | year
-------+------
0 | 2018
相反,我得到了:
vol | year
-----+------
(0 rows)
这是sql语句:
select coalesce(vol,0) as vol, year
from (select sum(vol) as vol, year
from schema.fact_data
join schema.period_data
on schema.fact_data.period_tag = schema.period_data.tag
join schema.product_data
on schema.fact_data.product_tag =
schema.product_data.tag
join schema.market_data
on schema.fact_data.market_tag = schema.market_data.tag
where "retailer"='MadeUpRetailer'
and "product_tag"='FakeProductTag'
and "year"='2018' group by year
) as DerivedTable;
我知道查询有效,因为它在有数据时返回数据。只是没有默认设置为0 ...
对于找到这种情况的任何帮助,将不胜感激!
答案 0 :(得分:2)
使用子查询DerivedTable
,您可以编写:
SELECT coalesce(DerivedTable.vol, 0) AS vol,
y.year
FROM (VALUES ('2018'::text)) AS y(year)
LEFT JOIN (SELECT ...) AS DerivedTable
ON DerivedTable.year = y.year;
答案 1 :(得分:1)
删除GROUP BY
(和外部查询):
select 2018 as year, coalesce(sum(vol), 0) as vol
from schema.fact_data f join
schema.period_data p
on f.period_tag = p.tag join
schema.product_data pr
on f.product_tag = pr.tag join
schema.market_data m
on fd.market_tag = m.tag
where "retailer" = 'MadeUpRetailer' and
"product_tag" = 'FakeProductTag' and
"year" = '2018';
没有GROUP BY
的聚合查询总是返回恰好一行,因此这应该做您想要的。
编辑:
查询看起来像这样:
select v.yyyy as year, coalesce(sum(vol), 0) as vol
from (values (2018), (2019)) v(yyyy) left join
schema.fact_data f
on f.year = v.yyyy left join -- this is just an example. I have no idea where year is coming from
schema.period_data p
on f.period_tag = p.tag left join
schema.product_data pr
on f.product_tag = pr.tag left join
schema.market_data m
on fd.market_tag = m.tag
group by v.yyyy
但是,您必须将where
条件移动到适当的on
子句。我不知道这些列从哪里来。
答案 2 :(得分:0)
根据您发布的代码,您不清楚在哪个表中有year
列。
如果该表中没有2018年的行,则可以使用UNION仅获取1行,如下所示:
select sum(vol) as vol, year
from schema.fact_data innrt join schema.period_data
on schema.fact_data.period_tag = schema.period_data.tag
inner join schema.product_data
on schema.fact_data.product_tag = schema.product_data.tag
inner join schema.market_data
on schema.fact_data.market_tag = schema.market_data.tag
where
"retailer"='MadeUpRetailer' and
"product_tag"='FakeProductTag' and
"year"='2018'
group by "year"
union
select 0 as vol, '2018' as year
where not exists (
select 1 from tablename where "year" = '2018'
)
如果2018年有行,那么第二个查询将不会获取任何内容,