Kusto: How can I get the value from the column that doesn't participate in a SUMMARIZE? - azure-log-analytics

Having the below table and Kusto query, how can I obtain a result that has the Purchase column?
let ProductsTable = datatable(Supplier: string, Fruit: string, Price: int, Purchase: datetime)
[
'Contoso', 'Grapes', 220, datetime(2018-10-01 01:00),
'Fabrikam', 'Lemons', 31, datetime(2018-10-01 02:00),
'Contoso', 'Lemons', 29, datetime(2018-10-02 03:00),
'Contoso', 'Grapes', 210, datetime(2018-10-02 04:00),
'Fabrikam', 'Lemons', 30, datetime(2018-10-03 05:00),
'Contoso', 'Bananas', 12, datetime(2018-10-03 06:00),
'Contoso', 'Bananas', 12, datetime(2018-10-04 07:00),
'Contoso', 'Lemons', 29, datetime(2018-10-04 08:00),
'Contoso', 'Grapes', 200, datetime(2018-10-05 09:00),
];
ProductsTable
| summarize Price = min(Price) by Supplier, Fruit
| order by Supplier asc, Fruit asc, Price asc
Result
Contoso Bananas 12
Contoso Grapes 200
Contoso Lemons 29
Fabrikam Lemons 30
DESIRED Result
Contoso Bananas 12 2018-10-03 06:00
Contoso Grapes 200 2018-10-05 09:00
Contoso Lemons 29 2018-10-02 03:00
Fabrikam Lemons 30 2018-10-03 05:00
I know that there could be multiple results, for example for Contoso-Bananas-12 we can have any of the following
2018-10-03 06:00
2018-10-04 07:00


try using arg_min(): https://learn.microsoft.com/en-us/azure/kusto/query/arg-min-aggfunction
let ProductsTable = datatable(Supplier: string, Fruit: string, Price: int, Purchase: datetime)
[
'Contoso', 'Grapes', 220, datetime(2018-10-01 01:00),
'Fabrikam', 'Lemons', 31, datetime(2018-10-01 02:00),
'Contoso', 'Lemons', 29, datetime(2018-10-02 03:00),
'Contoso', 'Grapes', 210, datetime(2018-10-02 04:00),
'Fabrikam', 'Lemons', 30, datetime(2018-10-03 05:00),
'Contoso', 'Bananas', 12, datetime(2018-10-03 06:00),
'Contoso', 'Bananas', 12, datetime(2018-10-04 07:00),
'Contoso', 'Lemons', 29, datetime(2018-10-04 08:00),
'Contoso', 'Grapes', 200, datetime(2018-10-05 09:00),
];
ProductsTable
| summarize Price = arg_min(Price, *) by Supplier, Fruit
| order by Supplier asc, Fruit asc, Price asc


I'm new to Kusto but I found below could return the same output by using partition by and row_number() in Kusto.
KQL:
let ProductsTable = datatable(Supplier: string, Fruit: string, Price: int, Purchase: datetime)
[
'Contoso', 'Grapes', 220, datetime(2018-10-01 01:00),
'Fabrikam', 'Lemons', 31, datetime(2018-10-01 02:00),
'Contoso', 'Lemons', 29, datetime(2018-10-02 03:00),
'Contoso', 'Grapes', 210, datetime(2018-10-02 04:00),
'Fabrikam', 'Lemons', 30, datetime(2018-10-03 05:00),
'Contoso', 'Bananas', 12, datetime(2018-10-03 06:00),
'Contoso', 'Bananas', 12, datetime(2018-10-04 07:00),
'Contoso', 'Lemons', 29, datetime(2018-10-04 08:00),
'Contoso', 'Grapes', 200, datetime(2018-10-05 09:00),
];
ProductsTable
| partition by Fruit
( sort by Price asc
| extend rn = row_number(1, prev(Supplier) != Supplier)
| where rn == 1
)
| project Supplier, Fruit, Price, Purchase
| sort by Supplier asc, Fruit asc;
Results:
Supplier Fruit Price Purchase
Contoso Bananas 12 2018-10-03 06:00:00.0000000
Contoso Grapes 200 2018-10-05 09:00:00.0000000
Contoso Lemons 29 2018-10-02 03:00:00.0000000
Fabrikam Lemons 30 2018-10-03 05:00:00.0000000
However, this is not as efficient as Yoni L's solution. I was used to writing similar queries using Redshift/PostgreSQL so I was wondering if this could be done by row_num() which is a very common window function.

Related

how to do list_agg with a character limit of 1440 characters in Snowflake

I have a table as below, I have 1775 ids and length of id column is 10 characters, I want to create multiple groups of list_agg of ids with a limit of not more than 1440 characters to distribute 1775 ids into groups
id
distributor_name
1234567890
Sample_name1
2345678901
Sample_name1
3456789012
Sample_name1
4567890123
Sample_name2
5678901234
Sample_name2
6789012345
Sample_name3
7890123456
Sample_name3
8901234567
Sample_name3
Required output is:
group
id_count
list_agg
1
120
1234567890,2345678901,3456789012...
2
122
7890123456,5678901234,8901234567...
Very much appreciate your help!

If your ID space is symmetrically distributed you can use WIDTH_BUCKET
with data1 as (
select
row_number() over (order by true)-1 as rn
from table(generator(rowcount=>100))
)
select
width_bucket(rn, 0, 100, 5) as group_id,
count(*) as c,
array_agg(rn) within group(order by rn) as bucket_values
from data1
group by 1
order by 1;
GROUP_ID
C
BUCKET_VALUES
1
20
[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 ]
2
20
[ 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 ]
3
20
[ 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59 ]
4
20
[ 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79 ]
5
20
[ 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 ]
If your data is not symmetrical, you can allocate row numbers to each row, and then shave the yack again.
you can also be data driven:
width_bucket(rn, (select min(rn) from data1), (select max(rn) from data1)+1, 5) as group_id,

It's easier done with array_agg but if you must use listagg, here is a spin on Simeon's answer. The basic idea is to keep track of length of numbers when stitched together and also account for the number of commas so we don't go over 1440 char limit.
create or replace temporary table t as
select row_number() over (order by true)-1 as id,
uniform(1000000000, 1999999999, random()) as num
from table(generator(rowcount=>1775));
with cte as
(select *, ceil((sum(len(num)) over (order by id) + count(num) over (order by id) -1)/1440) as group_id
from t)
select group_id,
count(num) as id_count,
listagg(num,',') as id_list,
len(id_list) as len_check
from cte
group by group_id
order by group_id;

Average with same id

INSERT INTO `iot_athlete_ind_cont_non_cur_chlng_consp`
(`aicicc_id`, `aicid_id`, `aicidl_id`, `aica_id`, `at_id`, `aicicc_type`, `aicicc_tp`, `aicicc_attempt`, `aicicc_lastposition`, `aicicc_status`, `pan_percentile`, `age_percentile`, `created_at`, `updated_at`) VALUES
(270, 3, 14, 17, 7, 'Time', 50, 1, 5, 'Active', NULL, NULL, '2022-11-15 08:34:40', '2022-11-15 08:34:40'),
(271, 3, 14, 20, 7, 'Time', 60, 1, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(272, 3, 14, 21, 7, 'Time', 70, 1, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(273, 3, 14, 17, 7, 'Time', 90, 2, 5, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:13:42'),
(274, 3, 14, 20, 7, 'Time', 40, 2, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(275, 3, 14, 21, 7, 'Time', 70, 2, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(276, 3, 10, 17, 3, 'Time', 80, 1, 5, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:10:25'),
(277, 3, 10, 20, 3, 'Time', 60, 1, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:10:43'),
(278, 3, 10, 21, 3, 'Time', 60, 1, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:11:03');
I need 3 rows form this table with average like this
at_id
aicicc_attempt
average
7
1
60
7
2
66.66
3
1
66.66
my query is
SELECT DISTINCT at_id, AVG(aicicc_tp) OVER (PARTITION BY aicicc_attempt) as average
FROM iot_athlete_ind_cont_non_cur_chlng_consp
WHERE aicid_id = '3';
but its not working properly average calculation is wrong here in my query.

Let's first say that's basically just a combination of average and GROUP BY:
SELECT at_id, aicicc_attempt,
AVG(aicicc_tp) AS average
FROM iot_athlete_ind_cont_non_cur_chlng_consp
GROUP BY at_id, aicicc_attempt
ORDER BY at_id DESC;
(I don't know if the ORDER BY clause is necessary, otherwise the last row appears as first row).
The "problem" might be that the "average" column will not exactly be shown as you wanted. For example, let's assume the column "aicicc_tp" has been declared as data type int and you are using a SQLServer DB. In this case, your outcome will also show the average as integer:
at_id
aicicc_attempt
average
7
1
60
7
2
66
3
1
66
You will need to cast the column as float and format the outcome to generate exactly the desired result (of course, the correct average for your sample data is 66.67, not 66.66):
SELECT at_id, aicicc_attempt,
FORMAT(AVG(CAST(aicicc_tp AS float)), '##.##') AS average
FROM iot_athlete_ind_cont_non_cur_chlng_consp
GROUP BY at_id, aicicc_attempt
ORDER BY at_id DESC;
at_id
aicicc_attempt
average
7
1
60
7
2
66.67
3
1
66.67
If you are using another DB type, the concrete query will differ. That's why it's recommended to tag your DB type.
EDIT because you changed the question:
Adding the WHERE clause that is now mentioned in your question does not change the result:
SELECT at_id, aicicc_attempt,
FORMAT(AVG(CAST(aicicc_tp AS float)), '##.##') AS average
FROM iot_athlete_ind_cont_non_cur_chlng_consp
WHERE aicid_id = 3
GROUP BY at_id, aicicc_attempt
ORDER BY at_id DESC;
The outcome is still the same and correct:
at_id
aicicc_attempt
average
7
1
60
7
2
66.67
3
1
66.67
And a last note: If you want to keep your PARTITION BY idea, your query must be like this:
SELECT DISTINCT at_id, aicicc_attempt,
AVG(aicicc_tp)
OVER (PARTITION BY at_id, aicicc_attempt) AS average
FROM iot_athlete_ind_cont_non_cur_chlng_consp
WHERE aicid_id = 3
ORDER BY at_id DESC;
But I don't recommend this because of some disadvantages:
The usage of DISTINCT often slows down the query.
This will not solve the issue the average is possibly built as integer which is not intended according to your description.
Window functions often differ depending on the DB type, GROUP BY works the same on each DB type.
You can verify all these things here: db<>fiddle

For the average, you may use AVG()
Solution below is for sql-server, as you didn't tag your rdbms.
SELECT at_id, aicicc_attempt, AVG(aicicc_tp) FROM iot_athlete_ind_cont_non_cur_chlng_consp
GROUP BY at_id, aicicc_attempt

with cte (aicicc_id, aicid_id,aicidl_id, aica_id, at_id, aicicc_type, aicicc_tp, aicicc_attempt, aicicc_lastposition, aicicc_status,
pan_percentile, age_percentile, created_at, updated_at) as (
values (270, 3, 14, 17, 7, 'Time', 50, 1, 5, 'Active', NULL, NULL, '2022-11-15 08:34:40', '2022-11-15 08:34:40'),
(271, 3, 14, 20, 7, 'Time', 60, 1, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(272, 3, 14, 21, 7, 'Time', 70, 1, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(273, 3, 14, 17, 7, 'Time', 90, 2, 5, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:13:42'),
(274, 3, 14, 20, 7, 'Time', 40, 2, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(275, 3, 14, 21, 7, 'Time', 70, 2, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 08:35:21'),
(276, 3, 10, 17, 3, 'Time', 80, 1, 5, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:10:25'),
(277, 3, 10, 20, 3, 'Time', 60, 1, 231, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:10:43'),
(278, 3, 10, 21, 3, 'Time', 60, 1, 20, 'Active', NULL, NULL, '2022-11-15 08:34:45', '2022-11-15 12:11:03')
)
select at_id, aicicc_attempt, AVG(aicicc_tp) from cte group by 1,2
Result :

Divide result of 2 queries element wis

I can't find a way to divide the result of my 2 queries.
They look like that :
SELECT periode, cee_ref_no, SUM(somme) AS total FROM V_STAT_NAMUR
WHERE code_ref_no IN (1, 2, 3, 4, 5, 6, 193, 215, 237, 259, 281)
AND periode BETWEEN '201401' AND '201412'
AND cee_ref_no = '961'
GROUP BY periode, cee_ref_no
ORDER BY periode;
AND
SELECT periode, cee_ref_no, SUM(somme) AS total FROM V_STAT_NAMUR
WHERE code_ref_no IN (7, 8, 9, 10, 205, 227, 249, 271, 293)
AND periode BETWEEN '201401' AND '201412'
AND cee_ref_no = '961'
GROUP BY periode, cee_ref_no
ORDER BY periode;
They look pretty similar, and both return something like this :
DATE | CEE_REF_NO | TOTAL
201401 | 961 | 10713
201402 | 961 | 9593
... | 961 | ...
201412 | 961 | 10426
How can I merge these to obtain something like this :
DATE | CEE_REF_NO | TOTAL
201401 | 961 | Total Q1/ Total Q2
201402 | 961 | Total Q1/ Total Q2
... | 961 | ...
201412 | 961 | Total Q1/ Total Q2
Everything I tried returned either only one row, or 12 rows with the same result.
Thanks a lot !

You can try with this:
select q1.periode, q1.cee_ref_no, q1.total as Total1, q2.total as Total2, q1.total/q2.total as Division
from (
SELECT periode, cee_ref_no, SUM(somme) AS total FROM V_STAT_NAMUR
WHERE code_ref_no IN (1, 2, 3, 4, 5, 6, 193, 215, 237, 259, 281)
AND periode BETWEEN '201401' AND '201412'
AND cee_ref_no = '961'
GROUP BY periode, cee_ref_no
) q1
join (
SELECT periode, cee_ref_no, SUM(somme) AS total FROM V_STAT_NAMUR
WHERE code_ref_no IN (7, 8, 9, 10, 205, 227, 249, 271, 293)
AND periode BETWEEN '201401' AND '201412'
AND cee_ref_no = '961'
GROUP BY periode, cee_ref_no
) q2
on q1.Periode=q2.Periode
and q1.cee_ref_no=q2.cee_ref_no
Basicaly you have just to create 2 subselect with your queries and join them by period and cee_ref_no (in case you were going to include more than 1 cee_ref_no, in your example there is just one). Then you will be able to divide the Total from q1 and q2.
Take care about the join, I don't know if your data will have information for all the months in both queries.
PS: Query not tested, written directly on editor.

Use conditional aggregation:
SELECT periode, cee_ref_no,
SUM(CASE WHEN code_ref_no IN (1, 2, 3, 4, 5, 6, 193, 215, 237, 259, 281) THEN somme ELSE 0 END) AS total_1,
SUM(CASE WHEN code_ref_no IN (7, 8, 9, 10, 205, 227, 249, 271, 293) THEN somme ELSE 0 END) AS total_2,
(SUM(CASE WHEN code_ref_no IN (1, 2, 3, 4, 5, 6, 193, 215, 237, 259, 281) THEN somme ELSE 0 END) /
SUM(CASE WHEN code_ref_no IN (7, 8, 9, 10, 205, 227, 249, 271, 293) THEN sommeEND)
) AS ratio
FROM V_STAT_NAMUR
WHERE AND
periode BETWEEN '201401' AND '201412'
GROUP BY periode, cee_ref_no
ORDER BY periode;

Try this
Select periode, cee_ref_no, total1/total2 as Total
From (
SELECT periode, cee_ref_no,
sum(Case when code_ref_no in (1, 2, 3, 4, 5, 6, 193, 215, 237, 259, 281) Then somme else 0 end) as total1,
sum(Case when code_ref_no in (7, 8, 9, 10, 205, 227, 249, 271, 293) Then somme else 0 end) as total2
From my_table
WHERE code_ref_no IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 193, 205, 215, 227, 237, 249, 259, 271, 281, 293)
AND periode BETWEEN '201401' AND '201412'
AND cee_ref_no = '961'
GROUP BY periode, cee_ref_no
)
ORDER BY periode;

Daily Attendance Summed Weekly

Greetings all,
I’m wondering if I could get some insights on the best way to get Attendance data.
I need get every viable in(AttendanceTypeID = 1) and out(AttendanceTypeID = 2) pairs in a day. Sum up the time values up per employee by week starting Sunday and ending Saturday. The closet in to the an out is the business rule for what is needed, and there may be many in/out pairs in a single day. I am also anchored to SQL 2008 logic since some of our customers are still using SQL 2008. I have seen a view examples using CTE’s, which I prefer, but they had used lead,lag, LastVal, NestVal functions which start in 2012.
Output.
https://forums.asp.net/t/1946217.aspx?Time+Attendance+working+hours
https://www.red-gate.com/simple-talk/sql/t-sql-programming/solving-complex-t-sql-problems,-step-by-step/
CREATE TABLE tblAttendance
(
[AttendanceID] int,
[DepartmentID] int,
[EmployeeID] int,
[AttendanceDate] datetime,
[AttendanceTime] varchar(8),
[AttendanceTypeID] int,
[AttendanceCodeID] int,
[Submitted] int
);
INSERT INTO tblAttendance
([AttendanceID], [DepartmentID], [EmployeeID], [AttendanceDate],
[AttendanceTime], [AttendanceTypeID], [AttendanceCodeID], [Submitted])
VALUES
(838, 33, 260, '2018-02-26 00:00:00', '8:00:00', 1, 1, 0),
(839, 33, 260, '2018-02-26 00:00:00', '22:00:00', 2, 1, 0),
(836, 41, 344, '2018-02-26 00:00:00', '9:00:00', 1, 1, 0),
(837, 41, 344, '2018-02-26 00:00:00', '22:00:00', 2, 1, 0),
(812, 33, 348, '2018-02-26 00:00:00', '8:00:00', 1, 1, 0),
(813, 33, 348, '2018-02-26 00:00:00', '12:00:00', 2, 1, 0),
(814, 33, 350, '2018-02-26 00:00:00', '8:00:00', 1, 1, 0),
(815, 33, 350, '2018-02-26 00:00:00', '12:00:00', 2, 1, 0),
(930, 7, 361, '2018-02-26 00:00:00', '7:00:00', 1, 1, 0),
(931, 7, 361, '2018-02-26 00:00:00', '9:00:00', 2, 1, 0),
(940, 19, 361, '2018-02-26 00:00:00', '8:55:00', 1, 1, 0),
(941, 19, 361, '2018-02-26 00:00:00', '10:00:00', 2, 1, 0),
(824, 1, 114, '2018-02-27 00:00:00', '23:59:57', 2, 1, 0),
(816, 33, 206, '2018-02-27 00:00:00', '11:12:00', 1, 1, 0),
(819, 33, 206, '2018-02-27 00:00:00', '11:16:00', 2, 1, 0),
(822, 1, 350, '2018-02-27 00:00:00', '0:00:00', 1, 1, 0),
(829, 33, 350, '2018-02-27 00:00:00', '16:15:30', 1, 1, 0),
(830, 33, 359, '2018-02-27 00:00:00', '16:15:30', 1, 1, 0),
(932, 7, 361, '2018-02-27 00:00:00', '7:00:00', 1, 1, 0),
(933, 7, 361, '2018-02-27 00:00:00', '9:00:00', 2, 1, 0),
(942, 19, 361, '2018-02-27 00:00:00', '8:30:00', 1, 1, 0),
(943, 19, 361, '2018-02-27 00:00:00', '10:30:00', 2, 1, 0),
(835, 33, 206, '2018-02-28 00:00:00', '9:23:00', 1, 1, 0),
(934, 7, 361, '2018-02-28 00:00:00', '7:00:00', 1, 1, 0),
(935, 7, 361, '2018-02-28 00:00:00', '9:00:00', 2, 1, 0),
(944, 19, 361, '2018-02-28 00:00:00', '7:00:00', 1, 1, 0),
(945, 19, 361, '2018-02-28 00:00:00', '9:00:00', 2, 1, 0),
(936, 7, 361, '2018-03-01 00:00:00', '7:00:00', 1, 1, 0),
(937, 7, 361, '2018-03-01 00:00:00', '9:00:00', 2, 1, 0),
(946, 19, 361, '2018-03-01 00:00:00', '9:00:00', 1, 1, 0),
(947, 19, 361, '2018-03-01 00:00:00', '9:30:00', 2, 1, 0),
(840, 33, 350, '2018-03-02 00:00:00', '8:21:00', 1, 1, 0),
(841, 33, 350, '2018-03-02 00:00:00', '8:22:00', 2, 1, 0),
(938, 7, 361, '2018-03-02 00:00:00', '7:00:00', 1, 1, 0),
(939, 7, 361, '2018-03-02 00:00:00', '9:00:00', 2, 1, 0),
(948, 19, 361, '2018-03-02 00:00:00', '9:01:00', 1, 1, 0),
(949, 19, 361, '2018-03-02 00:00:00', '10:00:00', 2, 1, 0),
(894, 33, 260, '2018-03-05 00:00:00', '6:00:00', 1, 1, 0),
(895, 33, 260, '2018-03-05 00:00:00', '7:00:00', 2, 1, 0),
(859, 33, 348, '2018-03-05 00:00:00', '9:30:00', 1, 1, 0),
(860, 33, 348, '2018-03-05 00:00:00', '9:30:00', 1, 1, 0),
(842, 33, 206, '2018-03-06 00:00:00', '13:21:00', 1, 1, 0),
(856, 33, 206, '2018-03-06 00:00:00', '2:51:27', 2, 1, 0),
(848, 33, 206, '2018-03-06 00:00:00', '13:57:00', 2, 1, 0),
(843, 33, 260, '2018-03-06 00:00:00', '14:00:00', 1, 1, 0),
(861, 33, 348, '2018-03-06 00:00:00', '9:30:00', 1, 1, 0),
(862, 33, 348, '2018-03-06 00:00:00', '9:31:00', 1, 1, 0),
(853, 33, 350, '2018-03-06 00:00:00', '2:32:36', 1, 1, 0),
(854, 33, 350, '2018-03-06 00:00:00', '2:48:54', 1, 1, 0),
(855, 33, 350, '2018-03-06 00:00:00', '2:49:11', 1, 1, 0),
(857, 33, 350, '2018-03-06 00:00:00', '2:52:19', 1, 1, 0),
(844, 33, 350, '2018-03-06 00:00:00', '13:32:00', 1, 1, 0),
(846, 33, 350, '2018-03-06 00:00:00', '13:53:00', 1, 1, 0),
(845, 33, 350, '2018-03-06 00:00:00', '13:35:00', 2, 1, 0),
(850, 33, 350, '2018-03-06 00:00:00', '14:06:00', 2, 1, 0),
(847, 33, 359, '2018-03-06 00:00:00', '13:56:00', 1, 1, 0),
(858, 33, 359, '2018-03-06 00:00:00', '14:52:00', 1, 1, 0),
(852, 33, 359, '2018-03-06 00:00:00', '2:29:06', 2, 1, 0),
(851, 33, 359, '2018-03-06 00:00:00', '14:09:00', 2, 1, 0),
(896, 33, 260, '2018-03-07 00:00:00', '6:00:00', 1, 1, 0),
(897, 33, 260, '2018-03-07 00:00:00', '7:00:00', 2, 1, 0),
(907, 33, 348, '2018-03-07 00:00:00', '7:00:00', 1, 1, 0),
(908, 33, 348, '2018-03-07 00:00:00', '8:00:00', 2, 1, 0),
(893, 33, 350, '2018-03-07 00:00:00', '14:36:40', 1, 1, 0),
(915, 33, 350, '2018-03-07 00:00:00', '17:00:00', 2, 1, 0),
(913, 33, 359, '2018-03-07 00:00:00', '8:00:00', 1, 1, 0),
(914, 33, 359, '2018-03-07 00:00:00', '17:00:00', 2, 1, 0),
(923, 33, 348, '2018-03-08 00:00:00', '7:00:00', 1, 1, 0),
(925, 33, 348, '2018-03-08 00:00:00', '11:00:00', 1, 1, 0),
(928, 33, 348, '2018-03-08 00:00:00', '11:45:00', 1, 1, 0),
(927, 33, 348, '2018-03-08 00:00:00', '11:35:00', 2, 1, 0),
(924, 33, 348, '2018-03-08 00:00:00', '12:00:00', 2, 1, 0),
(926, 33, 348, '2018-03-08 00:00:00', '13:00:00', 2, 1, 0),
(898, 33, 350, '2018-03-08 00:00:00', '11:42:57', 1, 1, 0),
(906, 33, 206, '2018-03-09 00:00:00', '8:14:43', 1, 1, 0),
(905, 33, 260, '2018-03-09 00:00:00', '8:12:53', 1, 1, 0),
(972, 33, 348, '2018-03-09 00:00:00', '8:00:00', 1, 1, 0),
(911, 33, 350, '2018-03-09 00:00:00', '10:43:59', 1, 1, 0),
(912, 33, 350, '2018-03-09 00:00:00', '10:44:22', 1, 1, 0),
(917, 33, 350, '2018-03-09 00:00:00', '12:44:48', 1, 1, 0),
(929, 33, 350, '2018-03-09 00:00:00', '15:18:17', 1, 1, 0),
(921, 33, 350, '2018-03-09 00:00:00', '12:50:14', 2, 1, 0),
(918, 33, 359, '2018-03-09 00:00:00', '12:44:48', 1, 1, 0),
(922, 33, 359, '2018-03-09 00:00:00', '12:50:14', 2, 1, 0),
(970, 33, 350, '2018-03-11 00:00:00', '11:25:00', 1, 1, 0),
(968, 33, 260, '2018-03-12 00:00:00', '7:00:00', 1, 1, 0),
(962, 33, 348, '2018-03-12 00:00:00', '7:00:00', 1, 1, 0),
(969, 33, 348, '2018-03-12 00:00:00', '9:00:00', 2, 1, 0),
(951, 33, 350, '2018-03-12 00:00:00', '8:54:07', 1, 1, 0),
(953, 33, 350, '2018-03-12 00:00:00', '10:31:29', 1, 1, 0),
(954, 33, 350, '2018-03-12 00:00:00', '10:34:18', 1, 1, 0),
(950, 33, 350, '2018-03-12 00:00:00', '8:21:11', 2, 1, 0),
(952, 33, 350, '2018-03-12 00:00:00', '9:02:26', 2, 1, 0),
(955, 33, 359, '2018-03-12 00:00:00', '10:37:26', 1, 1, 0),
(959, 33, 206, '2018-03-13 00:00:00', '1:01:38', 1, 1, 0),
(961, 33, 206, '2018-03-13 00:00:00', '14:00:51', 1, 1, 0),
(975, 33, 295, '2018-03-13 00:00:00', '7:00:00', 1, 1, 0),
(976, 33, 295, '2018-03-13 00:00:00', '8:00:00', 2, 1, 0),
(957, 33, 350, '2018-03-13 00:00:00', '11:26:52', 1, 1, 0),
(958, 33, 359, '2018-03-13 00:00:00', '1:00:12', 1, 1, 0),
(965, 33, 359, '2018-03-13 00:00:00', '21:00:00', 1, 1, 0),
(960, 33, 359, '2018-03-13 00:00:00', '13:14:14', 2, 1, 0),
(967, 33, 359, '2018-03-13 00:00:00', '22:00:00', 2, 1, 0),
(964, 33, 350, '2018-03-14 00:00:00', '14:34:36', 2, 1, 0),
(963, 33, 359, '2018-03-14 00:00:00', '13:45:25', 1, 1, 0)
;
Here is the query I used to return the data above:
SELECT AttendanceID , DepartmentID , EmployeeID , AttendanceDate , AttendanceTime , AttendanceTypeID , AttendanceCodeID , Submitted
FROM tblAttendance
WHERE AttendanceDate BETWEEN #StartDate AND #EndDate
AND AttendanceTypeID IN (1,2) -- 1 = in, and 2 = out
AND AttendanceCodeID = 1
ORDER BY
AttendanceDate
,AttendanceTime
The tables added below show the steps that are needed to get the end results.
First a data example:
+------------+----------------+----------------+------------------+
| EmployeeID | AttendanceDate | AttendanceTime | AttendanceTypeID |
+------------+----------------+----------------+------------------+
| 350 | 3/6/18 | 2:32:36 | 1 |
| 350 | 3/6/18 | 2:48:54 | 1 |
| 350 | 3/6/18 | 2:49:11 | 1 |
| 350 | 3/6/18 | 2:52:19 | 1 |
| 350 | 3/6/18 | 13:32:00 | 1 |
| 350 | 3/6/18 | 13:53:00 | 1 |
| 350 | 3/6/18 | 13:35:00 | 2 |
| 350 | 3/6/18 | 14:06:00 | 2 |
| 350 | 3/7/18 | 14:36:40 | 1 |
| 350 | 3/7/18 | 17:00:00 | 2 |
| 350 | 3/8/18 | 11:42:57 | 1 |
| 350 | 3/9/18 | 10:43:59 | 1 |
| 350 | 3/9/18 | 10:44:22 | 1 |
| 350 | 3/9/18 | 12:44:48 | 1 |
| 350 | 3/9/18 | 15:18:17 | 1 |
| 350 | 3/9/18 | 12:50:14 | 2 |
| 350 | 3/9/18 | 10:43:59 | 1 |
| 350 | 3/9/18 | 10:44:22 | 1 |
| 350 | 3/9/18 | 12:44:48 | 1 |
| 350 | 3/9/18 | 15:18:17 | 1 |
| 350 | 3/9/18 | 12:50:14 | 2 |
+------------+----------------+----------------+------------------+
Second Pair up the matching data in out pairs, and get there time difference.
+------------+----------------+------------------+------------------+
| EmployeeID | AttendanceDate | AttendanceTime | Pair Total |
+------------+----------------+------------------+------------------+
| 350 | 3/6/18 |13:35:00 -13:32:00| 0:03:00 |
| 350 | 3/6/18 |14:06:00 -13:53:00| 0:13:00 |
| 350 | 3/7/18 |17:00:00 -14:36:40| 2:23:20 |
| 350 | 3/9/18 |12:44:48 -12:44:48| 0:05:26 |
+------------+----------------+------------------+------------------+
Third the compiled data for the employee during that week.
+------------+-------------------+----------------------+
| EmployeeID | AttendanceWeek | AttendanceTime Total |
+------------+-------------------+----------------------+
| 350 | 3/4/18 to 3/10/18 | 2:44:46 |
+------------+-------------------+----------------------+
Hope that this helps narrow the focus.
Thank you.

First you need to make sure that Sunday is the default value for the start week.
--see what day is the default start day of the week
SELECT ##DATEFIRST
--set it to Sunday if value isn't 7
SET DATEFIRST 7;
I think I figured out what you were asking by using a CTE, a couple SUM CASE statements, and the DATEPART function.
DECLARE #StartDate DATETIME = '2/25/2018 12:00AM';
DECLARE #EndDate DATETIME = '3/17/2018 11:59PM';
--Count number of 1's and 2's in a day
--Group by EmployeeId and AttendanceDate
WITH daily1And2 AS(
SELECT EmployeeID,
AttendanceDate,
SUM(CASE WHEN AttendanceTypeID = 1 THEN 1 ELSE 0 END) 'Num1',
SUM(CASE WHEN AttendanceTypeID = 2 THEN 1 ELSE 0 END) 'Num2'
FROM tblAttendance
WHERE AttendanceDate BETWEEN #StartDate AND #EndDate
AND AttendanceTypeID IN (1,2)
AND AttendanceCodeID = 1
GROUP BY EmployeeID,AttendanceDate)
--Find the number of pairs and group by week
SELECT EmployeeID,
DATEPART(wk,AttendanceDate)'Week', --Get Week
--Getting the lowest of the 2 numbers, because that will
--be the number of pairs, then summing for the week
SUM(CASE WHEN Num1 > Num2 THEN Num2 ELSE Num1 END) 'Num1and2Pairs'
FROM daily1And2
GROUP BY EmployeeID,DATEPART(wk,AttendanceDate)
ORDER BY EmployeeID,DATEPART(wk,AttendanceDate)
Output:
+------------+------+---------------+
| EmployeeID | Week | Num1and2Pairs |
+------------+------+---------------+
| 114 | 9 | 0 |
| 206 | 9 | 1 |
| 206 | 10 | 1 |
| 206 | 11 | 0 |
| 260 | 9 | 1 |
| 260 | 10 | 2 |
| 260 | 11 | 0 |
| 295 | 11 | 1 |
| 344 | 9 | 1 |
| 348 | 9 | 1 |
| 348 | 10 | 4 |
| 348 | 11 | 1 |
| 350 | 9 | 2 |
| 350 | 10 | 4 |
| 350 | 11 | 2 |
| 359 | 9 | 0 |
| 359 | 10 | 4 |
| 359 | 11 | 2 |
| 361 | 9 | 10 |
+------------+------+---------------+

count null values and group results

Problem
i want to count null values and group the results but it gives me wrong values
String jpql = "select c.commande.user.login, (select count(*)
from Designation c
WHERE c.commande.commandeTms IS NOT EMPTY
AND c.etatComde = 0) AS count1,
(select count(*)
from Designation c WHERE c.commande.commandeTms IS EMPTY ) AS count2
from Designation c GROUP BY c.commande.user.login";
I have got these results :
user1 user2
10 10
0 0
But I should have these ones :
user1 user2
4 2
3 1
Sample data:
table Commande
idComdeComm, commandeTms_idComndeTms, user_idUser
6, 17 2
8, NULL 2
10, 28 2
12, NULL 2
14, NULL 2
16, NULL 2
21, NULL 19
23, NULL 19
25, 26 19
31 NULL 19
table designation
idDesignation, designation, etatComde, commande_idComdeComm
5, 'fef', 0, 6
7, 'ferf', 0, 8
9, 'hrhrh', 0, 10
11, 'ujujuju', 0, 12
13, 'kikolol', 0, 14
15, 'ololo', 0, 16
20, 'gdfgfd', 0, 21
22, 'gdfgfdd', 0, 23
24, 'nhfn', 0, 25
30, 'momo', 0, 31
table user
idUser, login, password, profil
1, 'moez', '***', 'admin'
2, 'user1', '**', 'comm'
3, 'log', '**', 'log'
4, 'mo', '*', 'comm'
19, 'user2', '*', 'comm'
table Commande TMS
idComndeTms, etatOperationNumCMD, numeroComndeTms
17, '', 3131
26, '', 2525
28, '', 3333