I have this query, and it returns the following result, I need to delete the records repeated by date, and keep the oldest, how could I do this?
select
a.EMP_ID, a.EMP_DATE,
from
EMPLOYES a
inner join
TABLE2 b on a.table2ID = b.table2ID and b.ID_TYPE = 'E'
where
a.ID = 'VJAHAJHSJHDAJHSJDH'
and year(a.DATE) = 2021
and month(a.DATE) = 1
and a.ID <> 31
order by
a.DATE;
Additionally, I would like to fill in the missing days of the month ... and put them empty if I don't have that data, can this be done?
I would appreciate if you could guide me to solve this problem
Thank you!
The other answers miss some of the requirement..
Initial step - do this once only. Make a calendar table. This will come in handy for all sorts of things over the time:
DECLARE #Year INT = '2000';
DECLARE #YearCnt INT = 50 ;
DECLARE #StartDate DATE = DATEFROMPARTS(#Year, '01','01')
DECLARE #EndDate DATE = DATEADD(DAY, -1, DATEADD(YEAR, #YearCnt, #StartDate));
;WITH Cal(n) AS
(
SELECT 0 UNION ALL SELECT n + 1 FROM Cal
WHERE n < DATEDIFF(DAY, #StartDate, #EndDate)
),
FnlDt(d, n) AS
(
SELECT DATEADD(DAY, n, #StartDate), n FROM Cal
),
FinalCte AS
(
SELECT
[D] = CONVERT(DATE,d),
[Dy] = DATEPART(DAY, d),
[Mo] = DATENAME(MONTH, d),
[Yr] = DATEPART(YEAR, d),
[DN] = DATENAME(WEEKDAY, d),
[N] = n
FROM FnlDt
)
SELECT * INTO Cal FROM finalCte
ORDER BY [Date]
OPTION (MAXRECURSION 0);
credit: mostly this site
Now we can write some simple query to stick your data (with one small addition) onto it:
--your query, minus the date bits in the WHERE, and with a ROW_NUMBER
WITH yourQuery AS(
SELECT a.emp_id, a.emp_date,
ROW_NUMBER() OVER(PARTITION BY CAST(a.emp_date AS DATE) ORDER BY a.emp_date) rn
FROM EMPLOYES a
INNER JOIN TABLE2 b on a.table2ID = b.table2ID
WHERE a.emp_id = 'VJAHAJHSJHDAJHSJDH' AND a.id <> 31 AND b.id_type = 'E'
)
--your query, left joined onto the cal table so that you get a row for every day even if there is no emp data for that day
SELECT c.d, yq.*
FROM
Cal c
LEFT JOIN yourQuery yq
ON
c.d = CAST(yq.emp_date AS DATE) AND --cut the time off
yq.rn = 1 --keep only the earliest time per day
WHERE
c.d BETWEEN '2021-01-01' AND EOMONTH('2021-01-01')
We add a rownumbering to your table, it restarts every time the date changes and counts up in order of time. We make this into a CTE (or a subquery, CTE is cleaner) then we simply left join it to the calendar table. This means that for any date you don't have data, you still have the calendar date. For any days you do have data, the rownumber rn being a condition of the join means that only the first datetime from each day is present in the results
Note: something is wonky about your question . You said you SELECT a.emp_id and your results show 'VJAHAJHSJHDAJHSJDH' is the emp id, but your where clause says a.id twice, once as a string and once as a number - this can't be right, so I've guessed at fixing it but I suspect you have translated your query into something for SO, perhaps to hide real column names.. Also your SELECT has a dangling comma that is a syntax error.
If you have translated/obscured your real query, make absolutely sure you understand any answer here when translating it back. It's very frustrating when someone is coming back and saying "hi your query doesn't work" then it turns out that they damaged it trying to translate it back to their own db, because they hid the real column names in the question..
FInally, do not use functions on table data in a where clause; it generally kills indexing. Always try and find a way of leaving table data alone. Want all of january? Do like I did, and say table.datecolumn BETWEEN firstofjan AND endofjan etc - SQLserver at least stands a chance of using an index for this, rather than calling a function on every date in the table, every time the query is run
You can use ROW_NUMBER
WITH CTE AS
(
SELECT a.EMP_ID, a.EMP_DATE,
RN = ROW_NUMBER() OVER (PARTITION BY a.EMP_ID, CAST(a.DATE as Date) ORDER BY a.DATE ASC)
from EMPLOYES a INNER JOIN TABLE2 b
on a.table2ID = b.table2ID
and b.ID_TYPE = 'E'
where a.ID = 'VJAHAJHSJHDAJHSJDH'
and year(a.DATE) = 2021
and MONTH(a.DATE) = 1
and a.ID <> 31
)
SELECT * FROM CTE
WHERE RN = 1
Try with an aggregate function MAX or MIN
create table #tmp(dt datetime, val numeric(4,2))
insert into #tmp values ('2021-01-01 10:30:35', 1)
insert into #tmp values ('2021-01-02 10:30:35', 2)
insert into #tmp values ('2021-01-02 11:30:35', 3)
insert into #tmp values ('2021-01-03 10:35:35', 4)
select * from #tmp
select tmp.*
from #tmp tmp
inner join
(select max(dt) as dt, cast(dt as date) as dt_aux from #tmp group by cast(dt as date)) compressed_rows on
tmp.dt = compressed_rows.dt
drop table #tmp
results:
We have appointment table as shown below. Each appointment need to be categorized as "New" or "Followup". Any appointment (for a patient) within 30 days of first appointment (of that patient) is Followup. After 30 days, appointment is again "New". Any appointment within 30 days become "Followup".
I am currently doing this by typing while loop.
How to achieve this without WHILE loop?
Table
CREATE TABLE #Appt1 (ApptID INT, PatientID INT, ApptDate DATE)
INSERT INTO #Appt1
SELECT 1,101,'2020-01-05' UNION
SELECT 2,505,'2020-01-06' UNION
SELECT 3,505,'2020-01-10' UNION
SELECT 4,505,'2020-01-20' UNION
SELECT 5,101,'2020-01-25' UNION
SELECT 6,101,'2020-02-12' UNION
SELECT 7,101,'2020-02-20' UNION
SELECT 8,101,'2020-03-30' UNION
SELECT 9,303,'2020-01-28' UNION
SELECT 10,303,'2020-02-02'
You need to use recursive query.
The 30days period is counted starting from prev(and no it is not possible to do it without recursion/quirky update/loop). That is why all the existing answer using only ROW_NUMBER failed.
WITH f AS (
SELECT *, rn = ROW_NUMBER() OVER(PARTITION BY PatientId ORDER BY ApptDate)
FROM Appt1
), rec AS (
SELECT Category = CAST('New' AS NVARCHAR(20)), ApptId, PatientId, ApptDate, rn, startDate = ApptDate
FROM f
WHERE rn = 1
UNION ALL
SELECT CAST(CASE WHEN DATEDIFF(DAY, rec.startDate,f.ApptDate) <= 30 THEN N'FollowUp' ELSE N'New' END AS NVARCHAR(20)),
f.ApptId,f.PatientId,f.ApptDate, f.rn,
CASE WHEN DATEDIFF(DAY, rec.startDate, f.ApptDate) <= 30 THEN rec.startDate ELSE f.ApptDate END
FROM rec
JOIN f
ON rec.rn = f.rn - 1
AND rec.PatientId = f.PatientId
)
SELECT ApptId, PatientId, ApptDate, Category
FROM rec
ORDER BY PatientId, ApptDate;
db<>fiddle demo
Output:
+---------+------------+-------------+----------+
| ApptId | PatientId | ApptDate | Category |
+---------+------------+-------------+----------+
| 1 | 101 | 2020-01-05 | New |
| 5 | 101 | 2020-01-25 | FollowUp |
| 6 | 101 | 2020-02-12 | New |
| 7 | 101 | 2020-02-20 | FollowUp |
| 8 | 101 | 2020-03-30 | New |
| 9 | 303 | 2020-01-28 | New |
| 10 | 303 | 2020-02-02 | FollowUp |
| 2 | 505 | 2020-01-06 | New |
| 3 | 505 | 2020-01-10 | FollowUp |
| 4 | 505 | 2020-01-20 | FollowUp |
+---------+------------+-------------+----------+
How it works:
f - get starting point(anchor - per every PatientId)
rec - recursibe part, if the difference between current value and prev is > 30 change the category and starting point, in context of PatientId
Main - display sorted resultset
Similar class:
Conditional SUM on Oracle - Capping a windowed function
Session window (Azure Stream Analytics)
Running Total until specific condition is true - Quirky update
Addendum
Do not ever use this code on production!
But another option, that is worth mentioning besides using cte, is to use temp table and update in "rounds"
It could be done in "single" round(quirky update):
CREATE TABLE Appt_temp (ApptID INT , PatientID INT, ApptDate DATE, Category NVARCHAR(10))
INSERT INTO Appt_temp(ApptId, PatientId, ApptDate)
SELECT ApptId, PatientId, ApptDate
FROM Appt1;
CREATE CLUSTERED INDEX Idx_appt ON Appt_temp(PatientID, ApptDate);
Query:
DECLARE #PatientId INT = 0,
#PrevPatientId INT,
#FirstApptDate DATE = NULL;
UPDATE Appt_temp
SET #PrevPatientId = #PatientId
,#PatientId = PatientID
,#FirstApptDate = CASE WHEN #PrevPatientId <> #PatientId THEN ApptDate
WHEN DATEDIFF(DAY, #FirstApptDate, ApptDate)>30 THEN ApptDate
ELSE #FirstApptDate
END
,Category = CASE WHEN #PrevPatientId <> #PatientId THEN 'New'
WHEN #FirstApptDate = ApptDate THEN 'New'
ELSE 'FollowUp'
END
FROM Appt_temp WITH(INDEX(Idx_appt))
OPTION (MAXDOP 1);
SELECT * FROM Appt_temp ORDER BY PatientId, ApptDate;
db<>fiddle Quirky update
You could do this with a recursive cte. You should first order by apptDate within each patient. That can be accomplished by a run-of-the-mill cte.
Then, in the anchor portion of your recursive cte, select the first ordering for each patient, mark the status as 'new', and also mark the apptDate as the date of the most recent 'new' record.
In the recursive portion of your recursive cte, increment to the next appointment, calculate the difference in days between the present appointment and the most recent 'new' appointment date. If it's greater than 30 days, mark it 'new' and reset the most recent new appointment date. Otherwise mark it as 'follow up' and just pass along the existing days since new appointment date.
Finallly, in the base query, just select the columns you want.
with orderings as (
select *,
rn = row_number() over(
partition by patientId
order by apptDate
)
from #appt1 a
),
markings as (
select apptId,
patientId,
apptDate,
rn,
type = convert(varchar(10),'new'),
dateOfNew = apptDate
from orderings
where rn = 1
union all
select o.apptId, o.patientId, o.apptDate, o.rn,
type = convert(varchar(10),iif(ap.daysSinceNew > 30, 'new', 'follow up')),
dateOfNew = iif(ap.daysSinceNew > 30, o.apptDate, m.dateOfNew)
from markings m
join orderings o
on m.patientId = o.patientId
and m.rn + 1 = o.rn
cross apply (select daysSinceNew = datediff(day, m.dateOfNew, o.apptDate)) ap
)
select apptId, patientId, apptDate, type
from markings
order by patientId, rn;
I should mention that I initially deleted this answer because Abhijeet Khandagale's answer seemed to meet your needs with a simpler query (after reworking it a bit). But with your comment to him about your business requirement and your added sample data, I undeleted mine because believe this one meets your needs.
I'm not sure that it's exactly what you implemented. But another option, that is worth mentioning besides using cte, is to use temp table and update in "rounds". So we are going to update temp table while all statuses are not set correctly and build result in an iterative way. We can control number of iteration using simply local variable.
So we split each iteration into two stages.
Set all Followup values that are near to New records. That's pretty easy to do just using right filter.
For the rest of the records that dont have status set we can select first in group with same PatientID. And say that they are new since they not processed by the first stage.
So
CREATE TABLE #Appt2 (ApptID INT, PatientID INT, ApptDate DATE, AppStatus nvarchar(100))
select * from #Appt1
insert into #Appt2 (ApptID, PatientID, ApptDate, AppStatus)
select a1.ApptID, a1.PatientID, a1.ApptDate, null from #Appt1 a1
declare #limit int = 0;
while (exists(select * from #Appt2 where AppStatus IS NULL) and #limit < 1000)
begin
set #limit = #limit+1;
update a2
set
a2.AppStatus = IIF(exists(
select *
from #Appt2 a
where
0 > DATEDIFF(day, a2.ApptDate, a.ApptDate)
and DATEDIFF(day, a2.ApptDate, a.ApptDate) > -30
and a.ApptID != a2.ApptID
and a.PatientID = a2.PatientID
and a.AppStatus = 'New'
), 'Followup', a2.AppStatus)
from #Appt2 a2
--select * from #Appt2
update a2
set a2.AppStatus = 'New'
from #Appt2 a2 join (select a.*, ROW_NUMBER() over (Partition By PatientId order by ApptId) rn from (select * from #Appt2 where AppStatus IS NULL) a) ar
on a2.ApptID = ar.ApptID
and ar.rn = 1
--select * from #Appt2
end
select * from #Appt2 order by PatientID, ApptDate
drop table #Appt1
drop table #Appt2
Update. Read the comment provided by Lukasz. It's by far smarter way. I leave my answer just as an idea.
I believe the recursive common expression is great way to optimize queries avoiding loops, but in some cases it can lead to bad performance and should be avoided if possible.
I use the code below to solve the issue and test it will more values, but encourage you to test it with your real data, too.
WITH DataSource AS
(
SELECT *
,CEILING(DATEDIFF(DAY, MIN([ApptDate]) OVER (PARTITION BY [PatientID]), [ApptDate]) * 1.0 / 30 + 0.000001) AS [GroupID]
FROM #Appt1
)
SELECT *
,IIF(ROW_NUMBER() OVER (PARTITION BY [PatientID], [GroupID] ORDER BY [ApptDate]) = 1, 'New', 'Followup')
FROM DataSource
ORDER BY [PatientID]
,[ApptDate];
The idea is pretty simple - I want separate the records in group (30 days), in which group the smallest record is new, the others are follow ups. Check how the statement is built:
SELECT *
,DATEDIFF(DAY, MIN([ApptDate]) OVER (PARTITION BY [PatientID]), [ApptDate])
,DATEDIFF(DAY, MIN([ApptDate]) OVER (PARTITION BY [PatientID]), [ApptDate]) * 1.0 / 30
,CEILING(DATEDIFF(DAY, MIN([ApptDate]) OVER (PARTITION BY [PatientID]), [ApptDate]) * 1.0 / 30 + 0.000001)
FROM #Appt1
ORDER BY [PatientID]
,[ApptDate];
So:
first, we are getting the first date, for each group and calculating the differences in days with the current one
then, we are want to get groups - * 1.0 / 30 is added
as for 30, 60, 90, etc days we are getting whole number and we wanted to start a new period, I have added + 0.000001; also, we are using ceiling function to get the smallest integer greater than, or equal to, the specified numeric expression
That's it. Having such group we simply use ROW_NUMBER to find our start date and make it as new and leaving the rest as follow ups.
With due respect to everybody and in IMHO,
There is not much difference between While LOOP and Recursive CTE in terms of RBAR
There is not much performance gain when using Recursive CTE and Window Partition function all in one.
Appid should be int identity(1,1) , or it should be ever increasing clustered index.
Apart from other benefit it also ensure that all successive row APPDate of that patient must be greater.
This way you can easily play with APPID in your query which will be more efficient than putting inequality operator like >,< in APPDate.
Putting inequality operator like >,< in APPID will aid Sql Optimizer.
Also there should be two date column in table like
APPDateTime datetime2(0) not null,
Appdate date not null
As these are most important columns in most important table,so not much cast ,convert.
So Non clustered index can be created on Appdate
Create NonClustered index ix_PID_AppDate_App on APP (patientid,APPDate) include(other column which is not i predicate except APPID)
Test my script with other sample data and lemme know for which sample data it not working.
Even if it do not work then I am sure it can be fix in my script logic itself.
CREATE TABLE #Appt1 (ApptID INT, PatientID INT, ApptDate DATE)
INSERT INTO #Appt1
SELECT 1,101,'2020-01-05' UNION ALL
SELECT 2,505,'2020-01-06' UNION ALL
SELECT 3,505,'2020-01-10' UNION ALL
SELECT 4,505,'2020-01-20' UNION ALL
SELECT 5,101,'2020-01-25' UNION ALL
SELECT 6,101,'2020-02-12' UNION ALL
SELECT 7,101,'2020-02-20' UNION ALL
SELECT 8,101,'2020-03-30' UNION ALL
SELECT 9,303,'2020-01-28' UNION ALL
SELECT 10,303,'2020-02-02'
;With CTE as
(
select a1.* ,a2.ApptDate as NewApptDate
from #Appt1 a1
outer apply(select top 1 a2.ApptID ,a2.ApptDate
from #Appt1 A2
where a1.PatientID=a2.PatientID and a1.ApptID>a2.ApptID
and DATEDIFF(day,a2.ApptDate, a1.ApptDate)>30
order by a2.ApptID desc )A2
)
,CTE1 as
(
select a1.*, a2.ApptDate as FollowApptDate
from CTE A1
outer apply(select top 1 a2.ApptID ,a2.ApptDate
from #Appt1 A2
where a1.PatientID=a2.PatientID and a1.ApptID>a2.ApptID
and DATEDIFF(day,a2.ApptDate, a1.ApptDate)<=30
order by a2.ApptID desc )A2
)
select *
,case when FollowApptDate is null then 'New'
when NewApptDate is not null and FollowApptDate is not null
and DATEDIFF(day,NewApptDate, FollowApptDate)<=30 then 'New'
else 'Followup' end
as Category
from cte1 a1
order by a1.PatientID
drop table #Appt1
Although it's not clearly addressed in the question, it's easy to figure out that the appointment dates cannot be simply categorized by 30-day groups. It makes no business sense. And you cannot use the appt id either. One can make a new appointment today for 2020-09-06.
Here is how I address this issue. First, get the first appointment, then calculate the date difference between each appointment and the first appt. If it's 0, set to 'New'. If <= 30 'Followup'. If > 30, set as 'Undecided' and do the next round check until there is no more 'Undecided'. And for that, you really need a while loop, but it does not loop through each appointment date, rather only a few datasets. I checked the execution plan. Even though there are only 10 rows, the query cost is significantly lower than that using recursive CTE, but not as low as Lukasz Szozda's addendum method.
IF OBJECT_ID('tempdb..#TEMPTABLE') IS NOT NULL DROP TABLE #TEMPTABLE
SELECT ApptID, PatientID, ApptDate
,CASE WHEN (DATEDIFF(DAY, MIN(ApptDate) OVER (PARTITION BY PatientID), ApptDate) = 0) THEN 'New'
WHEN (DATEDIFF(DAY, MIN(ApptDate) OVER (PARTITION BY PatientID), ApptDate) <= 30) THEN 'Followup'
ELSE 'Undecided' END AS Category
INTO #TEMPTABLE
FROM #Appt1
WHILE EXISTS(SELECT TOP 1 * FROM #TEMPTABLE WHERE Category = 'Undecided') BEGIN
;WITH CTE AS (
SELECT ApptID, PatientID, ApptDate
,CASE WHEN (DATEDIFF(DAY, MIN(ApptDate) OVER (PARTITION BY PatientID), ApptDate) = 0) THEN 'New'
WHEN (DATEDIFF(DAY, MIN(ApptDate) OVER (PARTITION BY PatientID), ApptDate) <= 30) THEN 'Followup'
ELSE 'Undecided' END AS Category
FROM #TEMPTABLE
WHERE Category = 'Undecided'
)
UPDATE #TEMPTABLE
SET Category = CTE.Category
FROM #TEMPTABLE t
LEFT JOIN CTE ON CTE.ApptID = t.ApptID
WHERE t.Category = 'Undecided'
END
SELECT ApptID, PatientID, ApptDate, Category
FROM #TEMPTABLE
I hope this will help you.
WITH CTE AS
(
SELECT #Appt1.*, RowNum = ROW_NUMBER() OVER (PARTITION BY PatientID ORDER BY ApptDate, ApptID) FROM #Appt1
)
SELECT A.ApptID , A.PatientID , A.ApptDate ,
Expected_Category = CASE WHEN (DATEDIFF(MONTH, B.ApptDate, A.ApptDate) > 0) THEN 'New'
WHEN (DATEDIFF(DAY, B.ApptDate, A.ApptDate) <= 30) then 'Followup'
ELSE 'New' END
FROM CTE A
LEFT OUTER JOIN CTE B on A.PatientID = B.PatientID
AND A.rownum = B.rownum + 1
ORDER BY A.PatientID, A.ApptDate
You could use a Case statement.
select
*,
CASE
WHEN DATEDIFF(d,A1.ApptDate,A2.ApptDate)>30 THEN 'New'
ELSE 'FollowUp'
END 'Category'
from
(SELECT PatientId, MIN(ApptId) 'ApptId', MIN(ApptDate) 'ApptDate' FROM #Appt1 GROUP BY PatientID) A1,
#Appt1 A2
where
A1.PatientID=A2.PatientID AND A1.ApptID<A2.ApptID
The question is, should this category be assigned based off the initial appointment, or the one prior? That is, if a Patient has had three appointments, should we compare the third appointment to the first, or the second?
You problem states the first, which is how I've answered. If that's not the case, you'll want to use lag.
Also, keep in mind that DateDiff makes not exception for weekends. If this should be weekdays only, you'll need to create your own Scalar-Valued function.
using Lag function
select apptID, PatientID , Apptdate ,
case when date_diff IS NULL THEN 'NEW'
when date_diff < 30 and (date_diff_2 IS NULL or date_diff_2 < 30) THEN 'Follow Up'
ELSE 'NEW'
END AS STATUS FROM
(
select
apptID, PatientID , Apptdate ,
DATEDIFF (day,lag(Apptdate) over (PARTITION BY PatientID order by ApptID asc),Apptdate) date_diff ,
DATEDIFF(day,lag(Apptdate,2) over (PARTITION BY PatientID order by ApptID asc),Apptdate) date_diff_2
from #Appt1
) SRC
Demo --> https://rextester.com/TNW43808
with cte
as
(
select
tmp.*,
IsNull(Lag(ApptDate) Over (partition by PatientID Order by PatientID,ApptDate),ApptDate) PriorApptDate
from #Appt1 tmp
)
select
PatientID,
ApptDate,
PriorApptDate,
DateDiff(d,PriorApptDate,ApptDate) Elapsed,
Case when DateDiff(d,PriorApptDate,ApptDate)>30
or DateDiff(d,PriorApptDate,ApptDate)=0 then 'New' else 'Followup' end Category from cte
Mine is correct. The authors was incorrect, see elapsed
I have a large table of users (as a guid), some associated values, and a time stamp of when each row was inserted. A user might be associated with many rows in this table.
guid | <other columns> | insertdate
I want to count for each month: how many unique new users were inserted. It's easy to do manually:
select count(distinct guid)
from table
where insertdate >= '20060201' and insertdate < '20060301'
and guid not in (select guid from table where
insertdate >= '20060101' and insertdate < '20060201')
How could this be done for each successive month in sql?
I thought to use a rank function to associate clearly each guid with a month:
select guid,
,dense_rank() over ( order by datepart(YYYY, insertdate),
datepart(m, t.TransactionDateTime)) as MonthRank
from table
and then iterate upon each rank value:
declare #no_times int
declare #counter int = 1
set #no_times = select count(distinct concat(datepart(year, t.TransactionDateTime),
datepart(month, t.TransactionDateTime))) from table
while #no_times > 0 do
(
select count(*), #counter
where guid not in (select guid from table where rank = #counter)
and rank = #int + 1
#counter += 1
#no_times -= 1
union all
)
end
I know this strategy is probably the wrong way to go about things.
Ideally, I would like a result set to look like this:
MonthRank | NoNewUsers
I would be extremely interested and grateful if a sql wizard could point me in the right direction.
SELECT
DATEPART(year,t.insertdate) AS YearNum
,DATEPART(mm,t.insertdate) as MonthNum
,COUNT(DISTINCT guid) AS NoNewUsers
,DENSE_RANK() OVER (ORDER BY COUNT(DISTINCT t.guid) DESC) AS MonthRank
FROM
table t
LEFT JOIN table t2
ON t.guid = t2.guid
AND t.insertdate > t2.insertdate
WHERE
t2.guid IS NULL
GROUP BY
DATEPART(year,t.insertdate)
,DATEPART(mm,t.insertdate)
Use a left join to see if the table ever existed as a prior insert date and if they didn't then count them using aggregation like you normally would. If you want to add a rank to see which month(s) have the highest number of new users then you can use your DENSE_RANK() function but because you are already grouping by want you want you do not need a partition clause.
If you want the first time that a guid entered, then your query doesn't exactly work. You can get the first time with two aggregations:
select year(first_insertdate), month(first_insertdate), count(*)
from (select t.guid, min(insertdate) as first_insertdate
from t
group by t.guid
) t
group by year(first_insertdate), month(first_insertdate)
order by year(first_insertdate), month(first_insertdate);
If you are looking for counting guids each time they skip a month, then you can use lag():
select year(insertdate), month(insertdate), count(*)
from (select t.*,
lag(insertdate) over (partition by guid order by insertdate) as prev_insertdate
from t
) t
where prev_insertdate is null or
datediff(month, prev_insertdate, insertdate) >= 2
group by year(insertdate), month(insertdate)
order by year(insertdate), month(insertdate);
I solved it with the terrible while loop, then a friend helped me to solve it more efficiently in another way.
The loop version:
--ranked by month
select t.TransactionID
,t.BuyerUserID
,concat(datepart(year, t.InsertDate), datepart(month,
t.InsertDate)) MonthRankName
,dense_rank() over ( order by datepart(YYYY, t.InsertDate),
datepart(m, t.InsertDate)) as MonthRank
into #ranked
from table t;
--iteratate
declare #counter int = 1
declare #no_times int
select #no_times = count(distinct concat(datepart(year, t.InsertDate),
datepart(month, t.InsertDate))) from table t;
select count(distinct r.guid) as NewUnique, r.Monthrank into #results
from #ranked r
where r.MonthRank = 1 group by r.MonthRank;
while #no_times > 1
begin
insert into #results
select count(distinct rt.guid) as NewUnique, #counter + 1 as MonthRank
from #ranked r
where rt.guid not in
(
select rt2.guid from #ranked rt2
where rt2.MonthRank = #counter
)
and rt.MonthRank = #counter + 1
set #counter = #counter+1
set #no_times = #no_times-1
end
select * from #results r
This turned out to run pretty slowly (as you might expect)
What turned out to be faster by a factor of 10 was this method:
select t.guid,
cast (concat(datepart(year, min(t.InsertDate)),
case when datepart(month, min(t.InsertDate)) < 10 then
'0'+cast( datepart(month, min(t.InsertDate)) as varchar(10))
else cast (datepart(month, min(t.InsertDate)) as varchar(10)) end
) as int) as MonthRankName
into #NewUnique
from table t
group by t.guid;
select count(1) as NewUniques, t.MonthRankName from #NewUnique t
group by t.MonthRankName
order by t.MonthRankName
Simply identifying the very first month each guid appears, then counting the number of these occurring each month. With a bit of a hack to get YearMonth formatted nicely (this seems to be more efficient than format([date], 'yyyyMM') but need to experiment more on that.
I have a table of items that, for sake of simplicity, contains the ItemID, the StartDate, and the EndDate for a list of items.
ItemID StartDate EndDate
1 1/1/2011 1/15/2011
2 1/2/2011 1/14/2011
3 1/5/2011 1/17/2011
...
My goal is to be able to join this table to a table with a sequential list of dates,
and say both how many items are open on a particular date, and also how many items are cumulatively open.
Date ItemsOpened CumulativeItemsOpen
1/1/2011 1 1
1/2/2011 1 2
...
I can see how this would be done with a WHILE loop,
but that has performance implications. I'm wondering how
this could be done with a set-based approach?
SELECT COUNT(CASE WHEN d.CheckDate = i.StartDate THEN 1 ELSE NULL END)
AS ItemsOpened
, COUNT(i.StartDate)
AS ItemsOpenedCumulative
FROM Dates AS d
LEFT JOIN Items AS i
ON d.CheckDate BETWEEN i.StartDate AND i.EndDate
GROUP BY d.CheckDate
This may give you what you want
SELECT DATE,
SUM(ItemOpened) AS ItemsOpened,
COUNT(StartDate) AS ItemsOpenedCumulative
FROM
(
SELECT d.Date, i.startdate, i.enddate,
CASE WHEN i.StartDate = d.Date THEN 1 ELSE 0 END AS ItemOpened
FROM Dates d
LEFT OUTER JOIN Items i ON d.Date BETWEEN i.StartDate AND i.EndDate
) AS x
GROUP BY DATE
ORDER BY DATE
This assumes that your date values are DATE data type. Or, the dates are DATETIME with no time values.
You may find this useful. The recusive part can be replaced with a table. To demonstrate it works I had to populate some sort of date table. As you can see, the actual sql is short and simple.
DECLARE #i table (itemid INT, startdate DATE, enddate DATE)
INSERT #i VALUES (1,'1/1/2011', '1/15/2011')
INSERT #i VALUES (2,'1/2/2011', '1/14/2011')
INSERT #i VALUES (3,'1/5/2011', '1/17/2011')
DECLARE #from DATE
DECLARE #to DATE
SET #from = '1/1/2011'
SET #to = '1/18/2011'
-- the recusive sql is strictly to make a datelist between #from and #to
;WITH cte(Date)
AS (
SELECT #from DATE
UNION ALL
SELECT DATEADD(day, 1, DATE)
FROM cte ch
WHERE DATE < #to
)
SELECT cte.Date, sum(case when cte.Date=i.startdate then 1 else 0 end) ItemsOpened, count(i.itemid) ItemsOpenedCumulative
FROM cte
left join #i i on cte.Date between i.startdate and i.enddate
GROUP BY cte.Date
OPTION( MAXRECURSION 0)
If you are on SQL Server 2005+, you could use a recursive CTE to obtain running totals, with the additional help of the ranking function ROW_NUMBER(), like this:
WITH grouped AS (
SELECT
d.Date,
ItemsOpened = COUNT(i.ItemID),
rn = ROW_NUMBER() OVER (ORDER BY d.Date)
FROM Dates d
LEFT JOIN Items i ON d.Date BETWEEN i.StartDate AND i.EndDate
GROUP BY d.Date
WHERE d.Date BETWEEN #FilterStartDate AND #FilterEndDate
),
cumulative AS (
SELECT
Date,
ItemsOpened,
ItemsOpenedCumulative = ItemsOpened
FROM grouped
WHERE rn = 1
UNION ALL
SELECT
g.Date,
g.ItemsOpened,
ItemsOpenedCumulative = g.ItemsOpenedCumulative + c.ItemsOpened
FROM grouped g
INNER JOIN cumulative c ON g.Date = DATEADD(day, 1, c.Date)
)
SELECT *
FROM cumulative
Given this table:
How can I get the datediff in days between each status_date for each group of ID_Number? In other words I need to find the number of elapsed days for each status that the ID_Number has been given.
Some things to know:
All ID_Number will have a received_date which should be the earliest date for each ID_Number (but app doesn't enforce)
For each ID_Number there will be a status with a corresponding status_date which is the date that the ID_Number was given that particular status.
The status column doesn't always necessarily go in the same order every time (app doesn't enforce)
All ID_Number will have a closed_date which should be the latest date (but app doesn't enforce)
Sample output:
So for ID_Number 2001, the first date (received_date) is 2009-05-02 and the next date you encounter has a status of 'open' and is 2009-05-02 so elapsed days is 0. Moving on to the next date encountered is 2009-05-10 with a status of 'invest' and the elapsed days is 8 counting from the prior date. The next date encountered is 2009-07-11 and the elapsed days is 62 counting from the previous date.
Edited to add:
Is it possible to have the elapsed days end up as a column on this table/view?
I also forgot to add that this is SQL Server 2000.
What I understand is that you need the difference between the first status_date and the next status_date for the same id and so on up to the closed_date.
This will only work in SQL 2005 and up.
;with test as (
select
key,
id_number,
status,
received_date,
status_date,
closed_date,
row_number() over (partition by id order by status_date, key ) as rownum
from #test
)
select
t1.key,
t1.id_number,
t1.status,
t1.status_date,
t1.received_date,
t1.closed_date,
datediff(d, case when t1.rownum = 1
then t1.received_date
else
case when t2.status_date is null
then t1.closed_date
else t2.status_date
end
end,
t1.status_date
) as days
from test t1
left outer join test t2
on t1.id = t2.id
and t2.rownum = t1.rownum - 1
This solution will work with SQL 2000 but I am not sure how good will perform:
select *,
datediff(d,
case when prev_date is null
then closed_date
else prev_date
end,
status_date )
from (
select *,
isnull( ( select top 1 t2.status_date
from #test t2
where t1.id_number = t2.id_number
and t2.status_date < t1.status_date
order by t2.status_date desc
),received_date) as prev_date
from #test t1
) a
order by id_number, status_date
Note: Replace the #Test table with the name of your table.
Some sample output would really help, but this is a guess at what you mean, assuming you want that information for each ID_Number/Status combination:
select ID_Number, Status, EndDate - StartDate as DaysElapsed
from (
select ID_Number, Status, min(coalesce(received_date, status_date)) as StartDate, max(coalesce(closed_date, status_date)) as EndDate
from Table1
group by ID_Number, Status
) a
The tricky bit is determining the previous status and putting it on the same row as the current status. It would be simplified a little if there were a correlation between Key and StatusDate (i.e. that Key(x) > Key(y) always implies StatusDate(x) >= StatusDate(y)). Unfortunately, that doesn't seem to be the case.
PS: I am assuming Key is a unique identifier on your table; you haven't said anything to indicate otherwise.
SELECT Key,
ID_Number,
(
SELECT TOP 1 Key
FROM StatusUpdates prev
WHERE (prev.ID_Number = cur.ID_Number)
AND ( (prev.StatusDate < cur.StatusDate)
OR ( prev.StatusDate = cur.StatusDate
AND prev.Key < cur.Key
)
)
ORDER BY StatusDate, Key /*Consider index on (ID_Number, StatusDate, Key)*/
) PrevKey
FROM StatusUpdates cur
Once you have this as a basis, it's easy to extrapolate to any other info you need from the current or previous StatusUpdate. E.g.
SELECT c.*,
p.Status AS PrevStatus,
p.StatusDate AS PrevStatusDate,
DATEDIFF(d, c.StatusDate, p.StatusDate) AS DaysElapsed
FROM (
SELECT Key,
ID_Number,
Status,
SattusDate,
(
SELECT TOP 1 Key
FROM StatusUpdates prev
WHERE (prev.ID_Number = cur.ID_Number)
AND ( (prev.StatusDate < cur.StatusDate)
OR ( prev.StatusDate = cur.StatusDate
AND prev.Key < cur.Key
)
)
ORDER BY StatusDate, Key
) PrevKey
FROM StatusUpdates cur
) c
JOIN StatusUpdates p ON
p.Key = c.PrevKey