I am making a payroll system and I bought the B3 tft from zktechnology and would like to arrange the record.
Currently I can pull the data from the biometric with this format:
Count EmpID InOutMode Date
1 1 0 8/20/2012 07:49:01
2 1 1 8/20/2012 12:08:21
3 1 0 8/20/2012 12:43:10
4 1 1 8/20/2012 17:56:15
5 2 0 8/20/2012 07:53:11
6 2 1 8/20/2012 12:02:01
7 2 0 8/20/2012 12:39:56
8 2 1 8/20/2012 17:20:43
9 1 0 8/21/2012 08:10:20
10 1 1 8/21/2012 12:01:26
11 1 0 8/21/2012 13:03:11
12 1 1 8/21/2012 17:11:15
13 2 0 8/21/2012 07:48:26
14 2 1 8/21/2012 12:14:58
15 2 0 8/21/2012 12:59:31
16 2 1 8/21/2012 17:20:12
InOutMode:
0 = In, 1 = Out
Now, I want to convert the data above like this:
EmpID Date AM_In AM_Out PM_In PM_Out
1 8/20/2012 07:49:01 12:08:21 12:43:10 17:56:15
2 8/20/2012 07:53:11 12:02:01 12:39:56 17:20:43
1 8/21/2012 08:10:20 12:01:26 13:03:11 17:11:15
2 8/21/2012 07:48:26 12:14:58 12:59:31 17:20:12
So I can save it to the database with EmpID, Date, AM_In, AM_Out, PM_In, PM_Out fields.
I saw a similar code here before but I can't remember the URL.
Update:
VB.net code or sql in ms access format is acceptable.
It might be easiest to create two cross tabs and a query to join them to the available dates and employees.
1 AM Crosstab
TRANSFORM Min(tm.Date) AS MinOfDate
SELECT Format([Date],"dd/mm/yyyy") AS dt, tm.EmpID
FROM tm
GROUP BY Format([Date],"dd/mm/yyyy"), tm.EmpID
PIVOT tm.InOutMode;
2 PM Crosstab
TRANSFORM Max(tm.Date) AS MinOfDate
SELECT Format([Date],"dd/mm/yyyy") AS dt, tm.EmpID
FROM tm
GROUP BY Format([Date],"dd/mm/yyyy"), tm.EmpID
PIVOT tm.InOutMode;
Where tm is the name of your table.
You can then join these up.
SELECT Alldates.dt,
Alldates.empid,
am.[0] AS [Am In],
am.[1] AS [Am Out],
pm.[0] AS [Pm In],
pm.[1] AS [Pm Out]
FROM ((SELECT DISTINCT Format([date], "dd/mm/yyyy") AS dt,
empid
FROM tm) AS Alldates
LEFT JOIN am
ON ( Alldates.empid = am.empid )
AND ( Alldates.dt = am.dt ))
LEFT JOIN pm
ON ( Alldates.empid = pm.empid )
AND ( Alldates.dt = pm.dt );
Here is a query that should produce the results that you want in MS Access:
select am_in.empid,
format(am_in.min_in_dt, "MM/DD/YYYY") as [date],
format(am_in.min_in_dt, "hh:mm:ss") as AM_In,
format(am_out.min_out_dt, "hh:mm:ss") as AM_Out,
format(pm_in.max_in_dt, "hh:mm:ss") as PM_In,
format(pm_out.max_out_dt, "hh:mm:ss") as PM_Out
from
(
(
(
SELECT empid,
min(dt) as min_in_dt
FROM yourTable
where inoutmode = 0
group by empid
) am_in
inner join
(
SELECT empid,
min(dt) as min_out_dt
FROM yourTable
where inoutmode = 1
group by empid
) am_out
on am_in.empid = am_out.empid
)
inner join
(
SELECT empid,
max(dt) as max_in_dt
FROM yourTable
where inoutmode = 0
group by empid
) pm_in
on am_in.empid = pm_in.empid
)
inner join
(
SELECT empid,
max(dt) as max_out_dt
FROM yourTable
where inoutmode = 1
group by empid
) pm_out
on am_in.empid = pm_out.empid
Something like this will work
select
empid,
dateadd(day,datediff(day,0,DATE),0) as date,
max(case when sno=1 then convert(varchar(8),DATE,108)) as AM_IN,
max(case when sno=2 then convert(varchar(8),DATE,108)) as AM_OUT,
max(case when sno=3 then convert(varchar(8),DATE,108)) as PM_IN,
max(case when sno=4 then convert(varchar(8),DATE,108)) as PM_OUT
from
(
select *,
row_number() over (partition by empid order by Empid) as sno
from
table
) as t
group by
empid,dateadd(day,datediff(day,0,DATE),0)
Related
I have the following table in SQL Server. I would like to find the longest duration for the machine running.
Row
DateTime
Machine On
1
9/22/2022 8:20
1
2
9/22/2022 9:10
0
3
9/22/2022 10:40
1
4
9/22/2022 10:52
0
5
9/22/2022 12:30
1
6
9/22/2022 14:30
0
7
9/22/2022 15:00
1
8
9/22/2022 15:40
0
9
9/22/2022 16:25
1
10
9/22/2022 16:55
0
In the example above, the longest duration for the machine is ON is 2 hours using rows 5 and 6. What would be the best SQL statement that can provide the longest duration given a time range?
Desired Result:
60 minutes
I have looked into the LAG Function and the LEAD Function in SQL.
Here's another way that uses traditional gaps & islands methodology:
WITH src AS
(
SELECT Island, mint = MIN([Timestamp]), maxt = MAX([Timestamp])
FROM
(
SELECT [Timestamp], Island =
ROW_NUMBER() OVER (ORDER BY [Timestamp]) -
ROW_NUMBER() OVER (PARTITION BY Running ORDER BY [Timestamp])
FROM dbo.Machine_Status
) AS x GROUP BY Island
)
SELECT TOP (1) delta =
(DATEDIFF(second, mint, LEAD(mint,1) OVER (ORDER BY island)))
FROM src ORDER BY delta DESC;
Example db<>fiddle based on the sample data in your new duplicate.
If this is really your data, you can simply use INNER JOIN and DATEDIFF:
SELECT MAX(DATEDIFF(MINUTE, T1.[DateTime], T2.[DateTime]))
FROM [my_table] T1
INNER JOIN [my_table] T2
ON T1.[Row] + 1 = T2.[Row];
This is a gaps and islands problem, one option to solve it is to use a running sum that increased by 1 whenever a machine_on = 0, this will define unique groups for consecutive 1s followed by 0.
select top 1 datediff(minute, min([datetime]), max([datetime])) duration
from
(
select *,
sum(case when machine_on = 0 then 1 else 0 end) over (order by datetime desc) grp
from table_name
) T
group by grp
order by datediff(minute, min([datetime]), max([datetime])) desc
See demo
This is a classic Gaps and Islands with a little twist Adj
Example
Select Top 1
Row1 = min(row)
,Row2 = max(row)+1
,TS1 = min(TimeStamp)
,TS2 = dateadd(SECOND,max(Adj),max(TimeStamp))
,Dur = datediff(Second,min(TimeStamp),max(TimeStamp)) + max(Adj)
From (
Select *
,Grp = row_number() over( partition by Running order by TimeStamp) - row_number() over (order by timeStamp)
,Adj = case when Running=1 and lead(Running,1) over (order by timestamp) = 0 then datediff(second,TimeStamp,lead(TimeStamp,1) over (order by TimeStamp) ) else 0 end
From Machine_Status
) A
Where Running=1
Group By Grp
Order By Dur Desc
Results
Row1 Row2 TS1 TS2 Dur
8 12 2023-01-10 08:25:30.000 2023-01-10 08:28:55.000 205
I have an events table which contains the date of status changes. What I'm trying to achieve is to produce summary counts for each date, however I'm struggling as it is not a straight count by date but instead a count based on the last time the status changed.
The data is as follows:
------------------------------------------
IT_ID NEW_STATUS OLD_STATUS TIMESTAMP
------------------------------------------
100 4 3 06/05/2019
100 3 2 04/05/2019
200 2 1 03/05/2019
100 2 1 02/05/2019
300 2 1 02/05/2019
200 1 - 01/05/2019
100 1 - 01/05/2019
300 1 - 01/05/2019
-------------------------------------------
I've tried grouping, but this hasn't worked due to the above, SQL below for the straight count.
select max(trunc(timestamp)), new_status ,count(new_status)
from status_hist
where trunc(timestamp) >= '01/01/2019'
group by trunc(timestamp), new_status
Ideally I would like the data in the following format, however the key here is to counts against each date. Note, as no status changes took place on the 05/05/19 then it shows the same of the 04/05/19:
---------------------------------------------------------
Date Status 1 Status 2 Status 3 Status 4
---------------------------------------------------------
06/05/2019 0 2 0 1
05/05/2019 0 2 1 0
04/05/2019 0 2 1 0
03/05/2019 0 3 0 0
02/05/2019 1 2 0 0
01/05/2019 3 0 0 0
--------------------------------------------------------
Any help would be gratefully received.
Thanks
I think about handling this problem by getting the status of each person on each date. That requires a cross join to get the person/dates combinations and then some aggregation:
WITH dates as (
SELECT min_dt + LEVEL - 1 AS dt
FROM (SELECT MIN(ts) AS min_dt, MAX(ts) AS max_dt
FROM test_data
)
CONNECT BY min_dt + LEVEL - 1 <= max_dt
)
SELECT d.dt, i.it_id, max(td.new_status) keep (dense_rank first order by td.ts desc) as status
FROM dates d CROSS JOIN
(SELECT DISTINCT IT_ID FROM test_data) i LEFT JOIN
test_data td
ON td.IT_ID = i.IT_ID AND td.ts <= d.dt
GROUP BY d.dt, i.it_id;
The dates CTE is just calculating all dates. The rest is bringing in the latest status.
This can then be expanded to aggregate (or pivot) the results:
WITH dates as (
SELECT min_dt + LEVEL - 1 AS dt
FROM (SELECT MIN(ts) AS min_dt, MAX(ts) AS max_dt
FROM test_data
)
CONNECT BY min_dt + LEVEL - 1 <= max_dt
),
di as (
SELECT d.dt, i.it_id, max(td.new_status) keep (dense_rank first order by td.ts desc) as status
FROM dates d CROSS JOIN
(SELECT DISTINCT IT_ID FROM test_data) i LEFT JOIN
test_data td
ON td.IT_ID = i.IT_ID AND td.ts <= d.dt
GROUP BY d.dt, i.it_id
)
select dt,
sum(case when status = 1 then 1 else 0 end) as num_1,
sum(case when status = 2 then 1 else 0 end) as num_2,
sum(case when status = 3 then 1 else 0 end) as num_3,
sum(case when status = 4 then 1 else 0 end) as num_4
from di
group by dt
order by dt desc;
Here is a db<>fiddle.
You can do it using windowed aggregation functions:
Oracle Setup:
CREATE TABLE test_data ( IT_ID, NEW_STATUS, OLD_STATUS, "TIMESTAMP" ) AS
SELECT 100, 4, 3, DATE '2019-05-06' FROM DUAL UNION ALL
SELECT 100, 3, 2, DATE '2019-05-04' FROM DUAL UNION ALL
SELECT 200, 2, 1, DATE '2019-05-03' FROM DUAL UNION ALL
SELECT 100, 2, 1, DATE '2019-05-02' FROM DUAL UNION ALL
SELECT 300, 2, 1, DATE '2019-05-02' FROM DUAL UNION ALL
SELECT 200, 1, NULL, DATE '2019-05-01' FROM DUAL UNION ALL
SELECT 100, 1, NULL, DATE '2019-05-01' FROM DUAL UNION ALL
SELECT 300, 1, NULL, DATE '2019-05-01' FROM DUAL;
Query:
SELECT DISTINCT
dt AS "TIMESTAMP",
COUNT( CASE new_status WHEN 1 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
- COUNT( CASE old_status WHEN 1 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
AS Status1,
COUNT( CASE new_status WHEN 2 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
- COUNT( CASE old_status WHEN 2 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
AS Status2,
COUNT( CASE new_status WHEN 3 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
- COUNT( CASE old_status WHEN 3 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
AS Status3,
COUNT( CASE new_status WHEN 4 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
- COUNT( CASE old_status WHEN 4 THEN IT_ID END ) OVER ( ORDER BY dt RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW )
AS Status4
FROM test_data t
RIGHT OUTER JOIN (
SELECT min_dt + LEVEL - 1 AS dt
FROM ( SELECT MIN("TIMESTAMP") AS min_dt,
MAX("TIMESTAMP") AS max_dt
FROM test_data
)
CONNECT BY min_dt + LEVEL - 1 <= max_dt
) c
ON ( c.dt = t."TIMESTAMP" )
ORDER BY "TIMESTAMP" DESC
Output:
TIMESTAMP | STATUS1 | STATUS2 | STATUS3 | STATUS4
:-------- | ------: | ------: | ------: | ------:
06-MAY-19 | 0 | 2 | 0 | 1
05-MAY-19 | 0 | 2 | 1 | 0
04-MAY-19 | 0 | 2 | 1 | 0
03-MAY-19 | 0 | 3 | 0 | 0
02-MAY-19 | 1 | 2 | 0 | 0
01-MAY-19 | 3 | 0 | 0 | 0
db<>fiddle here
You can use the pivot function of SQL.
I don't have an oracle DB to test this:
declare #dates table(Date timestamp(3), NEW_STATUS number(10))
v_StartDate DATE := (SELECT MIN(timestamp) FROM [test].dbo)
v_EndDate DATE := (SELECT MAX(timestamp) FROM [test].dbo)
insert into #dates
SELECT nbr * INTERVAL '1' DAY(5) - 1 + v_StartDate as 'Date', null as NEW_STATUS
FROM ( SELECT ROW_NUMBER() OVER ( ORDER BY c.object_id ) AS Nbr
FROM sys.columns c
) nbrs
WHERE nbr - 1 <= v_EndDate - v_StartDate
SELECT timestamp as 'Date', 1 AS 'Status 1', 2 AS 'Status 2', 3 AS 'Status 3', 4 AS 'Status 4'
FROM
(SELECT Date as 'timestamp', NVL(NVL(d.new_status, t.NEW_STATUS),t2.NEW_STATUS) as new_status
FROM #dates d
left outer join Table_test t on d.Date = t.TIMESTAMP
left outer join Table_test t2 on INTERVAL '-1' DAY(5) +d.Date = t2.TIMESTAMP and NVL(d.new_status, t.NEW_STATUS) is null ) p
PIVOT
(
COUNT (new_status)
FOR new_status IN
( 1, 2, 3, 4 )
) AS pvt
ORDER BY pvt.TIMESTAMP desc
My Microsoft SQL Syntax is:
declare #dates table([Date] datetime, [NEW_STATUS] int)
DECLARE #StartDate DATE = (SELECT MIN(timestamp) FROM [test].[dbo].[Table_test])
DECLARE #EndDate DATE = (SELECT MAX(timestamp) FROM [test].[dbo].[Table_test])
insert into #dates
SELECT DATEADD(DAY, nbr - 1, #StartDate) as 'Date', null as NEW_STATUS
FROM ( SELECT ROW_NUMBER() OVER ( ORDER BY c.object_id ) AS Nbr
FROM sys.columns c
) nbrs
WHERE nbr - 1 <= DATEDIFF(DAY, #StartDate, #EndDate)
SELECT timestamp as 'Date', [1] AS 'Status 1', [2] AS 'Status 2', [3] AS 'Status 3', [4] AS 'Status 4'
FROM
(SELECT Date as 'timestamp', ISNULL(ISNULL(d.new_status, t.NEW_STATUS),t2.NEW_STATUS) as new_status
FROM #dates d
left outer join Table_test t on d.Date = t.TIMESTAMP
left outer join Table_test t2 on DATEADD(DAY,-1,d.Date) = t2.TIMESTAMP and ISNULL(d.new_status, t.NEW_STATUS) is null ) p
PIVOT
(
COUNT (new_status)
FOR new_status IN
( [1], [2], [3], [4] )
) AS pvt
ORDER BY pvt.TIMESTAMP desc
I need to create a report and I am struggling with the SQL script.
The table I want to query is a company_status_history table which has entries like the following (the ones that I can't figure out)
Table company_status_history
Columns:
| id | company_id | status_id | effective_date |
Data:
| 1 | 10 | 1 | 2016-12-30 00:00:00.000 |
| 2 | 10 | 5 | 2017-02-04 00:00:00.000 |
| 3 | 11 | 5 | 2017-06-05 00:00:00.000 |
| 4 | 11 | 1 | 2018-04-30 00:00:00.000 |
I want to answer to the question "Get all companies that have been at least for some point in status 1 inside the time period 01/01/2017 - 31/12/2017"
Above are the cases that I don't know how to handle since I need to add some logic of type :
"If this row is status 1 and it's date is before the date range check the next row if it has a date inside the date range."
"If this row is status 1 and it's date is after the date range check the row before if it has a date inside the date range."
I think this can be handled as a gaps and islands problem. Consider the following input data: (same as sample data of OP plus two additional rows)
id company_id status_id effective_date
-------------------------------------------
1 10 1 2016-12-15
2 10 1 2016-12-30
3 10 5 2017-02-04
4 10 4 2017-02-08
5 11 5 2017-06-05
6 11 1 2018-04-30
You can use the following query:
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
ORDER BY company_id, effective_date
to get:
id company_id status_id effective_date grp
-----------------------------------------------
1 10 1 2016-12-15 0
2 10 1 2016-12-30 1
3 10 5 2017-02-04 2
4 10 4 2017-02-08 2
5 11 5 2017-06-05 0
6 11 1 2018-04-30 0
Now you can identify status = 1 islands using:
;WITH CTE AS
(
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
)
SELECT id, company_id, status_id, effective_date,
ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) -
cnt AS grp
FROM CTE
Output:
id company_id status_id effective_date grp
-----------------------------------------------
1 10 1 2016-12-15 1
2 10 1 2016-12-30 1
3 10 5 2017-02-04 1
4 10 4 2017-02-08 2
5 11 5 2017-06-05 1
6 11 1 2018-04-30 2
Calculated field grp will help us identify those islands:
;WITH CTE AS
(
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
), CTE2 AS
(
SELECT id, company_id, status_id, effective_date,
ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) -
cnt AS grp
FROM CTE
)
SELECT company_id,
MIN(effective_date) AS start_date,
CASE
WHEN COUNT(*) > 1 THEN DATEADD(DAY, -1, MAX(effective_date))
ELSE MIN(effective_date)
END AS end_date
FROM CTE2
GROUP BY company_id, grp
HAVING COUNT(CASE WHEN status_id = 1 THEN 1 END) > 0
Output:
company_id start_date end_date
-----------------------------------
10 2016-12-15 2017-02-03
11 2018-04-30 2018-04-30
All you want know is those records from above that overlap with the specified interval.
Demo here with somewhat more complicated use case.
Maybe this is what you are looking for? For these kind of questions, you need to join two instance of your table, in this case I am just joining with next record by Id, which probably is not totally correct. To do it better, you can create a new Id using a windowed function like row_number, ordering the table by your requirement criteria
If this row is status 1 and it's date is before the date range check
the next row if it has a date inside the date range
declare #range_st date = '2017-01-01'
declare #range_en date = '2017-12-31'
select
case
when csh1.status_id=1 and csh1.effective_date<#range_st
then
case
when csh2.effective_date between #range_st and #range_en then true
else false
end
else NULL
end
from company_status_history csh1
left join company_status_history csh2
on csh1.id=csh2.id+1
Implementing second criteria:
"If this row is status 1 and it's date is after the date range check
the row before if it has a date inside the date range."
declare #range_st date = '2017-01-01'
declare #range_en date = '2017-12-31'
select
case
when csh1.status_id=1 and csh1.effective_date<#range_st
then
case
when csh2.effective_date between #range_st and #range_en then true
else false
end
when csh1.status_id=1 and csh1.effective_date>#range_en
then
case
when csh3.effective_date between #range_st and #range_en then true
else false
end
else null -- ¿?
end
from company_status_history csh1
left join company_status_history csh2
on csh1.id=csh2.id+1
left join company_status_history csh3
on csh1.id=csh3.id-1
I would suggest the use of a cte and the window functions ROW_NUMBER. With this you can find the desired records. An example:
DECLARE #t TABLE(
id INT
,company_id INT
,status_id INT
,effective_date DATETIME
)
INSERT INTO #t VALUES
(1, 10, 1, '2016-12-30 00:00:00.000')
,(2, 10, 5, '2017-02-04 00:00:00.000')
,(3, 11, 5, '2017-06-05 00:00:00.000')
,(4, 11, 1, '2018-04-30 00:00:00.000')
DECLARE #StartDate DATETIME = '2017-01-01';
DECLARE #EndDate DATETIME = '2017-12-31';
WITH cte AS(
SELECT *
,ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) AS rn
FROM #t
),
cteLeadLag AS(
SELECT c.*, ISNULL(c2.effective_date, c.effective_date) LagEffective, ISNULL(c3.effective_date, c.effective_date)LeadEffective
FROM cte c
LEFT JOIN cte c2 ON c2.company_id = c.company_id AND c2.rn = c.rn-1
LEFT JOIN cte c3 ON c3.company_id = c.company_id AND c3.rn = c.rn+1
)
SELECT 'Included' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date BETWEEN #StartDate AND #EndDate
UNION ALL
SELECT 'Following' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date > #EndDate
AND LagEffective BETWEEN #StartDate AND #EndDate
UNION ALL
SELECT 'Trailing' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date < #EndDate
AND LeadEffective BETWEEN #StartDate AND #EndDate
I first select all records with their leading and lagging Dates and then I perform your checks on the inclusion in the desired timespan.
Try with this, self-explanatory. Responds to this part of your question:
I want to answer to the question "Get all companies that have been at
least for some point in status 1 inside the time period 01/01/2017 -
31/12/2017"
Case that you want to find those id's that have been in any moment in status 1 and have records in the period requested:
SELECT *
FROM company_status_history
WHERE id IN
( SELECT Id
FROM company_status_history
WHERE status_id=1 )
AND effective_date BETWEEN '2017-01-01' AND '2017-12-31'
Case that you want to find id's in status 1 and inside the period:
SELECT *
FROM company_status_history
WHERE status_id=1
AND effective_date BETWEEN '2017-01-01' AND '2017-12-31'
I’m looking to join two tables that do not have a common data point, but common value (date). I want a table that lists the date and total number of hired/terminated employees on that day. Example is below:
Table 1
Hire Date Employee Number Employee Name
--------------------------------------------
5/5/2018 10078 Joe
5/5/2018 10077 Adam
5/5/2018 10078 Steve
5/8/2018 10079 Jane
5/8/2018 10080 Mary
Table 2
Termination Date Employee Number Employee Name
----------------------------------------------------
5/5/2018 10010 Tony
5/6/2018 10025 Jonathan
5/6/2018 10035 Mark
5/8/2018 10052 Chris
5/9/2018 10037 Sam
Desired result:
Date Total Hired Total Terminated
--------------------------------------
5/5/2018 3 1
5/6/2018 0 2
5/7/2018 0 0
5/8/2018 2 1
5/9/2018 0 1
Getting the total count is easy, just unsure as the best approach from the standpoint of "adding" a date column
If you need all dates within some window then you need to join the data to a calendar. You can then left join and sum flags for data points.
DECLARE #StartDate DATETIME = (SELECT MIN(ActionDate) FROM(SELECT ActionDate = MIN(HireDate) FROM Table1 UNION SELECT ActionDate = MIN(TerminationDate) FROM Table2)AS X)
DECLARE #EndDate DATETIME = (SELECT MAX(ActionDate) FROM(SELECT ActionDate = MAX(HireDate) FROM Table1 UNION SELECT ActionDate = MAX(TerminationDate) FROM Table2)AS X)
;WITH AllDates AS
(
SELECT CalendarDate=#StartDate
UNION ALL
SELECT DATEADD(DAY, 1, CalendarDate)
FROM AllDates
WHERE DATEADD(DAY, 1, CalendarDate) <= #EndDate
)
SELECT
CalendarDate,
TotalHired = SUM(CASE WHEN H.HireDate IS NULL THEN NULL ELSE 1 END),
TotalTerminated = SUM(CASE WHEN T.TerminationDate IS NULL THEN NULL ELSE 1 END)
FROM
AllDates D
LEFT OUTER JOIN Table1 H ON H.HireDate = D.CalendarDate
LEFT OUTER JOIN Table2 T ON T.TerminationDate = D.CalendarDate
/* If you only want dates with data points then uncomment out the where clause
WHERE
NOT (H.HireDate IS NULL AND T.TerminationDate IS NULL)
*/
GROUP BY
CalendarDate
I would do this with a union all and aggregations:
select dte, sum(is_hired) as num_hired, sum(is_termed) as num_termed
from (select hiredate as dte, 1 as is_hired, 0 as is_termed from table1
union all
select terminationdate, 0 as is_hired, 1 as is_termed from table2
) ht
group by dte
order by dte;
This does not include the "missing" dates. If you want those, a calendar or recursive CTE works. For instance:
with ht as (
select dte, sum(is_hired) as num_hired, sum(is_termed) as num_termed
from (select hiredate as dte, 1 as is_hired, 0 as is_termed from table1
union all
select terminationdate, 0 as is_hired, 1 as is_termed from table2
) ht
group by dte
),
d as (
select min(dte) as dte, max(dte) as max_dte)
from ht
union all
select dateadd(day, 1, dte), max_dte
from d
where dte < max_dte
)
select d.dte, coalesce(ht.num_hired, 0) as num_hired, coalesce(ht.num_termed) as num_termed
from d left join
ht
on d.dte = ht.dte
order by dte;
Try this one
SELECT ISNULL(a.THE_DATE, b.THE_DATE) as Date,
ISNULL(a.Total_Hire,0) as Total_Hire,
ISNULL (b.Total_Terminate,0) as Total_terminate
FROM (SELECT Hire_date as the_date, COUNT(1) as Total_Hire
FROM TABLE_HIRE GROUP BY HIRE_DATE) a
FULL OUTER JOIN (SELECT Termination_Date as the_date, COUNT(1) as Total_Terminate
FROM TABLE_TERMINATE GROUP BY HIRE_DATE) a
ON a.the_date = b.the_date
Let say I have this kind of data:
Date Category Amount
01/10/2014 20:04 2 12212
01/11/2014 0:00 3 11043.38
01/11/2014 16:03 2 12082
01/11/2014 16:32 3 110.43
01/12/2014 20:41 2 12196
01/12/2014 20:42 3 103.22
31/12/2014 14:20 2 12440
31/12/2014 14:21 3 104.25
I wish to get below result:
Date Category Amount
01/10/2014 20:04 2 12212
01/11/2014 16:03 2 12082
01/11/2014 16:32 3 110.43
01/12/2014 20:41 2 12196
01/12/2014 20:42 3 103.22
So far, I am able to make this query:
select t.date, t.Category, t.Amount
from mytable t
inner join (
select Category,MONTH(date) MONTHH,YEAR(date) YEARR, max(date) as MaxDate
from mytable
group by Category,MONTH(date) MONTHH,YEAR(date) YEARR
) tm on t.date = tm.MaxDate and t.Category = tm.Category
But it returns a wrong result if there is more than 1 date in 1 month. This is the result:
Date Category Amount
01/10/2014 20:04 2 12212
01/11/2014 16:03 2 12082
01/11/2014 16:32 3 110.43
31/12/2014 14:20 2 12440
31/12/2014 14:21 3 104.25
Could anyone help please? thanks
Use row_number() and rank():
select t.*
from (select t.*,
dense_rank() over (partition by year(date), month(date) order by day(date)) as seqnum,
row_number() over (partition by year(date), month(date), day(date) order by date desc) as seqnum_d
from mytable t
) t
where seqnum = 1 and seqnum_d = 1;
Try This
;WITH CTE
AS
(
SELECT
RN = ROW_NUMBER() OVER(PARTITION BY MONTH([Date]),YEAR([Date]),Category ORDER BY [Date]),
*
FROM YourTable
)
SELECT
Date,
Category,
Amount
FROM CTE
WHERE RN = 1
Do not use reserved words as columns (i.e. Date).
No need to group, you are not using any summation/averaging:
select *
from tda t
where not exists(
-- not exists: same date, later time, cat is same
select 1
from tda b
where 1 = 1
and cast(t.dDate as date) = cast(b.dDate as date)
and t.ddate > b.ddate
and t.cat = b.cat
)
and not exists(
-- not exists: same month, earlier date
select 1
from tda b
where month(b.ddate) = month(t.ddate)
and day(b.ddate)<day(t.ddate)
)
to get (reformat the date to your liking):
ddate Cat Amount
2014-10-01T20:04:00Z 2 12212
2014-11-01T00:00:00Z 3 11043.38
2014-11-01T16:03:00Z 2 12082
2014-12-01T20:41:00Z 2 12196
2014-12-01T20:42:00Z 3 103.22
by
CREATE TABLE tda ([ddate] datetime,[Cat] int, [Amount] numeric(10,2));
INSERT INTO tda (dDate, Cat, Amount)
VALUES
('2014/10/01 20:04', 2, 12212),
('2014/11/01 0:00', 3, 11043.38),
('2014/11/01 16:03', 2, 12082),
('2014/11/01 16:32', 3, 110.43),
('2014/12/01 20:41', 2, 12196),
('2014/12/01 20:42', 3, 103.22),
('2014/12/31 14:20', 2, 12440),
('2014/12/31 14:21', 3, 104.25)
;