I'm trying to get the number of days difference in dates between the effdate status 0 that follows the most recent status 1
the code below yields the following results
SELECT * FROM
(SELECT FILEKEY, STATUS, EFFDATE FROM ASTATUSHIST
UNION
SELECT FILEKEY, ASTATUS, ASTATUSEFFDATE FROM USERS ) A
ORDER BY 1, 3 DESC
130 0 2019-10-25 00:00:00.000
130 0 2017-03-01 00:00:00.000
130 0 2017-01-01 00:00:00.000
130 1 2005-02-01 00:00:00.000
130 0 2001-03-03 00:00:00.000
130 0 2000-01-30 00:00:00.000
130 0 2000-01-01 00:00:00.000
this code combines 2 tables to get the complete history for a given user.
Ideally I could produce something that looks like this:
130 4352
or
125 null
where the null is filekey without a status 1 or a filekey with a status 1 but without a following status 0
Thanks
In all supported versions of SQL Server, you can use window functions:
with t as (
<your query here>
)
select t.*,
datediff(day, date, next_date) as days_diff
from (select t.*,
row_number() over (partition by filekey, status order by date desc) as seqnum,
lead(date) over (partition by filekey order by date) as next_date
from t
) t
where seqnum = 1;
Related
I have a table like below
AID BID CDate
-----------------------------------------------------
1 2 2018-11-01 00:00:00.000
8 1 2018-11-08 00:00:00.000
1 3 2018-11-09 00:00:00.000
7 1 2018-11-15 00:00:00.000
6 1 2018-12-24 00:00:00.000
2 5 2018-11-02 00:00:00.000
2 7 2018-12-15 00:00:00.000
And I am trying to get a result set as follows
ID MaxDate
-------------------
1 2018-12-24 00:00:00.000
2 2018-12-15 00:00:00.000
Each value in the id columns(AID,BID) should return the max of CDate .
ex: in the case of 1, its max CDate is 2018-12-24 00:00:00.000 (here 1 appears under BID)
in the case of 2 , max date is 2018-12-15 00:00:00.000 . (here 2 is under AID)
I tried the following.
1.
select
g.AID,g.BID,
max(g.CDate) as 'LastDate'
from dbo.TT g
inner join
(select AID,BID,max(CDate) as maxdate
from dbo.TT
group by AID,BID)a
on (a.AID=g.AID or a.BID=g.BID)
and a.maxdate=g.CDate
group by g.AID,g.BID
and 2.
SELECT
AID,
CDate
FROM (
SELECT
*,
max_date = MAX(CDate) OVER (PARTITION BY [AID])
FROM dbo.TT
) AS s
WHERE CDate= max_date
Please suggest a 3rd solution.
You can assemble the data in a table expression first, and the compute the max for each value is simple. For example:
select
id, max(cdate)
from (
select aid as id, cdate from t
union all
select bid, cdate from t
) x
group by id
You seem to only care about values that are in both columns. If this interpretation is correct, then:
select id, max(cdate)
from ((select aid as id, cdate, 1 as is_a, 0 as is_b
from t
) union all
(select bid as id, cdate, 1 as is_a, 0 as is_b
from t
)
) ab
group by id
having max(is_a) = 1 and max(is_b) = 1;
I've the following code
declare #test table (id int, [Status] int, [Date] date)
insert into #test (Id,[Status],[Date]) VALUES
(1,1,'2018-01-01'),
(2,1,'2018-01-01'),
(1,1,'2017-11-01'),
(1,2,'2017-10-01'),
(1,1,'2017-09-01'),
(2,2,'2017-01-01'),
(1,1,'2017-08-01'),
(1,1,'2017-07-01'),
(1,1,'2017-06-01'),
(1,2,'2017-05-01'),
(1,1,'2017-04-01'),
(1,1,'2017-03-01'),
(1,1,'2017-01-01')
SELECT
id,
[Status],
MIN([Date]) OVER (PARTITION BY id,[Status] ORDER BY [Date],id,[Status] ) as WindowStart,
max([Date]) OVER (PARTITION BY id,[Status] ORDER BY [Date],id,[Status]) as WindowEnd,
COUNT(*) OVER (PARTITION BY id,[Status] ORDER BY [Date],id,[Status] ) as total
from #test
But the result is this:
id Status WindowStart WindowEnd total
1 1 2017-01-01 2017-01-01 1
1 1 2017-01-01 2017-03-01 2
1 1 2017-01-01 2017-04-01 3
1 1 2017-01-01 2017-06-01 4
1 1 2017-01-01 2017-07-01 5
1 1 2017-01-01 2017-08-01 6
1 1 2017-01-01 2017-09-01 7
1 1 2017-01-01 2017-11-01 8
1 1 2017-01-01 2018-01-01 9
1 2 2017-05-01 2017-05-01 1
1 2 2017-05-01 2017-10-01 2
2 1 2018-01-01 2018-01-01 1
2 2 2017-01-01 2017-01-01 1
And I need to be grouped by window like this.
id Status WindowStart WindowEnd total
1 1 2017-01-01 2017-04-01 3
1 2 2017-05-01 2017-05-01 1
1 1 2017-06-01 2017-09-01 4
1 2 2017-10-01 2017-10-01 1
1 1 2017-11-01 2018-01-01 2
2 1 2018-01-01 2018-01-01 1
2 2 2017-01-01 2017-01-01 1
The first group for the id= 1 Status = 1 should end at the first row with Status = 2 (2017-05-01) so the total is 3 and then start again from the 2017-06-01 to 2017-09-01 with a total of 4 rows.
How can get this done?
This is a "classic" Groups and Island issue. There's probably 1000's of answers for these on the Internet.
This works for what you're after, however, try having a bit more of a research before hand. :)
WITH Groups AS(
SELECT t.*,
ROW_NUMBER() OVER (PARTITION BY id ORDER BY [Date]) -
ROW_NUMBER() OVER (PARTITION BY id, [status] ORDER BY [Date]) AS Grp
FROM #test t)
SELECT G.id,
G.[Status],
MIN([Date]) AS WindowStart,
MAX([date]) AS WindowsEnd,
COUNT(*) AS Total
FROM Groups G
GROUP BY G.id,
G.[Status],
G.Grp
ORDER BY G.id, WindowStart;
Note, that the ordering of your last 2 lines is the other way round in this solution; it seems you're ordering ASCENDING for id 1, for DESCENDING for id 2 in your expected results.
Here is one way using LAG function
;WITH cte
AS (SELECT *,
grp = Sum(CASE WHEN prev_val = Status THEN 0 ELSE 1 END)
OVER(partition BY id ORDER BY Date)
FROM (SELECT *,
prev_val = Lag(Status)OVER(partition BY id ORDER BY Date)
FROM #test) a)
SELECT id,
Status,
WindowStart = Min(date),
WindowEnd = Max(date),
Total = Count(*)
FROM cte
GROUP BY id, Status, grp
Using lag function first find the previous status of each date, then using Sum over() create a group by incrementing the number only when there is a change in status.
I have the following table:
pk_positions ass_pos_id underlying entry_date
1 1 abc 2016-03-14
2 1 xyz 2016-03-17
3 tlt 2016-03-18
4 4 ujf 2016-03-21
5 4 dks 2016-03-23
6 4 dqp 2016-03-26
I need to select one row per ass_pos_id which has the earliest entry_date. Rows which do not have a value for ass_pos_id are not included.
In other words, for each non null ass_pos_id group, select the row which has the earliest entry_date
The following is the desired result:
pk_positions ass_pos_id underlying entry_date
1 1 abc 2016-03-14
4 4 ujf 2016-03-21
You could use the row_number window function:
SELECT pk_positions, ass_pos_id, underlying, entry_date
FROM (SELECT pk_positions, ass_pos_id, underlying, entry_date,
ROW_NUMBER() OVER (PARTITION BY ass_pos_id
ORDER BY entry_date ASC) rn
FROM mytable
WHERE ass_pos_id IS NOT NULL) t
WHERE rn = 1
In Redshift, through SQL script want to consolidate monthly records as long as gap between the end date of first and the start date of the next record is 32 days or less (<=32) into single record with minimum startdate of continuous month as output startdate and maximum of end date of continuous month as output enddate.
The below input data refers to the table's data and also listed the expected output. The input data is listed ORDER BY ID,STARTDT,ENDDT in ASC.
For example, in below table, consider ID 100, the gab between the end of the first record and start of the next record <=32, however gap between the second record end date and third records start date falls more than 32 days, hence the first two records to be consolidate into one record i.e. (ID),MIN(STARTSDT),MAX(ENDDT) which corresponds to first record in the expected output. Similarly gab between 3 and 4 record in the input data falls within the 32 days and thus these 2 records to be consolidated into single records which corresponds to the second record in the expected output.
INPUT DATA:
ID STARTDT ENDDT
100 2000-01-01 2000-01-31
100 2000-02-01 2000-02-29
100 2000-05-01 2000-05-31
100 2000-06-01 2000-06-30
100 2000-09-01 2000-09-30
100 2000-10-01 2000-10-31
101 2012-06-01 2012-06-30
101 2012-07-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-03-31
103 2013-05-01 2013-05-31
EXPECTED OUTPUT:
ID MIN_STARTDT MAX_END_DT
100 2000-01-01 2000-02-29
100 2000-05-01 2000-06-30
100 2000-09-01 2000-10-31
101 2012-06-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-03-31
103 2013-05-01 2013-05-31
You can do this in steps:
Use a join to identify where two adjacent records should be combined.
Then do a cumulative sum to assign all such adjacent records a grouping identifier.
Aggregate.
It looks like:
select id, min(startdt), max(enddte)
from (select t.*,
count(case when tprev.id is null then 1 else 0 end) over
(partition by t.idid
order by t.startdt
rows between unbounded preceding and current row
) as grp
from t left join
t tprev
on t.id = tprev.id and
t.startdt = tprev.enddt + interval '1 day'
) t
group by id, grp;
The question is very similar to this one and my answer is also similar: Fetch rows based on condition
The gist of the idea is to use Window Functions to identify transitions between period (events which are less than 33 days apart), and then do some filtering to remove the rows within the period, and then Window Functions again.
Complete solution:
SELECT
id,
startdt AS period_start,
period_end
FROM (
SELECT
id,
startdt,
enddt,
lead(enddt, 1)
OVER (PARTITION BY id
ORDER BY enddt) AS period_end,
period_boundary
FROM (
SELECT
id,
startdt,
enddt,
CASE WHEN period_switch = 0 AND reverse_period_switch = 1
THEN 'start'
ELSE 'end' END AS period_boundary
FROM (
SELECT
id,
startdt,
enddt,
CASE WHEN datediff(days, enddt, lead(startdt, 1)
OVER (PARTITION BY id
ORDER BY enddt ASC)) > 32
THEN 1
ELSE 0 END AS period_switch,
CASE WHEN datediff(days, lead(enddt, 1)
OVER (PARTITION BY id
ORDER BY enddt DESC), startdt) > 32
THEN 1
ELSE 0 END AS reverse_period_switch
FROM date_test
)
AS sessioned
WHERE period_switch != 0 OR reverse_period_switch != 0
UNION
SELECT -- adding start rows without transition
id,
startdt,
enddt,
'start'
FROM (
SELECT
id,
startdt,
enddt,
row_number()
OVER (PARTITION BY id
ORDER BY enddt ASC) AS row_num
FROM date_test
) AS with_row_number
WHERE row_num = 1
UNION
SELECT -- adding end rows without transition
id,
startdt,
enddt,
'end'
FROM (
SELECT
id,
startdt,
enddt,
row_number()
OVER (PARTITION BY id
ORDER BY enddt desc) AS row_num
FROM date_test
) AS with_row_number
WHERE row_num = 1
) AS with_boundary -- data set containing start/end boundaries
) AS with_end -- data set where end date is propagated into the start row of the period
WHERE period_boundary = 'start'
ORDER BY id, startdt ASC;
Note that in your expected output, you had a row for 103 2013-05-01 2013-05-31, however its start date is 31 days apart from end date of the previous row, so this row should instead be merged with the previous row for id 103 according to your requirements.
So the output that I get looks like this:
id start end
100 2000-01-01 2000-02-29
100 2000-05-01 2000-06-30
100 2000-09-01 2000-10-31
101 2012-06-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-05-31
I have this bit of code:
;WITH MyCTE AS
(
SELECT *,
ROW_NUMBER() OVER(PARTITION BY CardUser ORDER BY CardTableID) AS NewVariation
FROM CardChecker
)
UPDATE MyCTE
SET Status = NewVariation
which currently updates the status column, however what I want to happen is over a 24 hour period, the status starts again the next day at 1, and counts again based on the CardUser like specified above:
Current data and what happens:
2 aaa 1 2015-06-25 08:00:00.000 123 1 NULL
3 ccc 1 2015-06-25 00:00:00.000 124 1 NULL
4 aaa 1 2015-06-25 17:30:00.000 125 2 NULL
5 aaa 1 2015-06-26 17:30:00.000 125 *3* NULL
what I want to happen:
2 aaa 1 2015-06-25 08:00:00.000 123 1 NULL
3 ccc 1 2015-06-25 00:00:00.000 124 1 NULL
4 aaa 1 2015-06-25 17:30:00.000 125 2 NULL
5 aaa 1 2015-06-26 17:30:00.000 125 *1* NULL
im not quite sure how I could add this to the above query so would it be possible for someone to point me in the right direction?
the main problem is the EventTime field contains both the date and the time, so adding it is as a PARTITION means the status would always be 1 based on the time parameter of the field
thanks for the help
Current CardTable structure:
CREATE TABLE CardTable (CardTableID INT IDENTITY (1,1) NOT NULL,
CardUser VARCHAR(50),
CardNumber VARCHAR(50),
EventTime DATETIME,
Status INT)
You can CONVERT() the EventTime to DATE type and then PARTITION:
;WITH MyCTE AS
(
SELECT Status,
ROW_NUMBER() OVER(PARTITION BY CardUser, CONVERT(DATE, EventTime)
ORDER BY CardTableID) AS NewVariation
FROM CardChecker
)
UPDATE MyCTE
SET Status = NewVariation
Your query basically unnecessarily updating entire table everytime. If EventTime is current date time of the system, having a flag to mark already updated status would improve the performance.
;WITH MyCTE AS
(
SELECT Status,
ROW_NUMBER() OVER(PARTITION BY CardUser, CONVERT(DATE, EventTime)
ORDER BY CardTableID) AS NewVariation
FROM CardChecker
WHERE Status IS NULL OR
CONVERT(DATE, EventTime) = CONVERT(DATE, GETDATE())
)
UPDATE MyCTE
SET Status = NewVariation