I have a table A:
Create table A(
Name varchar(10),
Number integer,
Exc integer,
D1 date
)
I have inserted 11 rows.
Sel * from A;
+ -----+--------+-----+------------+
| NAME | NUMBER | EXC | D1 |
+ -----+--------+-----+------------+
| a | 1 | 1 | 2020-02-03 |
| a | 1 | 2 | 2020-02-03 |
| a | 1 | 3 | 2020-02-03 |
| a | 1 | 4 | 2020-02-03 |
| a | 1 | 1 | 2020-02-04 |
| a | 1 | 2 | 2020-02-04 |
| a | 1 | 3 | 2020-02-04 |
| a | 1 | 1 | 2020-02-05 |
| a | 1 | 2 | 2020-02-05 |
| a | 1 | 3 | 2020-02-05 |
| a | 1 | 4 | 2020-02-05 |
+ -----+--------+-----+------------+
Now, when I apply dense rank like below:
sel vt.*,dense_rank() OVER(PARTITION BY Name,Number,EXC ORDER BY D1 ) AS rn
from vt;
Output:
+ -----+--------+-----+------------+----+
| NAME | NUMBER | EXC | D1 | RN |
+ -----+--------+-----+------------+----+
| a | 1 | 1 | 2020-02-03 | 1 |
| a | 1 | 2 | 2020-02-03 | 1 |
| a | 1 | 3 | 2020-02-03 | 1 |
| a | 1 | 4 | 2020-02-03 | 1 |
| a | 1 | 1 | 2020-02-04 | 2 |
| a | 1 | 2 | 2020-02-04 | 2 |
| a | 1 | 3 | 2020-02-04 | 2 |
| a | 1 | 1 | 2020-02-05 | 3 |
| a | 1 | 2 | 2020-02-05 | 3 |
| a | 1 | 3 | 2020-02-05 | 3 |
| a | 1 | 4 | 2020-02-05 | 2 |
+ -----+--------+-----+------------+----+
Expected:
+ -----+--------+-----+------------+----+
| NAME | NUMBER | EXC | D1 | RN |
+ -----+--------+-----+------------+----+
| a | 1 | 1 | 2020-02-03 | 1 |
| a | 1 | 2 | 2020-02-03 | 1 |
| a | 1 | 3 | 2020-02-03 | 1 |
| a | 1 | 4 | 2020-02-03 | 1 |
| a | 1 | 1 | 2020-02-04 | 2 |
| a | 1 | 2 | 2020-02-04 | 2 |
| a | 1 | 3 | 2020-02-04 | 2 |
| a | 1 | 1 | 2020-02-05 | 3 |
| a | 1 | 2 | 2020-02-05 | 3 |
| a | 1 | 3 | 2020-02-05 | 3 |
| a | 1 | 4 | 2020-02-05 | 3 | <-- Difference here
+ -----+--------+-----+------------+----+
Removing column EXC from the PARTITION would give you the results that you expect:
DENSE_RANK() OVER(PARTITION BY Name, Number ORDER BY D1)
Demo on DB Fiddle:
name | number | exc | d1 | rn
:--- | -----: | --: | :--------- | :-
a | 1 | 1 | 2020-02-03 | 1
a | 1 | 2 | 2020-02-03 | 1
a | 1 | 3 | 2020-02-03 | 1
a | 1 | 4 | 2020-02-03 | 1
a | 1 | 1 | 2020-02-04 | 2
a | 1 | 2 | 2020-02-04 | 2
a | 1 | 3 | 2020-02-04 | 2
a | 1 | 1 | 2020-02-05 | 3
a | 1 | 2 | 2020-02-05 | 3
a | 1 | 3 | 2020-02-05 | 3
a | 1 | 4 | 2020-02-05 | 3
Do you simply want to rank all rows by date? Then remove the partition clause, so the ranking is done not inside groups.
select name, number, exc, d1, dense_rank() over (order by d1) as rn
from vt
order by d1, name, number, exc;
Related
This is what I have right now:
| time | car_id | order | in_order |
|-------|--------|-------|----------|
| 12:31 | 32 | null | 0 |
| 12:33 | 32 | null | 0 |
| 12:35 | 32 | null | 0 |
| 12:37 | 32 | 123 | 1 |
| 12:38 | 32 | 123 | 1 |
| 12:39 | 32 | 123 | 1 |
| 12:41 | 32 | 123 | 1 |
| 12:43 | 32 | 123 | 1 |
| 12:45 | 32 | null | 0 |
| 12:47 | 32 | null | 0 |
| 12:49 | 32 | 321 | 1 |
| 12:51 | 32 | 321 | 1 |
I'm trying to rank orders, including those who have null values, in this case by car_id.
This is the result I'm looking for:
| time | car_id | order | in_order | row |
|-------|--------|-------|----------|-----|
| 12:31 | 32 | null | 0 | 1 |
| 12:33 | 32 | null | 0 | 1 |
| 12:35 | 32 | null | 0 | 1 |
| 12:37 | 32 | 123 | 1 | 2 |
| 12:38 | 32 | 123 | 1 | 2 |
| 12:39 | 32 | 123 | 1 | 2 |
| 12:41 | 32 | 123 | 1 | 2 |
| 12:43 | 32 | 123 | 1 | 2 |
| 12:45 | 32 | null | 0 | 3 |
| 12:47 | 32 | null | 0 | 3 |
| 12:49 | 32 | 321 | 1 | 4 |
| 12:51 | 32 | 321 | 1 | 4 |
I just don't know how to manage a count for the null values.
Thanks!
You can count the number of non-NULL values before each row and then use dense_rank():
select t.*,
dense_rank() over (partition by car_id order by grp) as row
from (select t.*,
count(order) over (partition by car_id order by time) as grp
from t
) t;
I need to increase the value of the proceeding row number by 1. When the row encounters another condition I then need to reset the counter. This is probably easiest explained with an example:
+---------+------------+------------+-----------+----------------+
| Acct_ID | Ins_Date | Acct_RowID | indicator | Desired_Output |
+---------+------------+------------+-----------+----------------+
| 5841 | 07/11/2019 | 1 | 1 | 1 |
| 5841 | 08/11/2019 | 2 | 0 | 2 |
| 5841 | 09/11/2019 | 3 | 0 | 3 |
| 5841 | 10/11/2019 | 4 | 0 | 4 |
| 5841 | 11/11/2019 | 5 | 1 | 1 |
| 5841 | 12/11/2019 | 6 | 0 | 2 |
| 5841 | 13/11/2019 | 7 | 1 | 1 |
| 5841 | 14/11/2019 | 8 | 0 | 2 |
| 5841 | 15/11/2019 | 9 | 0 | 3 |
| 5841 | 16/11/2019 | 10 | 0 | 4 |
| 5841 | 17/11/2019 | 11 | 0 | 5 |
| 5841 | 18/11/2019 | 12 | 0 | 6 |
| 5132 | 11/03/2019 | 1 | 1 | 1 |
| 5132 | 12/03/2019 | 2 | 0 | 2 |
| 5132 | 13/03/2019 | 3 | 0 | 3 |
| 5132 | 14/03/2019 | 4 | 1 | 1 |
| 5132 | 15/03/2019 | 5 | 0 | 2 |
| 5132 | 16/03/2019 | 6 | 0 | 3 |
| 5132 | 17/03/2019 | 7 | 0 | 4 |
| 5132 | 18/03/2019 | 8 | 0 | 5 |
| 5132 | 19/03/2019 | 9 | 1 | 1 |
| 5132 | 20/03/2019 | 10 | 0 | 2 |
+---------+------------+------------+-----------+----------------+
The column I want to create is 'Desired_Output'. It can be seen from this table that I need to use the column 'indicator'. I want the following row to be n+1; unless the next row is 1. The counter needs to reset when the value 1 is encountered again.
I have tried to use a loop method of some sort but this did not produce the desired results.
Is this possible in some way?
The trick is to identify the group of consecutive rows starts from indicator 1 to the next 1. This is achieve by using the cross apply finding the Acct_RowID with indicator = 1 and use that as a Grp_RowID to use as partition by in the row_number() window function
select *,
Desired_Output = row_number() over (partition by t.Acct_ID, Grp_RowID
order by Acct_RowID)
from your_table t
cross apply
(
select Grp_RowID = max(Acct_RowID)
from your_table x
where x.Acct_ID = t.Acct_ID
and x.Acct_RowID <= t.Acct_RowID
and x.indicator = 1
) g
I have a base table where I need to calculate the difference between two dates based on the type of the entry.
tblA
+----------+------------+---------------+--------------+
| TypeCode | Log_Date | Complete_Date | Pending_Date |
+----------+------------+---------------+--------------+
| 1 | 18/04/2016 | 19/04/2016 | |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 |
| 3 | 12/04/2016 | 19/04/2016 | |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 |
| 5 | 16/04/2016 | 21/04/2016 | |
| 1 | 19/04/2016 | 20/04/2016 | |
| 2 | 20/03/2016 | 31/03/2015 | |
| 3 | 25/03/2016 | 28/03/2016 | |
| 4 | 26/03/2016 | 27/03/2016 | |
| 5 | 27/03/2016 | 30/03/2016 | |
+----------+------------+---------------+--------------+
I have another look up table which has the column names to be considered based on the TypeCode.
tblB
+----------+----------+---------------+
| TypeCode | DateCol1 | DateCol2 |
+----------+----------+---------------+
| 1 | Log_Date | Complete_Date |
| 2 | Log_Date | Pending_Date |
| 3 | Log_Date | Complete_Date |
| 4 | Log_Date | Pending_Date |
| 5 | Log_Date | Complete_Date |
+----------+----------+---------------+
I am doing a simple DATEDIFF between two dates for my calculation. However I want to lookup which columns to consider for this calculation from tblB and apply it on tblA based on the TypeCode.
Resulting table:
For example: When the TypeCode is 2 or 4 then the calculation should be DATEDIFF(d, Log_Date, Pending_Date), otherwise DATEDIFF(d, Log_Date, Complete_Date)
+----------+------------+---------------+--------------+----------+
| TypeCode | Log_Date | Complete_Date | Pending_Date | Cal_Days |
+----------+------------+---------------+--------------+----------+
| 1 | 18/04/2016 | 19/04/2016 | | 1 |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 | 5 |
| 3 | 12/04/2016 | 19/04/2016 | | 7 |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 | 1 |
| 5 | 16/04/2016 | 21/04/2016 | | 5 |
| 1 | 19/04/2016 | 20/04/2016 | | 1 |
| 2 | 20/03/2016 | 31/03/2015 | | |
| 3 | 25/03/2016 | 28/03/2016 | | 3 |
| 4 | 26/03/2016 | 27/03/2016 | | |
| 5 | 27/03/2016 | 30/03/2016 | | 3 |
+----------+------------+---------------+--------------+----------+
Any help would be appreciated. Thanks.
Use JOIN with CASE expression:
SELECT
a.*,
Cal_Days =
DATEDIFF(
DAY,
CASE
WHEN b.DateCol1 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol1 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END,
CASE
WHEN b.DateCol2 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol2 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END
)
FROM TblA a
INNER JOIN TblB b
ON b.TypeCode = a.TypeCode
I have four tables as below:
tblAccount
Id i sprimary key
+----+-----------------+
| Id | AccName |
+----+-----------------+
| 1 | AccountA |
| 2 | AccountB |
+----+-----------------+
tblLocation
Id is primary key.
+----+---------------+
| Id | LocName |
+----+---------------+
| 1 | LocationA |
| 2 | LocationB |
| 3 | LocationC |
+----+---------------+
tblAccountwiseLocation
Id i sprimary key.LocId and AccId are foreign key.
+----+---------------+---------------+
| Id | LocId | AccId |
+----+---------------+---------------+
| 1 | 1 | 1 |
| 2 | 2 | 1 |
| 3 | 3 | 1 |
| 4 | 1 | 2 |
| 5 | 2 | 2 |
| 6 | 3 | 2 |
+----+---------------+---------------+
tblRSCMaster
Id i sprimary key.LocId and AccId are foreign key.
+----+---------------+---------------+----------------+------------------+
| Id | LocId | AccId | RSCNo | DateOfAddition |
+----+---------------+---------------+----------------+------------------+
| 1 | 1 | 1 | Acc1_Loc1_1_14 | 15/01/2014 |
| 2 | 2 | 1 | Acc1_Loc2_1_14 | 15/01/2014 |
| 3 | 3 | 1 | Acc1_Loc2_1_14 | 15/01/2014 |
| 4 | 1 | 2 | Acc2_Loc1_1_14 | 15/01/2014 |
| 5 | 2 | 2 | Acc2_Loc2_1_14 | 15/01/2014 |
| 6 | 3 | 2 | Acc2_Loc3_1_14 | 15/01/2014 |
| 7 | 1 | 1 | Acc1_Loc1_2_14 | 15/02/2014 |
| 8 | 2 | 1 | Acc1_Loc2_2_14 | 15/02/2014 |
| 9 | 3 | 1 | Acc1_Loc3_2_14 | 15/02/2014 |
| 10 | 1 | 2 | Acc2_Loc1_2_14 | 15/02/2014 |
| 11 | 2 | 2 | Acc2_Loc2_2_14 | 15/02/2014 |
| 12 | 3 | 2 | Acc2_Loc3_2_14 | 15/02/2014 |
| 13 | 1 | 1 | Acc1_Loc1_3_14 | 15/03/2014 |
| 14 | 2 | 1 | Acc1_Loc2_3_14 | 15/03/2014 |
| 15 | 3 | 1 | Acc1_Loc3_3_14 | 15/03/2014 |
| 16 | 1 | 2 | Acc2_Loc1_3_14 | 15/03/2014 |
| 17 | 2 | 2 | Acc2_Loc2_3_14 | 15/03/2014 |
| 18 | 3 | 2 | Acc2_Loc3_3_14 | 15/03/2014 |
| 19 | 1 | 1 | Acc1_Loc1_4_14 | 15/04/2014 |
| 20 | 2 | 1 | Acc1_Loc2_4_14 | 15/04/2014 |
| 21 | 3 | 1 | Acc1_Loc3_4_14 | 15/04/2014 |
| 22 | 1 | 2 | Acc2_Loc1_4_14 | 15/04/2014 |
| 23 | 2 | 2 | Acc2_Loc2_4_14 | 15/04/2014 |
| 24 | 3 | 2 | Acc2_Loc3_4_14 | 15/04/2014 |
| 25 | 1 | 1 | Acc1_Loc1_5_14 | 15/05/2014 |
| 26 | 2 | 1 | Acc1_Loc2_5_14 | 15/05/2014 |
| 27 | 3 | 1 | Acc1_Loc3_5_14 | 15/05/2014 |
| 28 | 1 | 2 | Acc2_Loc1_5_14 | 15/05/2014 |
| 29 | 2 | 2 | Acc2_Loc2_5_14 | 15/05/2014 |
| 30 | 3 | 2 | Acc2_Loc3_5_14 | 15/05/2014 |
+----+---------------+---------------+----------------+------------------+
Acc1_Loc1_1_14 resembles RSC for LocationA of AccountA for Jan 2014.
I need to get a output as below from tblRSCMaster.
+---------------+---------------+----------------+------------------+
| LocId | AccId | RSCNo | DateOfAddition |
+---------------+---------------+----------------+------------------+
| 1 | 1 | Acc1_Loc1_3_14 | 15/03/2014 |
| 1 | 1 | Acc1_Loc1_4_14 | 15/04/2014 |
| 1 | 1 | Acc1_Loc1_5_14 | 15/05/2014 |
| 2 | 1 | Acc1_Loc2_3_14 | 15/03/2014 |
| 2 | 1 | Acc1_Loc2_4_14 | 15/04/2014 |
| 2 | 1 | Acc1_Loc2_5_14 | 15/05/2014 |
| 3 | 1 | Acc1_Loc3_3_14 | 15/03/2014 |
| 3 | 1 | Acc1_Loc3_4_14 | 15/04/2014 |
| 3 | 1 | Acc1_Loc3_5_14 | 15/05/2014 |
+---------------+---------------+----------------+------------------+
Each account has multiple locations and each location has multiple RSCs.
I need to get last three RSCs for each location for AccountA.
I have tried the below query:
SELECT tblAccountwiseLocation.LocId,tblAccountwiseLocation.AccId,tblRSCMaster.RSCNo,tblRSCMaster.DateOfAddition FROM tblAccountwiseLocation
INNER JOIN tblRSCMaster ON tblAccountwiseLocation.LocId= tblRSCMaster.LocId
where tblRSCMaster.AccId=1
But not getting the proper output.
Please help me out.
Thank you all in advance.
You can wrap the existing query inside a common table expression, and use ROW_NUMBER() to get only the last 3 (by tblRSCMaster.DateOfAddition) entries per tblAccountwiseLocation.LocId.
WITH cte AS (
SELECT tblAccountwiseLocation.LocId,
tblAccountwiseLocation.AccId,
tblRSCMaster.RSCNo,
tblRSCMaster.DateOfAddition,
ROW_NUMBER() OVER (PARTITION BY tblAccountwiseLocation.LocId
ORDER BY tblRSCMaster.DateOfAddition DESC) rn
FROM tblAccountwiseLocation
INNER JOIN tblRSCMaster
ON tblAccountwiseLocation.LocId = tblRSCMaster.LocId
AND tblAccountwiseLocation.AccId = tblRSCMaster.AccId
WHERE tblRSCMaster.AccId=1
)
SELECT LocId, AccId, RSCNo, DateOfAddition
FROM cte
WHERE rn <= 3
ORDER BY LocId, AccId, DateOfAddition
An SQLfiddle to test with.
Is this what you need?
select m.*
from (select m.*, row_number() over (partition by accID
order by DateOfAddition desc) as seqnum
from tblRSCMaster
where m.locid = 1
) m
where seqnum <= 3
order by AccId, DateOfAddition;
I think you need to filter on the locid rather than on the AccId to get what you want.
I have a table where I have a list of people, lets say i have 100 people listed in that table
I need to filter out the people using different criteria's and put them in groups, problem is when i start excluding on the 4th-5th level, performance issues come up and it becomes slow
with lst_tous_movements as (
select
t1.refid_eClinibase
t1.[dthrfinmouvement]
t1.[unite_service_id]
t1.[unite_service_suiv_id]
from sometable t1
)
,lst_patients_hospitalisés as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
where
t1.[dthrfinmouvement] = '4000-01-01'
)
,lst_patients_admisUIB_transferes as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
left join lst_patients_hospitalisés t2 on t1.refid_eClinibase = t2.refid_eClinibase
where
t1.[unite_service_id] = 4
and t1.[unite_service_suiv_id] <> 0
and t2.refid_eClinibase is null
)
,lst_patients_admisUIB_nonTransferes as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
left join lst_patients_admisUIB_transferes t2 on t1.refid_eClinibase = t2.refid_eClinibase
left join lst_patients_hospitalisés t3 on t1.refid_eClinibase = t3.refid_eClinibase
where
t1.[unite_service_id] = 4
and t1.[unite_service_suiv_id] = 0
and t2.refid_eClinibase is null
and t3.refid_eClinibase is null
)
,lst_patients_autres as (
select distinct
t1.refid_eClinibase
from lst_patients t1
left join lst_patients_admisUIB_transferes t2 on t1.refid_eClinibase = t2.refid_eClinibase
left join lst_patients_hospitalisés t3 on t1.refid_eClinibase = t3.refid_eClinibase
left join lst_patients_admisUIB_nonTransferes t4 on t1.refid_eClinibase = t4.refid_eClinibase
where
t2.refid_eClinibase is null
and t3.refid_eClinibase is null
and t4.refid_eClinibase is null
)
as you can see i have a multi level filtering out going on here...
1st i get the people where t1.[dthrfinmouvement] = '4000-01-01'
2nd i get the people with another criteria EXCLUDING the 1st group
3rd i get the people with yet another criteria EXCLUDING the 1st and
the 2nd group
etc..
when i get to the 4th level, my query takes 6 - 10 seconds to complete
is there any way to speed this up ?
this is my dataset i'm working with:
+------------------+-------------------------------+------------------+------------------+-----------------------+
| refid_eClinibase | nodossierpermanent_eClinibase | dthrfinmouvement | unite_service_id | unite_service_suiv_id |
+------------------+-------------------------------+------------------+------------------+-----------------------+
| 25611 | P0017379 | 2013-04-27 | 58 | 0 |
| 25611 | P0017379 | 2013-05-02 | 4 | 2 |
| 25611 | P0017379 | 2013-05-18 | 2 | 0 |
| 85886 | P0077918 | 2013-04-10 | 58 | 0 |
| 85886 | P0077918 | 2013-05-06 | 6 | 12 |
| 85886 | P0077918 | 4000-01-01 | 12 | 0 |
| 91312 | P0083352 | 2013-07-24 | 3 | 14 |
| 91312 | P0083352 | 2013-07-24 | 14 | 3 |
| 91312 | P0083352 | 2013-07-30 | 3 | 8 |
| 91312 | P0083352 | 4000-01-01 | 8 | 0 |
| 93835 | P0085879 | 2013-04-30 | 58 | 0 |
| 93835 | P0085879 | 2013-05-07 | 4 | 2 |
| 93835 | P0085879 | 2013-05-16 | 2 | 0 |
| 93835 | P0085879 | 2013-05-22 | 58 | 0 |
| 93835 | P0085879 | 2013-05-24 | 4 | 0 |
| 93835 | P0085879 | 2013-05-31 | 58 | 0 |
| 93836 | P0085880 | 2013-05-20 | 58 | 0 |
| 93836 | P0085880 | 2013-05-22 | 4 | 2 |
| 93836 | P0085880 | 2013-05-31 | 2 | 0 |
| 97509 | P0089576 | 2013-04-09 | 58 | 0 |
| 97509 | P0089576 | 2013-04-11 | 4 | 0 |
| 102787 | P0094886 | 2013-04-08 | 58 | 0 |
| 102787 | P0094886 | 2013-04-11 | 4 | 2 |
| 102787 | P0094886 | 2013-05-21 | 2 | 0 |
| 103029 | P0095128 | 2013-04-04 | 58 | 0 |
| 103029 | P0095128 | 2013-04-10 | 4 | 1 |
| 103029 | P0095128 | 2013-05-03 | 1 | 0 |
| 103813 | P0095922 | 2013-07-02 | 58 | 0 |
| 103813 | P0095922 | 2013-07-03 | 4 | 6 |
| 103813 | P0095922 | 2013-08-14 | 6 | 0 |
| 105106 | P0097215 | 2013-08-09 | 58 | 0 |
| 105106 | P0097215 | 2013-08-13 | 4 | 0 |
| 105106 | P0097215 | 2013-08-14 | 58 | 0 |
| 105106 | P0097215 | 4000-01-01 | 4 | 0 |
| 106223 | P0098332 | 2013-06-11 | 1 | 0 |
| 106223 | P0098332 | 2013-08-01 | 58 | 0 |
| 106223 | P0098332 | 4000-01-01 | 1 | 0 |
| 106245 | P0098354 | 2013-04-02 | 58 | 0 |
| 106245 | P0098354 | 2013-05-24 | 58 | 0 |
| 106245 | P0098354 | 2013-05-29 | 4 | 1 |
| 106245 | P0098354 | 2013-07-12 | 1 | 0 |
| 106280 | P0098389 | 2013-04-07 | 58 | 0 |
| 106280 | P0098389 | 2013-04-09 | 4 | 0 |
| 106416 | P0098525 | 2013-04-19 | 58 | 0 |
| 106416 | P0098525 | 2013-04-23 | 4 | 0 |
| 106444 | P0098553 | 2013-04-22 | 58 | 0 |
| 106444 | P0098553 | 2013-04-25 | 4 | 0 |
| 106609 | P0098718 | 2013-05-08 | 58 | 0 |
| 106609 | P0098718 | 2013-05-10 | 4 | 11 |
| 106609 | P0098718 | 2013-07-24 | 11 | 12 |
| 106609 | P0098718 | 4000-01-01 | 12 | 0 |
| 106616 | P0098725 | 2013-05-09 | 58 | 0 |
| 106616 | P0098725 | 2013-05-09 | 4 | 1 |
| 106616 | P0098725 | 2013-07-27 | 1 | 0 |
| 106698 | P0098807 | 2013-05-16 | 58 | 0 |
| 106698 | P0098807 | 2013-05-22 | 4 | 6 |
| 106698 | P0098807 | 2013-06-14 | 6 | 1 |
| 106698 | P0098807 | 2013-06-28 | 1 | 0 |
| 106714 | P0098823 | 2013-05-20 | 58 | 0 |
| 106714 | P0098823 | 2013-05-21 | 58 | 0 |
| 106714 | P0098823 | 2013-05-24 | 58 | 0 |
| 106729 | P0098838 | 2013-05-21 | 58 | 0 |
| 106729 | P0098838 | 2013-05-23 | 4 | 1 |
| 106729 | P0098838 | 2013-06-03 | 1 | 0 |
| 107038 | P0099147 | 2013-06-25 | 58 | 0 |
| 107038 | P0099147 | 2013-06-28 | 4 | 1 |
| 107038 | P0099147 | 2013-07-04 | 1 | 0 |
| 107038 | P0099147 | 2013-08-13 | 58 | 0 |
| 107038 | P0099147 | 2013-08-15 | 4 | 6 |
| 107038 | P0099147 | 4000-01-01 | 6 | 0 |
| 107082 | P0099191 | 2013-06-29 | 58 | 0 |
| 107082 | P0099191 | 2013-07-04 | 4 | 6 |
| 107082 | P0099191 | 2013-07-19 | 6 | 0 |
| 107157 | P0099267 | 4000-01-01 | 13 | 0 |
| 107336 | P0099446 | 4000-01-01 | 6 | 0 |
+------------------+-------------------------------+------------------+------------------+-----------------------+
thanks.
It is hard to understand exactly what all your rules are from the question, but the general approach should be to add a "Grouping" column to a singl query that uses a CASE statement to categorize the people.
The conditions in a CASE are evaluated in order, so that if the first criteria is met, then the subsequent criteria are not even evaluated for that row.
Here is some code to get you started....
select t1.refid_eClinibase
,t1.[dthrfinmouvement]
,t1.[unite_service_id]
,t1.[unite_service_suiv_id]
CASE WHEN [dthrfinmouvement] = '4000-01-01' THEN 'Group1 Label'
WHEN condition2 = something THEN 'Group2 Label'
....
WHEN conditionN = something THEN 'GroupN Label'
ELSE 'Catch All Label'
END as person_category
from sometable t1