Given is a table with articles. The following exemplary table contains one article in different variations:
ID ARTICLE_NUMBER STORE_ID COUNTRY TYPE VALID_FROM
----------------------------------------------------------------
100 1 22 DE A 2015-11-01
101 1 22 DE A 2015-11-02
102 1 22 DE A 2015-11-03
103 1 22 DE A 2015-11-04
104 1 22 DE B 2015-11-10
105 1 22 DE B 2015-11-11
106 1 22 DE B 2015-11-11
What I need is a query which returns just the ID of the article with
article_number = 1 AND
store_id = 22 AND
country = 'DE' AND
the latest valid_from timestamp.
So far, the query should return ID = 105 or 106 (both have the same valid_from date, but I want only the one or the other in my result, no matter which, but not both). AND: because there are two types for this article (A + B), I also need ID = 103 in my result set.
How must the query look like?
You could try the HAVING parameter in your filter and selecting MAX(ID)
Or with a subselect:
SELECT [Type],(SELECT TOP(1) ID from dbo.articles S WHERE S.[Type] = A.Type AND S.Valid_From = MAX(A.Valid_From))
FROM dbo.articles A
WHERE
ARTICLE_NUMBER = 1
AND STORE_ID = 22
AND Country = 'DE'
-- AND Valid_FROM = (SELECT MAX(VALID_FROM) FROM dbo.articles)
GROUP BY [Type]
Related
I have a table t with
ORD_DATE
ORD_ID
ORD_REF
ORD_TYPE1
ORD_TYPE2
PRODNUM
PRODQUAL
PRICE
2020-09-01
101
101
ORDER
ORDER
456
F
555
2020-09-02
102
101
CONF
ORDER
456
F
555
2020-11-30
103
102
ORDER
ORDER
123
K
444
2020-12-01
104
102
CONF
ORDER
123
K
444
2020-12-01
105
103
ORDER
ORDER
123
K
444
2020-12-01
106
104
ORDER
ORDER
123
K
333
2020-12-02
107
104
CONF
ORDER
123
K
333
2020-12-08
108
104
CONF
RETURN
123
K
-333
2020-12-01
109
105
ORDER
ORDER
123
F
222
2020-12-02
110
105
CONF
ORDER
123
F
222
and a table s with:
ORD_DATE
PROD_NUMBER
PROD_QUAL
2020-12-01-00.00.00.000000
123
K
2020-12-01-00.00.00.000000
123
L
In table t are all sales per day.
A sale has 2 stages: first the order is generated when the customer buys something
("ORDER"/"ORDER"). Then it gets confirmed which is at the next day or within the next days normally ("CONF"/"ORDER"). If a customer sends the product back it's a return ("CONF"/"RETURN").
In table s are the products that are "second hand".
if a product is in that table it means all sales from table t with
ORDER_TYPE_1 = "ORDER"
AND ORDER_TYPE_2 = "ORDER"
AND t.ORD_DATE >= s.ORD_DATE
AND t.PROD_NUMBER = s.PROD_NUMBER
AND t.PROD_QUAL = s.PROD_QUAL
count as "second hand".
I need the sum of all "second hand" sales that are confirmed from the year 2021 and month 12. But only rows with CONF/ORDER or CONF/RETURN should be in the calculation. I have CAL_YEAR and CAL_MONTH in table t for that (omitted for less clutter).
From table t only ORDER_REF 105 matches that and the sum would be 0 because only these 2 rows matter:
| 2020-12-02 | 107 | 104 | CONF | ORDER | 123 | K | 333
| 2020-12-08 | 108 | 104 | CONF | RETURN | 123 | K | -333
My code so far:
SELECT SUM(PRICE)
FROM t
--
LEFT JOIN s
ON t.PRODNUM = s.PRODNUM
AND t.PRODQUAL = s.PRODQUAL
AND (SELECT ORD_DATE FROM t WHERE ORDER_TYPE_1 = 'ORDER' AND ORDER_TYPE_2 = 'ORDER') >= s.ORD_DATE
--
WHERE CAL_YEAR = 2021
AND CAL_MONTH = 12
AND ORDER_TYPE_1 = 'CONF'
AND ORDER_TYPE_2 IN ('ORDER', 'RETURN')
--
GROUP BY PRICE
;
SQL-Error: "single-row subquery returns more than one row
My problem is limiting the LEFT JOIN to ORDER/ORDER (so that ORDER_REF 105 is in) but only use CONF/ORDER and CONF/RETURN for the sum (so that ORDER_REF 102 is out).
Anyone can help?
The simplest way I can think of would be to do a self-join, where you join a second copy of table t aliased t2 to use for the CONF/ORDER and CONF/RETURN rows, while you use t for the ORDER/ORDER rows.
SELECT SUM(t2.PRICE)
FROM t
--
INNER JOIN t t2
ON t2.ORD_REF = t.ORD_REF
AND t2.ORDER_TYPE_1 = 'CONF'
AND t2.ORDER_TYPE_2 IN ('ORDER', 'RETURN')
--
LEFT JOIN s
ON t.PRODNUM = s.PRODNUM
AND t.PRODQUAL = s.PRODQUAL
AND t.ORD_DATE >= s.ORD_DATE
--
WHERE t.CAL_YEAR = 2021
AND t.CAL_MONTH = 12
AND t.ORDER_TYPE_1 = 'ORDER'
AND t.ORDER_TYPE_2 = 'ORDER'
;
If you need it to be more efficient, you could use analytic/window functions to pull the summed price from the CONF rows into the ORDER/ORDER row as a new column. This way it will only query table t once instead of twice.
SELECT SUM(t2.order_price_sum)
FROM (select t.*,
sum(case when ORDER_TYPE_1 = 'CONF'
AND ORDER_TYPE_2 IN ('ORDER', 'RETURN')
then t.price
else 0 end) over (partition by ord_ref) as order_price_sum
from t) t2
--
LEFT JOIN s
ON t2.PRODNUM = s.PRODNUM
AND t2.PRODQUAL = s.PRODQUAL
AND t2.ord_date >= s.ORD_DATE
--
WHERE CAL_YEAR = 2021
AND CAL_MONTH = 12
AND ORDER_TYPE_1 = 'ORDER'
AND ORDER_TYPE_2 = 'ORDER'
;
I have 3 tables:
tblEmployee
E_ID E_Name E_City
--------------------------------
101 sasa Mumbai
102 sdf California
103 trt Illinois
104 dssd Texas
105 trt Pennsylvania
106 wee Arizona
107 rer Texas
108 wqe California
109 sadd Michigan
tblGen
Tgenerate is boolean value
Emp_ID Tgenerate
--------------------
105 1
108 1
102 1
102 1
102 0
104 1
107 0
108 1
109 0
And the tblStat:
Emp_ID Status
------------------
103 Pending
107 Pending
103 Pending
101 Delivered
104 Pending
104 Pending
108 Pending
101 Delivered
105 Delivered
I have to join these 3 tables and want output like this
E_Name EmployeeID City TgenerateCount Delivered_Count Ranking
TgenerateCount is calculated for every employee. It is count of TgenerateCount having value 1, for ex 102 has 2 TgenerateCount and 109 has 0 TgenerateCount.
Delivered_Count is count of Status of those who has 'Delivered' status. For ex. 101 has 2 Delivered. I want to display every user in the output table.
Any help would be greatly appreciated.
As your two fact tables have a many:1 relationship with your dimension table, you should aggregate them before joining them.
SELECT
e.*,
COALESCE(g.rows, 0) AS TgenerateCount,
COALESCE(s.rows, 0) AS DeliveredCount,
RANK() OVER (ORDER BY COALESCE(g.rows, 0) + COALESCE(s.rows,0) DESC) AS ranking
FROM
tblEmployee e
LEFT JOIN
(
SELECT E_ID, COUNT(*) AS rows FROM tblGen WHERE Tgenerate = 1 GROUP BY E_ID
)
g
ON g.E_ID = e.E_ID
LEFT JOIN
(
SELECT E_ID, COUNT(*) AS rows FROM tblStat WHERE STATUS = 'Delivered' GROUP BY E_ID
)
s
ON s.E_ID = e.E_ID
You've been unclear on how the ranking should be completed, so this simply gives an example ranking.
We just found out that the new database we have been given access to is Oracle 10g, so we are unable to use fcn like UNPIVOT.
We have a table like this..
SUBMISSION COUNTRY CPM_ID PFM_ID T_AREA CNTRY_CODE V_TYPE RES_CAT JAN_2014 FEB_2014
01-JUN-2014 USA 10 24 TEST1 USA V1 210 5 10
01-AUG-2014 UK 20 30 TEST2 UK V1 213 20 30
The desired output would look like this...
SUBMISSION COUNTRY CPM_ID PFM_ID T_AREA CNTRY_CODE V_TYPE RES_CAT MONTH VALUE
01-JUN-2014 USA 10 24 TEST1 USA V1 210 01-JAN-2014 5
01-JUN-2014 USA 10 24 TEST1 USA V1 210 01-FEB-2014 10
01-AUG-2014 UK 20 30 TEST2 UK V1 213 01-JAN-2014 20
01-AUG-2014 UK 20 30 TEST2 UK V1 213 01-FEB-2014 30
I am working with a query like this...but I cannot get the month column to come out right...
select *
from (select t.submission,
t.country,
t.cpm_id,
t.pfm_id,
t.t_area,
t.cntry_code,
t.v_type,
t.res_cat,
(case
when n.n = 1 then JAN-2014
when n.n = 1 then FEB-2014 end) as value
from table1 t cross join
(select FEB_2014 as n from dual union all
select FEB_2014 from dual) n
) s
where value is not null;
Thanks for your help,
I would do:
select t.submission,
t.country,
t.cpm_id,
t.pfm_id,
t.t_area,
t.cntry_code,
t.v_type,
t.res_cat,
n.d,
case when n.d = '01-JAN-2014' then t.jan_2014 else t.feb_2014 end value
from table1 t
cross join
(
select '01-JAN-2014' d from dual
union all
select '01-FEB-2014' d from dual
) n;
I have a table with IDs and primary information. I also have two delta tables keyed on ID and date of change. I need to build a view that merges these three tables together indicating all changes over time.
Main Table:
ID Name
-- ------------------
1 Bob Jones
2 Dave Smith
First Attribute Table:
ID Date Attr1
-- ---------- -----
1 01/01/2013 25
1 02/15/2013 33
1 02/17/2013 47
1 03/02/2013 58
2 02/01/2013 1
...
Second Attribute Table
ID Date Attr2
-- ---------- -----
1 01/01/2013 ABC
1 01/05/2013 DEF
1 01/15/2013 RST
1 02/10/2013 XYZ
1 02/15/2013 Foo
1 03/05/2013 Blah
2 02/01/2013 Two
...
Based on that data, for Bob Jones, I need the view to return the following:
ID Name Date Attr1 Attr2
-- ----------- ---------- ----- -----
1 Bob Jones 01/01/2013 25 ABC
1 Bob Jones 01/05/2013 25 DEF
1 Bob Jones 01/15/2013 25 RST
1 Bob Jones 02/10/2013 25 XYZ
1 Bob Jones 02/15/2013 33 Foo
1 Bob Jones 02/17/2013 47 Foo
1 Bob Jones 03/02/2013 58 Foo
1 Bob Jones 03/05/2013 58 Blah
I tried outer joining the attribute tables to get all change values ordered by date and then used an outer join on the entire query with itself to get "prior" records:
with qry as (
select
rownum = ROW_NUMBER() OVER (ORDER BY m.ID, a.DATE),
m.ID,
m.Name,
a.DATE,
a.Attr1,
a.Attr2
from Main m
inner join (
select
COALESCE(a1.ID, a2.ID) as ID,
COALESCE(a1.LOAD_DATE, a2.LOAD_DATE) as LOAD_DATE,
a1.Attr1,
a2.Attr2
from Attributes1 a1
full outer join Attributes2 a2
on (a1.ID = a2.ID and a1.DATE = a2.DATE)
) a on (a.ID = m.ID)
)
select
COALESCE(qry.ID, prev.ID) as ID,
COALESCE(qry.Name, prev.Name) as Name,
COALESCE(qry.DATE, prev.DATE) as DATE,
COALESCE(qry.Attr1, prev.Attr1) as Attr1,
COALESCE(qry.Attr2, prev.Attr2) as Attr2,
from qry
left join qry prev
on (prev.rownum = qry.rownum - 1)
order by ID, DATE
However, that doesn't work when one attribute table changes quicker than the other because the attributes that didn't change are null in the results of the attribute table join and if two nulls show up back-to-back, the coalesce will return a null when I need the last non-null value that was in that column.
Can this even be done in a view in SQL Server 2012?
I need some help. I need to take the data from these 3 tables and create an output that looks like below. The plan_name_x and pending_tallyx columns are derived to make one line per claim id. Each claim id can be associated to up to 3 plans and I want to show each plan and tally amounts in one record. What is the best way to do this?
Thanks for any ideas. :)
Output result set needed:
claim_id ac_name plan_name_1 pending_tally1 plan_name_2 Pending_tally2 plan_name_3 pending_tally3
-------- ------- ----------- -------------- ----------- -------------- ----------- --------------
1234 abc cooks delux_prime 22 prime_express 23 standard_prime 2
2341 zzz bakers delpux_prime 22 standard_prime 2 NULL NULL
3412 azb pasta's prime_express 23 NULL NULL NULL NULL
SQL Server 2005 table to use for the above result set:
company_claims
claim_id ac_name
1234 abc cooks
2341 zzz bakers
3412 azb pasta's
claim_plans
claim_id plan_id plan_name
1234 101 delux_prime
1234 102 Prime_express
1234 103 standard_prime
2341 101 delux_prime
2341 103 standard_prime
3412 102 Prime_express
Pending_amounts
claim_id plan_id Pending_tally
1234 101 22
1234 102 23
1234 103 2
2341 101 22
2341 103 2
3412 102 23
If you know that 3 is always the max amount of plans then some left joins will work fine:
select c.claim_id, c.ac_name,
cp1.plan_name as plan_name_1, pa1.pending_tally as pending_tally1,
cp2.plan_name as plan_name_2, pa2.pending_tally as pending_tally2,
cp3.plan_name as plan_name_3, pa3.pending_tally as pending_tally3,
from company_claims c
left join claim_plans cp1 on c.claim_id = cp1.claim_id and cp1.planid = 101
left join claim_plans cp2 on c.claim_id = cp2.claim_id and cp2.planid = 102
left join claim_plans cp3 on c.claim_id = cp3.claim_id and cp3.planid = 103
left join pending_amounts pa1 on cp1.claim_id = pa1.claimid and cp1.planid = pa1.plainid
left join pending_amounts pa2 on cp2.claim_id = pa2.claimid and cp2.planid = pa2.plainid
left join pending_amounts pa3 on cp3.claim_id = pa3.claimid and cp3.planid = pa3.plainid
I would first join all your data so that you get the relevant columns: claim_id, ac_name, plan_name, pending tally.
Then I would add transform this to get plan name and plan tally on different rows, with a label tying them together.
Then it should be easy to pivot.
I would tie these together with common table expressions.
Here's the query:
with X as (
select cc.*, cp.plan_name, pa.pending_tally,
rank() over (partition by cc.claim_id order by plan_name) as r
from company_claims cc
join claim_plans cp on cp.claim_id = cc.claim_id
join pending_amounts pa on pa.claim_id = cp.claim_id
and pa.plan_id = cp.plan_id
), P as (
select
X.claim_id,
x.ac_name,
x.plan_name as value,
'plan_name_' + cast(r as varchar(max)) as label
from x
union all
select
X.claim_id,
x.ac_name,
cast(x.pending_tally as varchar(max)) as value,
'pending_tally' + cast(r as varchar(max)) as label
from x
)
select claim_id, ac_name, [plan_name_1], [pending_tally1],[plan_name_2], [pending_tally2],[plan_name_3], [pending_tally3]
from (select * from P) p
pivot (
max(value)
for label in ([plan_name_1], [pending_tally1],[plan_name_2], [pending_tally2],[plan_name_3], [pending_tally3])
) as pvt
order by pvt.claim_id, ac_name
Here's a fiddle showing it in action: http://sqlfiddle.com/#!3/68f62/10