I have the table in sql db like this.
Category Series Value
1 A 100
2 B 200
2 C 300
How do I select to project like this?
Category Series Value
1 A 100
1 B 0
1 C 0
2 A 0
2 B 200
2 C 300
In order to get the result, you will want to generate a list of all categories with each series. You can use a CROSS JOIN to get the result:
select distinct c.category, s.series
from yourtable s
cross join yourtable c
Once you have this, then you can join this back to your table on both the category and series:
select sc.category,
sc.series,
coalesce(t.value, 0) value
from
(
select distinct c.category, s.series
from yourtable s
cross join yourtable c
) sc
left join yourtable t
on sc.series = t.series
and sc.category = t.category;
See SQL Fiddle with Demo
Related
I am unable to generate a looping kind of behaviour in a SQL query.
I am having two tables:
Table A
Id Brand Prod_Id Alt_Prod_Id
1 A 2 5
2 B 3 9
3 C 5 9
Table B
Id Prod_Id Rate
1 2 5
2 3 9
2 5 7
2 9 9
Rate in Table B needs to be looked up for each brands Prod_ID & Alt_Prod_Id & select the least value between 2 found value
The expected result / output is:
Brand Min_Prod_Val
A 5
B 9
C 7
Can this be done in a query?
Thanks!
You could join tableb twice (once for prod_id, another for alt_prod_id), and then select the smallest rate:
select
a.brand,
least(b1.rate, b2.rate) min_prod_val
from tablea a
inner join tableb b1 on b1.prod_id = a.prod_id
inner join tableb b2 on b2.prod_id = a.alt_prod_id
It is unclear which database you are using. If that's SQL Server: it does not support least(), so you need a case expression:
case when b1.rate < b2.rate then b1.rate else b2.rate end min_prod_val
You can use a single join and GROUP BY the brand:
SELECT a.Brand,
MIN( b.rate ) AS min_prod_val
FROM TableA A
INNER JOIN TableB b
ON ( b.prod_id IN ( a.prod_id, a.alt_prod_id ) )
GROUP BY a.Brand
Or you can use a correlated sub-query:
SELECT a.Brand,
(
SELECT MIN( rate )
FROM TableB b
WHERE b.prod_id IN ( a.prod_id, a.alt_prod_id )
) AS min_prod_val
FROM TableA A
db<>fiddle
The data like
mdn day flag
c 20180302 0
c 20180303 1
b 20180303 0
a 20180301 1
b 20180301 0
a 20180302 1
I get the whole by select distinct mdn from data, and left join every day, how to realize it by using hive? As following, it's only one day sample:
with temp as (select distinct mdn from data)
select * from temp b
left outer join
(select * from data where day=20180302) a
on a.mdn=b.mdn
The result of one day like:
c c 20180302 0
a a 20180302 1
b null null null
Exactly, it is just one day, and I want to get 'b null 20180302 null'
Use a cross join to generate all the combinations:
select m.mdn, d.day, data.flag
from (select distinct mdn from data) m cross join
(select distinct day from data) d left join
data
on data.mdn = m.mdn and data.day = d.day ;
I have following table
ID Name Stage
1 A 1
1 B 2
1 C 3
1 A 4
1 N 5
1 B 6
1 J 7
1 C 8
1 D 9
1 E 10
I need output as below with parameters A and N need to select closest rows where difference between stage is smallest
ID Name Stage
1 A 4
1 N 5
I need to select rows where difference between stage is smallest
This query can make use of an index on (name, stage) efficiently:
WITH cte AS (
SELECT TOP 1
a.id AS a_id, a.name AS a_name, a.stage AS a_stage
, n.id AS n_id, n.name AS n_name, n.stage AS n_stage
FROM tbl a
CROSS APPLY (
SELECT TOP 1 *, stage - a.stage AS diff
FROM tbl
WHERE name = 'N'
AND stage >= a.stage
ORDER BY stage
UNION ALL
SELECT TOP 1 *, a.stage - stage AS diff
FROM tbl
WHERE name = 'N'
AND stage < a.stage
ORDER BY stage DESC
) n
WHERE a.name = 'A'
ORDER BY diff
)
SELECT a_id AS id, a_name AS name, a_stage AS stage FROM cte
UNION ALL
SELECT n_id, n_name, n_stage FROM cte;
SQL Server uses CROSS APPLY in place of standard-SQL LATERAL.
In case of ties (equal difference) the winner is arbitrary, unless you add more ORDER BY expressions as tiebreaker.
dbfiddle here
This solution works, if u know the minimum difference is always 1
SELECT *
FROM myTable as a
CROSS JOIN myTable as b
where a.stage-b.stage=1;
a.ID a.Name a.Stage b.ID b.Name b.Stage
1 A 4 1 N 5
Or simpler if u don't know the minimum
SELECT *
FROM myTable as a
CROSS JOIN myTable as b
where a.stage-b.stage in (SELECT min (a.stage-b.stage)
FROM myTable as a
CROSS JOIN myTable as b)
I'm querying an access db from excel. I have a table similar to this one:
id Product Count
1 A 0
1 B 5
3 C 0
2 A 0
2 B 0
2 C 5
3 A 6
3 B 5
3 C 7
From which I'd like to return all the rows (including the ones where count for that product is 0) where the sum of the count for this ID is not 0 and the product is either A or B. So from the above table, I would get:
id Product Count
1 A 0
1 B 5
3 A 6
3 B 5
The following query gives the right output, but is quite slow (takes almost a minute when querying from a somewhat small 7k row db), so I was wondering if there is a more efficient way of doing it.
SELECT *
FROM [BD$] BD
WHERE (BD.Product='A' or BD.Product='B')
AND BD.ID IN (
SELECT BD.ID
FROM [BD$] BD
WHERE (Product='A' or Product='B')
GROUP BY BD.ID
HAVING SUM(BD.Count)<>0)
Use your GROUP BY approach in a subquery and INNER JOIN that back to the [BD$] table.
SELECT BD2.*
FROM
(
SELECT BD1.ID
FROM [BD$] AS BD1
WHERE BD1.Product IN ('A','B')
GROUP BY BD1.ID
HAVING SUM(BD1.Count) > 0
) AS sub
INNER JOIN [BD$] AS BD2
ON sub.ID = BD2.ID;
IN() statement can perform badly a lot of times, you can try EXISTS() :
SELECT * FROM [BD$] BD
WHERE BD.Product in('A','B')
AND EXISTS(SELECT 1 FROM [BD$] BD2
WHERE BD.id = BD2.id
AND BD2.Product in('A','B')
AND BD2.Count > 0)
If you are looking for the records where the sum of the count for the id is non-zero, then at least one non-unique id must have a count that is non-zero.
SELECT *
FROM [BD$] BD
WHERE BD.Product IN ('A', 'B')
AND BD.ID IN (
SELECT DISTINCT b.ID
FROM [BD$] b
WHERE b.Product IN ('A', 'B')
AND b.Count<>0
)
The question is:
Two tables (t1, t2)
Table t1:
SELLER | NON_SELLER
A B
A C
A D
B A
B C
B D
C A
C B
C D
D A
D B
D C
Table t2:
SELLER | COUPON | BAL
A 9 100
B 9 200
C 9 300
D 9 400
A 9.5 100
B 9.5 20
A 10 80
Using SELECT Statement to get this result:
SELLER| COUPON | SUM(BAL)
A 9 900
B 9 800
C 9 700
D 9 600
A 9.5 20
B 9.5 100
C 9.5 120
D 9.5 120
A 10 0 # !!!
B 10 80
C 10 80
D 10 80
For seller A SUM(BAL) means sum( B.BAL,C.BAL,D.BAL), for B, SUM(BAL)=SUM(A.BAL,C.BAL,D.BAL)...
Please find a way with good performance and don't use temporary table.
My solution:
Running this query will get the result but without the row "A 10 0":
select t1.seller, t2.coupon, sum(bal)
from t1, t2
where t1.non_seller = t2.seller
group by t1.seller, t2.coupon
order by t2.coupon
Please help ~~~~~~
If I understand you correctly, you're looking for data on all sellers and all coupons. So let's start with a cross join that generates a list of coupons and sellers:
select sellers.seller
, coupons.coupon
from (
select distinct seller
from Table2
) as sellers
cross join
(
select distinct coupon
from Table2
) as coupons
For each seller-coupon combination, you're looking for the sum they can buy from other sellers. This can be accomplished by a left join:
select sellers.seller
, coupons.coupon
, case when sum(t2.bal) is null then 0 else sum(t2.bal) end
from (
select distinct seller
from Table2
) as sellers
cross join
(
select distinct coupon
from Table2
) as coupons
left join
Table2 t2
on t2.seller <> sellers.seller
and t2.coupon = coupons.coupon
group by
sellers.seller
, coupons.coupon
The only function of the case statement is to replace a null sum with a 0.
The output matches the one in your answer. Note that this solution doesn't use Table1: the list of other sellers is produced by the t2.seller <> sellers.seller condition in the left join.
I get another way to this:
select t1.seller, t2.coupon, sum(bal)
from t1, t2
where t1.non_seller = t2.seller
group by t1.seller, t2.coupon
union
(select seller,coupon,0 from t2 group by coupon having count(seller) == 1);
And I don't know if it is better or worst than compare with #Andomar :
select sellers.seller
, coupons.coupon
, case when sum(t2.bal) is null then 0 else sum(t2.bal) end
from (
select distinct seller
from Table2
) as sellers
cross join
(
select distinct coupon
from Table2
) as coupons
left join
Table2 t2
on t2.seller <> sellers.seller
and t2.coupon = coupons.coupon
group by
sellers.seller
, coupons.coupon