I'm trying to get the top result from each status from a table grouped by customer id and status, ordered by time.
The data given:
CustNo Date Status
1 2016-03-24 C
1 2016-02-08 C
1 2016-01-17 A
1 2015-12-04 C
2 2016-04-28 B
2 2016-03-25 C
2 2016-02-13 C
2 2016-01-04 C
3 2016-02-02 A
3 2016-01-09 A
3 2015-12-12 A
3 2015-11-30 A
I want the output to look like this:
CustNo Date Status
1 2016-03-24 C
1 2016-01-17 A
1 2015-12-04 C
2 2016-04-28 B
2 2016-03-25 C
3 2016-02-02 A
As you can see I want the top date for each status change (if any) within each customer. I solved it for customer 2 and 3 where there is no change of status or the status never changes back, but as for customer 1 the status has changed from C to A and back to C and this is the tricky part (for me at least). I always seem to get the C status grouped all together.
You can try this.
With CTE as
{
select CustNo,
DATE,
Status,
ROW_NUMBER () over (partition by CustNo order by date) as ord
from tab
)
SELECT CustNo,
DATE,
Status
FROM CTE
EXCEPT
SELECT C1.CustNo,
C1.DATE,
C1.Status
FROM CTE C1
INNER JOIN CTE C2 ON C1.CustNo = C2.CustNo
AND C1.Status = C2.Status
AND C1.ord + 1 = C2.ord
You could use windowed function ROW_NUMBER to calculate groups:
WITH cte AS (
SELECT *,
ROW_NUMBER() OVER(PARTITION BY CustNo ORDER BY Date) -
ROW_NUMBER() OVER(PARTITION BY CustNo, Status ORDER BY Date) AS grp
FROM mytable
)
SELECT CustNo, Status, MAX(Date) AS Date
FROM cte
GROUP BY CustNo, Status, grp
ORDER BY CustNo, Date DESC;
LiveDemo
Output:
╔════════╦════════╦═════════════════════╗
║ CustNo ║ Status ║ Date ║
╠════════╬════════╬═════════════════════╣
║ 1 ║ C ║ 24.03.2016 00:00:00 ║
║ 1 ║ A ║ 17.01.2016 00:00:00 ║
║ 1 ║ C ║ 04.12.2015 00:00:00 ║
║ 2 ║ B ║ 28.04.2016 00:00:00 ║
║ 2 ║ C ║ 25.03.2016 00:00:00 ║
║ 3 ║ A ║ 02.02.2016 00:00:00 ║
╚════════╩════════╩═════════════════════╝
Related
I have a table like below :
Id Price1 Price2
3 30 20
3 40 20
3 50 20
I want to write a query to get a below result :
Desired Ouput :
RowNo Id Price
1 3 20
2 3 30
3 3 40
4 3 50
Please help!!
Use Cross apply to unpivot the data and generate row number
SELECT Row_number()OVER(ORDER BY price) AS Rowno,*
FROM (SELECT DISTINCT Id,
Price
FROM (VALUES (3,30,20),
(3,40,20),
(3,50,20) ) tc ( Id, Price1, Price2)
CROSS apply (VALUES (Price1),
(Price2)) Cs (Price)) A
Result :
╔═══════╦════╦═══════╗
║ Rowno ║ Id ║ Price ║
╠═══════╬════╬═══════╣
║ 1 ║ 3 ║ 20 ║
║ 2 ║ 3 ║ 30 ║
║ 3 ║ 3 ║ 40 ║
║ 4 ║ 3 ║ 50 ║
╚═══════╩════╩═══════╝
You can use union to combine the rows (so duplicates are removed). And then row_number() to calculate rownum:
select row_number() over (order by price) as rownum, id, price
from ((select id, price1 as price from t) union
(select id, price2 from t
) t
order by price;
How sort this
a 1 15
a 2 3
a 3 34
b 1 55
b 2 44
b 3 8
to (by third column sum):
b 1 55
b 2 44
b 3 8
a 1 15
a 2 3
a 3 34
since (55+44+8) > (15+3+34)
If you are using SQL Server/Oracle/Postgresql you could use windowed SUM:
SELECT *
FROM tab
ORDER BY SUM(col3) OVER(PARTITION BY col) DESC, col2
LiveDemo
Output:
╔═════╦══════╦══════╗
║ col ║ col2 ║ col3 ║
╠═════╬══════╬══════╣
║ b ║ 1 ║ 55 ║
║ b ║ 2 ║ 44 ║
║ b ║ 3 ║ 8 ║
║ a ║ 1 ║ 15 ║
║ a ║ 2 ║ 3 ║
║ a ║ 3 ║ 34 ║
╚═════╩══════╩══════╝
You can do this using ANSI standard window functions. I prefer to use a subquery although this is not strictly necessary:
select col1, col2, col3
from (select t.*, sum(col3) over (partition by col1) as sumcol3
from t
) t
order by sumcol3 desc, col3 desc;
...and an example how to do it without windowing functions, in for example MySQL (but also in just about any other standard SQL version)
SELECT m.col1, m.col2, m.col3
FROM myTable m
JOIN (
SELECT col1, SUM(col3) groupsum FROM myTable GROUP BY col1
) z ON m.col1 = z.col1
ORDER BY z.groupsum DESC, col2;
Basically, calculate the group sum in a subquery and join/order the results by the group's sum descending.
An SQLfiddle to test with.
For example, Below is input table which has Month & User
Output Required:
NewUsers are new in that month. ExistingUsers are users in that month which have some data in previous month as well. Inactive users are users active in previous month but not in current month
Is it possible?
You can use windowed function to achieve that:
New User is very easy COUNT rows that have rn = 1
Existing Users: easy too, COUNT rows that have rn > 1
Inactive Users: bit complicated (get sum of new + existing and substract (new + existing) from row before.
Code:
WITH cte AS
(
SELECT *
,rn = ROW_NUMBER() OVER (PARTITION BY UserKey ORDER BY MonthId)
FROM #tab t1
), cte2 AS(
SELECT
MonthId,
[New_User] = COUNT(CASE WHEN rn = 1 THEN 1 END),
[Existing_User] = COUNT(CASE WHEN rn > 1 THEN 1 END),
[s] = COUNT(rn)
FROM cte
GROUP BY MonthId
)
SELECT
MonthId,
[New_User],
[Existing_User],
[Inactive_User] = CASE WHEN [s] - LAG(s, 1) OVER(ORDER BY MonthId) < 0
THEN ABS([s] - LAG(s, 1) OVER(ORDER BY MonthId))
ELSE 0
END
FROM cte2
ORDER BY MonthId;
LiveDemo
Output:
╔═════════╦═══════════╦════════════════╦════════════════╗
║ MonthID ║ New_Users ║ Existing_Users ║ Inactive_Users ║
╠═════════╬═══════════╬════════════════╬════════════════╣
║ 201411 ║ 1 ║ 0 ║ 0 ║
║ 201412 ║ 1 ║ 1 ║ 0 ║
║ 201501 ║ 1 ║ 2 ║ 0 ║
║ 201502 ║ 0 ║ 2 ║ 1 ║
╚═════════╩═══════════╩════════════════╩════════════════╝
Warning:
I've assumed that data per each MonthId is UNIQUE if not add one more CTE step to remove duplicates first.
I have integer values: (199903, 199908, 201203, 201408, 201410, 201501, 201503)
and I would like to group these integers by integers falling within a range of 3.
In this example the grouping would be the following:
199903 (group 1)
199908 (group 2)
201203 (group 3)
201408 (group 4)
201410 (group 4)
201501 (group 5)
201503 (group 5)
You can use windowed function DENSE_RANK:
LiveDemo
CREATE TABLE #mytable(val INTEGER);
INSERT INTO #mytable(val)
VALUES(199903),(199908),(201203),(201408),(201410),(201501),(201503);
SELECT
val,
[group] = DENSE_RANK() OVER (ORDER BY val/3)
FROM #mytable;
Output:
╔════════╦═══════╗
║ val ║ group ║
╠════════╬═══════╣
║ 199903 ║ 1 ║
║ 199908 ║ 2 ║
║ 201203 ║ 3 ║
║ 201408 ║ 4 ║
║ 201410 ║ 4 ║
║ 201501 ║ 5 ║
║ 201503 ║ 5 ║
╚════════╩═══════╝
I suspect you mean sequences that differ by three or less. So, a new period starts when the difference is greater than 3. In SQL Server 2012+, you can use lag() for this. In SQL Server 2008, here is one way:
with t as (
select t.*,
(case when t.val - tprev.val < 3 then 0 else 1 end) as IsGroupStart
from table t outer apply
(select top 1 t2.val
from table t2
where t2.val < t.val
order by t2.val desc
) tprev
) t
select t.val, t2.grp
from t outer apply
(select sum(IsGroupStart) as grp
from t t2
where t2.val <= t.val
) t2;
I have table with about 100000 records.I need update same fields like this.
For example this is my table
id name
1 sss
2 bbb
3 ccc
4 avg
5 bbb
6 bbb
7 sss
8 mmm
9 avg
After executing script I need get
id name
1 sss
2 bbb
3 ccc
4 avg
5 bbb-5
6 bbb-6
7 sss-7
8 mmm
9 avg-9
How can I do that?
By using CTE
WITH greaterRecord
AS
(
SELECT id,
name,
ROW_NUMBER() OVER(PARTITION BY name ORDER BY id) RN
FROM TableName
)
UPDATE greaterRecord
SET name = name + '-' + CAST(id AS VARCHAR(10))
WHERE RN > 1
SQLFiddle Demo
This is the common query that works on most RDBMS
UPDATE a
SET a.Name = a.Name + '-' + CAST(ID AS VARCHAR(10))
FROM tableName a
LEFT JOIN
(
SELECT MIN(ID) min_ID, name
FROM tableName
GROUP BY name
) b ON a.name = b.name AND
a.ID = b.Min_ID
WHERE b.Name IS NULL
SQLFiddle Demo
OUTPUT after the update statement has been executed
╔════╦═══════╗
║ ID ║ NAME ║
╠════╬═══════╣
║ 1 ║ sss ║
║ 2 ║ bbb ║
║ 3 ║ ccc ║
║ 4 ║ avg ║
║ 5 ║ bbb-5 ║
║ 6 ║ bbb-6 ║
║ 7 ║ sss-7 ║
║ 8 ║ mmm ║
║ 9 ║ avg-9 ║
╚════╩═══════╝
This should do:
;WITH CTE AS
(
SELECT id,
name,
RN = ROW_NUMBER() OVER(PARTITION BY name ORDER BY id)
FROM YourTable
)
UPDATE CTE
SET name = name + '-' + CAST(id AS VARCHAR(8))
WHERE RN > 1