I'm trying to fetch the most recent record and find a non-NULL match. The problem is my subquery returns more than one result.
Data set
| ID | DD | SIG_ID | DCRP |
----------------------------------------
| 1 | 2010-06-01 | 1 | Expert |
| 2 | 2010-09-01 | 1 | Expert |
| 3 | 2010-12-01 | 1 | Expert |
| 4 | 2010-12-01 | 1 | Expert II |
| 5 | 2011-03-01 | 1 | Expert II |
| 6 | 2011-06-01 | 1 | (null) |
| 7 | 2010-06-01 | 2 | Senior |
| 8 | 2010-09-01 | 2 | Senior |
| 9 | 2010-09-01 | 2 | Senior |
| 10 | 2010-12-01 | 2 | Senior II |
| 11 | 2011-03-01 | 2 | (null) |
| 12 | 2011-03-01 | 2 | Senior |
| 13 | 2010-06-01 | 3 | (null) |
| 14 | 2010-09-01 | 3 | (null) |
| 15 | 2010-12-01 | 3 | (null) |
Query
SELECT a.sig_id, a.id,
CASE
WHEN b.dcrp IS NULL
THEN
(SELECT dcrp
FROM tbl
WHERE sig_id = a.sig_id
AND id < a.id
AND dcrp IS NOT NULL)
ELSE b.dcrp
END AS dcrp
FROM
(SELECT sig_id, MAX(id) id
FROM tbl
GROUP BY sig_id) a
LEFT JOIN
(SELECT id, dcrp
FROM tbl
WHERE dcrp IS NOT NULL) b ON b.id = a.id
Desired result
Fetch the most recent dcrp for each sig_id:
| ID | DD | SIG_ID | DCRP |
----------------------------------------
| 5 | 2011-03-01 | 1 | Expert II |
| 12 | 2011-03-01 | 2 | Senior |
| 15 | 2010-12-01 | 3 | (null) |
SQL Fiddle
You can use the following:
;WITH CTE AS
(
SELECT *, ROW_NUMBER() OVER(PARTITION BY SIG_ID
ORDER BY CASE WHEN DCRP IS NOT NULL THEN 0 ELSE 1 END,
DD DESC) RN
FROM tbl
)
SELECT *
FROM CTE
WHERE RN = 1
And the fiddle.
;with si as (
select distinct sig_id from tbl
)
select *
from si
cross apply (select top 1 * from tbl where si.sig_id=tbl.sig_id order by case when dcrp is null then 1 else 0 end asc,dd desc) sii
and with fiddler :
http://sqlfiddle.com/#!3/8e267/2/0
The query in SQLFiddle fails due to subquery returning more than 1 row.
Adding TOP 1 fixes that. Please check if it is OK.
THEN
(SELECT TOP 1 dcrp
FROM tbl
WHERE sig_id = a.sig_id
AND id < a.id
AND dcrp IS NOT NULL)
Related
I have data flowing from two tables, table A and table B. I'm doing an inner join on a common column from both the tables and creating two more new columns based on different conditions. Below is a sample dataset:
Table A
| Id | StartDate |
|-----|------------|
| 119 | 01-01-2018 |
| 120 | 01-02-2019 |
| 121 | 03-05-2018 |
| 123 | 05-08-2021 |
TABLE B
| Id | CodeId | Code | RedemptionDate |
|-----|--------|------|----------------|
| 119 | 1 | abc | null |
| 119 | 2 | abc | null |
| 119 | 3 | def | null |
| 119 | 4 | def | 2/3/2019 |
| 120 | 5 | ghi | 04/7/2018 |
| 120 | 6 | ghi | 4/5/2018 |
| 121 | 7 | jkl | null |
| 121 | 8 | jkl | 4/4/2019 |
| 121 | 9 | mno | 3/18/2020 |
| 123 | 10 | pqr | null |
What I'm basically doing is joining the tables on column 'Id' when StartDate>2018 and create two new columns - 'unlock' by counting CodeId when RedemptionDate is null and 'Redeem' by counting CodeId when RedmeptionDate is not null. Below is the SQL query:
WITH cte1 AS (
SELECT a.id, COUNT(b.CodeId) AS 'Unlock'
FROM TableA AS a
JOIN TableB AS b ON a.Id=b.Id
WHERE YEAR(a.StartDate) >= 2018 AND b.RedemptionDate IS NULL
GROUP BY a.id
), cte2 AS (
SELECT a.id, COUNT(b.CodeId) AS 'Redeem'
FROM TableA AS a
JOIN TableB AS b ON a.Id=b.Id
WHERE YEAR(a.StartDate) >= 2018 AND b.RedemptionDate IS NOT NULL
GROUP BY a.id
)
SELECT cte1.Id, cte1.Unlocked, cte2.Redeemed
FROM cte1
FULL OUTER JOIN cte2 ON cte1.Id = cte2.Id
If I break down the output of this query, result from cte1 will look like below:
| Id | Unlock |
|-----|--------|
| 119 | 3 |
| 121 | 1 |
| 123 | 1 |
And from cte2 will look like below:
| Id | Redeem |
|-----|--------|
| 119 | 1 |
| 120 | 2 |
| 121 | 2 |
The last select query will produce the following result:
| Id | Unlock | Redeem |
|------|--------|--------|
| 119 | 3 | 1 |
| null | null | 2 |
| 121 | 1 | 2 |
| 123 | 1 | null |
How can I replace the null value from Id with values from 'b.Id'? If I try coalesce or a case statement, they create new columns. I don't want to create additional columns, rather replace the null values from the column values coming from another table.
My final output should like:
| Id | Unlock | Redeem |
|-----|--------|--------|
| 119 | 3 | 1 |
| 120 | null | 2 |
| 121 | 1 | 2 |
| 123 | 1 | null |
If I'm following correctly, you can use apply with aggregation:
select a.*, b.*
from a cross apply
(select count(RedemptionDate) as num_redeemed,
count(*) - count(RedemptionDate) as num_unlock
from b
where b.id = a.id
) b;
However, the answer to your question is to use coalesce(cte1.id, cte2.id) as id.
Here is my table A.
| Id | GroupId | StoreId | Amount |
| 1 | 20 | 7 | 15000 |
| 2 | 20 | 7 | 1230 |
| 3 | 20 | 7 | 14230 |
| 4 | 20 | 7 | 9540 |
| 5 | 20 | 7 | 24230 |
| 6 | 20 | 7 | 1230 |
| 7 | 20 | 7 | 1230 |
Here is my table B.
| Id | GroupId | StoreId | Credit |
| 12 | 20 | 7 | 1230 |
| 14 | 20 | 7 | 15000 |
| 15 | 20 | 7 | 14230 |
| 16 | 20 | 7 | 1230 |
| 17 | 20 | 7 | 7004 |
| 18 | 20 | 7 | 65523 |
I want to get this result without getting duplicate Id of both table.
I need to get the Id of table B and A where the Amount = Credit.
| A.ID | B.ID | Amount |
| 1 | 14 | 15000 |
| 2 | 12 | 1230 |
| 3 | 15 | 14230 |
| 4 | null | 9540 |
| 5 | null | 24230 |
| 6 | 16 | 1230 |
| 7 | null | 1230 |
My problem is when I have 2 or more same Amount in table A, I get duplicate ID of table B. which should be null. Please help me. Thank you.
I think you want a left join. But this is tricky because you have duplicate amounts, but you only want one to match. The solution is to use row_number():
select . . .
from (select a.*, row_number() over (partition by amount order by id) as seqnum
from a
) a left join
(select b.*, row_number() over (partition by credit order by id) as seqnum
from b
)b
on a.amount = b.credit and a.seqnum = b.seqnum;
Another approach, I think simplier and shorter :)
select ID [A.ID],
(select top 1 ID from TABLE_B where Credit = A.Amount) [B.ID],
Amount
from TABLE_A [A]
I have huge data and sample of the table looks like below
+-----------+------------+-----------+-----------+
| Unique_ID | Date | RowNumber | Flag_Date |
+-----------+------------+-----------+-----------+
| 1 | 6/3/2014 | 1 | 6/3/2014 |
| 1 | 5/22/2015 | 2 | NULL |
| 1 | 6/3/2015 | 3 | NULL |
| 1 | 11/20/2015 | 4 | NULL |
| 2 | 2/25/2014 | 1 | 2/25/2014 |
| 2 | 7/31/2014 | 2 | NULL |
| 2 | 8/26/2014 | 3 | NULL |
+-----------+------------+-----------+-----------+
Now I need to check if the difference between Date in 2nd row and Flag_date in 1st row. If the difference is more than 180 then 2nd row Flag_date should be updated with the date in 2nd row else it needs to be updated by Flag_date in 1st Row. And same rule follows for all rows with same unique_ID
update a
set a.Flag_Date=case when DATEDIFF(dd,b.Flag_Date,a.[Date])>180 then a.[Date] else b.Flag_Date end
from Table1 a
inner join Table1 b
on a.RowNumber=b.RowNumber+1 and a.Unique_ID=b.Unique_ID
The above update query when executed once, only the second row under each Unique_ID gets updated and result looks like below
+-----------+------------+-----------+------------+
| Unique_ID | Date | RowNumber | Flag_Date |
+-----------+------------+-----------+------------+
| 1 | 2014-06-03 | 1 | 2014-06-03 |
| 1 | 2015-05-22 | 2 | 2015-05-22 |
| 1 | 2015-06-03 | 3 | NULL |
| 1 | 2015-11-20 | 4 | NULL |
| 2 | 2014-02-25 | 1 | 2014-02-25 |
| 2 | 2014-07-31 | 2 | 2014-02-25 |
| 2 | 2014-08-26 | 3 | NULL |
+-----------+------------+-----------+------------+
And I need to run four times to achieve my desired result
+-----------+------------+-----------+------------+
| Unique_ID | Date | RowNumber | Flag_Date |
+-----------+------------+-----------+------------+
| 1 | 2014-06-03 | 1 | 2014-06-03 |
| 1 | 2015-05-22 | 2 | 2015-05-22 |
| 1 | 2015-06-03 | 3 | 2015-05-22 |
| 1 | 2015-11-20 | 4 | 2015-11-20 |
| 2 | 2014-02-25 | 1 | 2014-02-25 |
| 2 | 2014-07-31 | 2 | 2014-02-25 |
| 2 | 2014-08-26 | 3 | 2014-08-26 |
+-----------+------------+-----------+------------+
Is there a way where I can run update only once and all the rows are updated.
Thank you!
If you are using SQL Server 2012+, then you can use lag():
with toupdate as (
select t1.*,
lag(flag_date) over (partition by unique_id order by rownumber) as prev_flag_date
from table1 t1
)
update toupdate
set Flag_Date = (case when DATEDIFF(day, prev_Flag_Date, toupdate.[Date]) > 180
then toupdate.[Date] else prev_Flag_Date
end);
Both this version and your version can take advantage of an index on table1(unique_id, rownumber) or, better yet, table1(unique_id, rownumber, flag_date).
EDIT:
In earlier versions, this might have better performance:
with toupdate as (
select t1.*, t2.flag_date as prev_flag_date
from table1 t1 outer apply
(select top 1 t2.flag_date
from table1 t2
where t2.unique_id = t1.unique_id and
t2.rownumber < t1.rownumber
order by t2.rownumber desc
) t2
)
update toupdate
set Flag_Date = (case when DATEDIFF(day, prev_Flag_Date, toupdate.[Date]) > 180
then toupdate.[Date] else prev_Flag_Date
end);
The CTE can make use of the same index -- and it is important to have the index. The reason for the better performance is because your join on row_number() cannot use an index on that field.
I need help with a SQL that will convert this table:
===================
| Id | FK | Status|
===================
| 1 | A | 100 |
| 2 | A | 101 |
| 3 | B | 100 |
| 4 | B | 101 |
| 5 | C | 100 |
| 6 | C | 101 |
| 7 | A | 102 |
| 8 | A | 102 |
| 9 | B | 102 |
| 10 | B | 102 |
===================
to this:
==========================================
| FK | Count 100 | Count 101 | Count 102 |
==========================================
| A | 1 | 1 | 2 |
| B | 1 | 1 | 2 |
| C | 1 | 1 | 0 |
==========================================
I can so simple counts, etc., but am struggling trying to pivot the table with the information derived. Any help is appreciated.
Use:
SELECT t.fk,
SUM(CASE WHEN t.status = 100 THEN 1 ELSE 0 END) AS count_100,
SUM(CASE WHEN t.status = 101 THEN 1 ELSE 0 END) AS count_101,
SUM(CASE WHEN t.status = 102 THEN 1 ELSE 0 END) AS count_102
FROM TABLE t
GROUP BY t.fk
use:
select * from
(select fk,fk as fk1,statusFK from #t
) as t
pivot
(COUNT(fk1) for statusFK IN ([100],[101],[102])
) AS pt
Just adding a shortcut to #OMG's answer.
You can eliminate CASE statement:
SELECT t.fk,
SUM(t.status = 100) AS count_100,
SUM(t.status = 101) AS count_101,
SUM(t.status = 102) AS count_102
FROM TABLE t
GROUP BY t.fk
Issuing the following query:
SELECT t.seq,
t.buddyId,
t.mode,
t.type,
t.dtCreated
FROM MIM t
WHERE t.userId = 'ali'
ORDER BY t.dtCreated DESC;
...returns me 6 rows.
+-------------+------------------------+------+------+---------------------+
| seq | buddyId | mode | type | dtCreated |
+-------------+------------------------+------+------+---------------------+
| 12 | abcdefghij25#gmail.com | 2 | 1 | 2009-09-14 12:39:05 |
| 11 | abcdefghij25#gmail.com | 4 | 1 | 2009-09-14 12:39:02 |
| 10 | op_eee_81#hotmail.com | 1 | -1 | 2009-09-14 12:39:00 |
| 9 | abcdefghij25#gmail.com | 1 | -1 | 2009-09-14 12:38:59 |
| 8 | op_eee_81#hotmail.com | 2 | 1 | 2009-09-14 12:37:53 |
| 7 | abcdefghij25#gmail.com | 2 | 1 | 2009-09-14 12:37:46 |
+-------------+------------------------+------+------+---------------------+
I want to return rows based on this condition:
If there are duplicate rows with the same buddyId, only return me the latest (as specified by dtCreated).
So, the query should return me:
+-------------+------------------------+------+------+---------------------+
| seq | buddyId | mode | type | dtCreated |
+-------------+------------------------+------+------+---------------------+
| 12 | abcdefghij25#gmail.com | 2 | 1 | 2009-09-14 12:39:05 |
| 10 | op_eee_81#hotmail.com | 1 | -1 | 2009-09-14 12:39:00 |
+-------------+------------------------+------+------+---------------------+
I've tried with no success to use a UNIQUE function but it's not working.
This should only return the most recent entry for each userId.
SELECT a.seq
, a.buddyId
, a.mode
, a.type
, a.dtCreated
FROM mim AS [a]
JOIN (SELECT MAX(dtCreated) FROM min GROUP BY buddyId) AS [b]
ON a.dtCreated = b.dtCreated
AND a.userId = b.userId
WHERE userId='ali'
ORDER BY dtCreated DESC;