I have a SQL database that collects temperature and sensor data from the barn.
The table definition is:
CREATE TABLE [dbo].[DataPoints]
(
[timestamp] [datetime] NOT NULL,
[pointname] [nvarchar](50) NOT NULL,
[pointvalue] [float] NOT NULL
)
The sensors report outside temperature (degrees), inside temperature (degrees), and heating (as on/off).
Sensors create a record when the previous reading has changed, so temperatures are generated every few minutes, one record for heat coming ON, one for heat going OFF, and so on.
I'm interested in how many minutes of heat has been used overnight, so a 24-hour period from 6 AM yesterday to 6 AM today would work fine.
This query:
SELECT *
FROM [home_network].[dbo].[DataPoints]
WHERE (pointname = 'Heaters')
AND (timestamp BETWEEN '2022-12-18 06:00:00' AND '2022-12-19 06:00:00')
ORDER BY timestamp
returns this data:
2022-12-19 02:00:20 | Heaters | 1
2022-12-19 02:22:22 | Heaters | 0
2022-12-19 03:43:28 | Heaters | 1
2022-12-19 04:25:31 | Heaters | 0
The end result should be 22 minutes + 42 minutes = 64 minutes of heat, but I can't see how to get this result from a single query. It also just happens that this result set has two complete heat on/off cycles, but that will not always be the case. So, if the first heat record was = 0, that means that at 6 AM, the heat was already on, but the start time won't show in the query. The same idea applies if the last heat record is =1 at, say 05:15, which means 45 minutes have to be added to the total.
Is it possible to get this minutes-of-heat-time result with a single query? Actually, I don't know the right approach, and it doesn't matter if I have to run several queries. If needed, I could use a small app that reads the raw data, and applies logic outside of SQL to arrive at the total. But I'd prefer to be able to do this within SQL.
This isn't a complete answer, but it should help you get started. From the SQL in the post, I'm assuming you're using SQL Server. I've formatted the code to match. Replace #input with your query above if you want to test on your own data. (SELECT * FROM [home_network].[dbo]...)
--generate dummy table with sample output from question
declare #input as table(
[timestamp] [datetime] NOT NULL,
[pointname] [nvarchar](50) NOT NULL,
[pointvalue] [float] NOT NULL
)
insert into #input values
('2022-12-19 02:00:20','Heaters',1),
('2022-12-19 02:22:22','Heaters',0),
('2022-12-19 03:43:28','Heaters',1),
('2022-12-19 04:25:31','Heaters',0);
--Append a row number to the result
WITH A as (
SELECT *,
ROW_NUMBER() OVER(ORDER BY(SELECT 1)) as row_count
from #input)
--Self join the table using the row number as a guide
SELECT sum(datediff(MINUTE,startTimes.timestamp,endTimes.timestamp))
from A as startTimes
LEFT JOIN A as endTimes on startTimes.row_count=endTimes.row_count-1
--Only show periods of time where the heater is turned on at the start
WHERE startTimes.row_count%2=1
Your problem can be divided into 2 steps:
Filter sensor type and date range, while also getting time span of each record by calculating date difference between timestamp of current record and the next one in chronological order.
Filter records with ON status and summarize the duration
(Optional) convert to HH:MM:SS format to display
Here's the my take on the problem with comments of what I do in each step, all combined into 1 single query.
-- Step 3: Convert output to HH:MM:SS, this is just for show and can be reduced
SELECT STUFF(CONVERT(VARCHAR(8), DATEADD(SECOND, total_duration, 0), 108),
1, 2, CAST(FLOOR(total_duration / 3600) AS VARCHAR(5)))
FROM (
-- Step 2: select records with status ON (1) and aggregate total duration in seconds
SELECT sum(duration) as total_duration
FROM (
-- Step 1: Use LEAD to get next adjacent timestamp and calculate date difference (time span) between the current record and the next one in time order
SELECT TOP 100 PERCENT
DATEDIFF(SECOND, timestamp, LEAD(timestamp, 1, '2022-12-19 06:00:00') OVER (ORDER BY timestamp)) as duration,
pointvalue
FROM [dbo].[DataPoints]
-- filtered by sensor name and time range
WHERE pointname = 'Heaters'
AND (timestamp BETWEEN '2022-12-18 06:00:00' AND '2022-12-19 06:00:00')
ORDER BY timestamp ASC
) AS tmp
WHERE tmp.pointvalue = 1
) as tmp2
Note: As the last record does not have next adjacent timestamp, it will be filled with the end time of inspection (In this case it's 6AM of the next day).
I do not really think it would be possible to achieve within single query.
Option 1:
implement stored procedure where you can implement some logic how to calculate these periods.
Option 2:
add new column (duration) and on insert new record calculate difference between NOW and previous timestamp and update duration for previous record
Hei guys, I'm trying to help my friend to design database tables. It is for a system tracking workers' working hours in a factory by reading card info from certain card readers. Each time a worker log his in/out information, there would be an record saved.
My problem is, how can I calculate each worker's working time (in minutes), each workday? A worker may work from 8:00AM~20:00PM, or 20:00PM~8:00AM.
Anyone can help me?
Thanks!
You guys did give me a lot of help.
The previous design is a table with in-record or out-record. It was hard for me to locate which ones belong to the same work-time-span. I now use another table with records both have the in-time and out-time in the same record. Insert to save in-time, update to save out-time, which makes it easy to calculate the total minutes between in-time and out-time.
SELECT datediff(hh,'2011-08-30 04:47','2011-08-30 05:48') as [Hour(s) Worked]
Hour(s) Worked
--------------
1
a simple example with 2 tables
[TblUsers]
User_id PK
FirstName
LastName
[TblSchedule]
Schedule_id PK
User_id FK
Date_From
Date_To
to get a daily work grid with times, you can write something like:
SELECT
u.FirstName + ' ' + u.LastName as [username],
CAST(FLOOR(CAST(#datetime as float)) as datetime) as [date],
DATEDIFF(minute, s.Date_To, s.Date_From) as [workMinutes]
FROM
[TblSchedule] s, [TblUsers] u
WHERE
s.user_id = u.user_id
GROUP BY
u.FirstName + ' ' + u.LastName,
CAST(FLOOR(CAST(#datetime as float)) as datetime)
ORDER BY
s.Date_From;
Just calculate the Minutes between each IN-Record and the following OUT-Record from this worker. If you want it for a whole day then fetch the relevant records and sum up the relevant differences.
The more complex thing here is when some worker forget about stamping. Your program have to be prepared for such cases.
Also be aware of things like daylight saving time. Time-Calcs can be very complicated.
I think I would do calculation on application level and not in SQL in this case.
DATEDIFF can give you some strange results.
For example take this two DATETIME2 (I presume you have SQL Server 2008) values that have a difference of 5 minutes:
SELECT DATEDIFF(hh,'2011-01-01 04:59:00','2011-01-01 05:04:00')
Results
-----------
1
The result is somehow strange: 1 hour. Strange, because the difference in minutes is 5 minutes but the difference in hours is 1 hour and we know that 1 hour = 60 minutse. Please read this article to see the explanations.
Solutions:
1) Instead of DATEDIFF(hh,...) use DATEDIFF(mi,...)
Ex:
SELECT DATEDIFF(mi,'2011-01-01 07:55:00','2011-01-01 16:02:00') [Minutes]
,DATEDIFF(mi,'2011-01-01 07:55:00','2011-01-01 16:02:00')/60 [Hours]
--8 hours
,DATEDIFF(mi,'2011-01-01 07:55:00','2011-01-01 16:02:00')%60 [Additional minute]
--7 minute
But:
SELECT DATEDIFF(mi,'2011-01-01 08:00:59','2011-01-01 16:00:05') [Minutes]
--480
,DATEDIFF(ss,'2011-01-01 08:00:59','2011-01-01 16:00:05')/60 [Seconds/60]
--479
2) Instead of using DATEDIFF function (with DATETIME[2][OFFSET] data types) use DATETIME values with the - operator:
DECLARE #Test TABLE
(
TestId INT IDENTITY(1,1) PRIMARY KEY
,[Enter] DATETIME NOT NULL
,[Exit] DATETIME NOT NULL
);
INSERT #Test
VALUES ('2011-01-01 07:55:00','2011-01-01 16:02:02')
,('2011-01-01 08:00:59','2011-01-01 16:00:05');
SELECT *
,t.[Exit] - t.[Enter] AS MyDateDiff
,DATEPART(hh,t.[Exit] - t.[Enter]) [Hours]
,DATEPART(mi,t.[Exit] - t.[Enter]) [Additional minutes]
,DATEPART(ss,t.[Exit] - t.[Enter]) [Additional seconds]
FROM #Test t
Results:
TestId Enter Exit MyDateDiff Hours Additional minute Additional seconds
----------- ----------------------- ----------------------- ----------------------- ----------- ----------------- ------------------
1 2011-01-01 07:55:00.000 2011-01-01 16:02:02.000 1900-01-01 08:07:02.000 8 7 2
2 2011-01-01 08:00:59.000 2011-01-01 16:00:05.000 1900-01-01 07:59:06.000 7 59 6
The root problem: I have an application which has been running for several months now. Users have been reporting that it's been slowing down over time (so in May it was quicker than it is now). I need to get some evidence to support or refute this claim. I'm not interested in precise numbers (so I don't need to know that a login took 10 seconds), I'm interested in trends - that something which used to take x seconds now takes of the order of y seconds.
The data I have is an audit table which stores a single row each time the user carries out any activity - it includes a primary key, the user id, a date time stamp and an activity code:
create table AuditData (
AuditRecordID int identity(1,1) not null,
DateTimeStamp datetime not null,
DateOnly datetime null,
UserID nvarchar(10) not null,
ActivityCode int not null)
(Notes: DateOnly (datetime) is the DateTimeStamp with the time stripped off to make group by for daily analysis easier - it's effectively duplicate data to make querying faster).
Also for the sake of ease you can assume that the ID is assigned in date time order, that is 1 will always be before 2 which will always be before 3 - if this isn't true I can make it so).
ActivityCode is an integer identifying the activity which took place, for instance 1 might be user logged in, 2 might be user data returned, 3 might be search results returned and so on.
Sample data for those who like that sort of thing...:
1, 01/01/2009 12:39, 01/01/2009, P123, 1
2, 01/01/2009 12:40, 01/01/2009, P123, 2
3, 01/01/2009 12:47, 01/01/2009, P123, 3
4, 01/01/2009 13:01, 01/01/2009, P123, 3
User data is returned (Activity Code 2) immediate after login (Activity Code 1) so this can be used as a rough benchmark of how long the login takes (as I said, I'm interested in trends so as long as I'm measuring the same thing for May as July it doesn't matter so much if this isn't the whole login process - it takes in enough of it to give a rough idea).
(Note: User data can also be returned under other circumstances so it's not a one to one mapping).
So what I'm looking to do is select the average time between login (say ActivityID 1) and the first instance after that for that user on that day of user data being returned (say ActivityID 2).
I can do this by going through the table with a cursor, getting each login instance and then for that doing a select to say get the minimum user data return following it for that user on that day but that's obviously not optimal and is slow as hell.
My question is (finally) - is there a "proper" SQL way of doing this using self joins or similar without using cursors or some similar procedural approach? I can create views and whatever to my hearts content, it doesn't have to be a single select.
I can hack something together but I'd like to make the analysis I'm doing a standard product function so would like it to be right.
SELECT TheDay, AVG(TimeTaken) AvgTimeTaken
FROM (
SELECT
CONVERT(DATE, logins.DateTimeStamp) TheDay
, DATEDIFF(SS, logins.DateTimeStamp,
(SELECT TOP 1 DateTimeStamp
FROM AuditData userinfo
WHERE UserID=logins.UserID
and userinfo.ActivityCode=2
and userinfo.DateTimeStamp > logins.DateTimeStamp )
)TimeTaken
FROM AuditData logins
WHERE
logins.ActivityCode = 1
) LogInTimes
GROUP BY TheDay
This might be dead slow in real world though.
In Oracle this would be a cinch, because of analytic functions. In this case, LAG() makes it easy to find the matching pairs of activity codes 1 and 2 and also to calculate the trend. As you can see, things got worse on 2nd JAN and improved quite a bit on the 3rd (I'm working in seconds rather than minutes).
SQL> select DateOnly
2 , elapsed_time
3 , elapsed_time - lag (elapsed_time) over (order by DateOnly) as trend
4 from
5 (
6 select DateOnly
7 , avg(databack_time - prior_login_time) as elapsed_time
8 from
9 ( select DateOnly
10 , databack_time
11 , ActivityCode
12 , lag(login_time) over (order by DateOnly,UserID, AuditRecordID, ActivityCode) as prior_login_time
13 from
14 (
15 select a1.AuditRecordID
16 , a1.DateOnly
17 , a1.UserID
18 , a1.ActivityCode
19 , to_number(to_char(a1.DateTimeStamp, 'SSSSS')) as login_time
20 , 0 as databack_time
21 from AuditData a1
22 where a1.ActivityCode = 1
23 union all
24 select a2.AuditRecordID
25 , a2.DateOnly
26 , a2.UserID
27 , a2.ActivityCode
28 , 0 as login_time
29 , to_number(to_char(a2.DateTimeStamp, 'SSSSS')) as databack_time
30 from AuditData a2
31 where a2.ActivityCode = 2
32 )
33 )
34 where ActivityCode = 2
35 group by DateOnly
36 )
37 /
DATEONLY ELAPSED_TIME TREND
--------- ------------ ----------
01-JAN-09 120
02-JAN-09 600 480
03-JAN-09 150 -450
SQL>
Like I said in my comment I guess you're working in MSSQL. I don't know whether that product has any equivalent of LAG().
If the assumptions are that:
Users will perform various tasks in no mandated order, and
That the difference between any two activities reflects the time it takes for the first of those two activities to execute,
Then why not create a table with two timestamps, the first column containing the activity start time, the second column containing the next activity start time. Thus the difference between these two will always be total time of the first activity. So for the logout activity, you would just have NULL for the second column.
So it would be kind of weird and interesting, for each activity (other than logging in and logging out), the time stamp would be recorded in two different rows--once for the last activity (as the time "completed") and again in a new row (as time started). You would end up with a jacob's ladder of sorts, but finding the data you are after would be much more simple.
In fact, to get really wacky, you could have each row have the time that the user started activity A and the activity code, and the time started activity B and the time stamp (which, as mentioned above, gets put down again for the following row). This way each row will tell you the exact difference in time for any two activities.
Otherwise, you're stuck with a query that says something like
SELECT TIME_IN_SEC(row2-timestamp) - TIME_IN_SEC(row1-timestamp)
which would be pretty slow, as you have already suggested. By swallowing the redundancy, you end up just querying the difference between the two columns. You probably would have less need of knowing the user info as well, since you'd know that any row shows both activity codes, thus you can just query the average for all users on any given day and compare it to the next day (unless you are trying to find out which users are having the problem as well).
This is the faster query to find out, in one row you will have current and row before datetime value, after that you can use DATEDIFF ( datepart , startdate , enddate ). I use #DammyVariable and DamyField as i remember the is some problem if is not first #variable=Field in update statement.
SELECT *, Cast(NULL AS DateTime) LastRowDateTime, Cast(NULL As INT) DamyField INTO #T FROM AuditData
GO
CREATE CLUSTERED INDEX IX_T ON #T (AuditRecordID)
GO
DECLARE #LastRowDateTime DateTime
DECLARE #DammyVariable INT
SET #LastRowDateTime = NULL
SET #DammyVariable = 1
UPDATE #T SET
#DammyVariable = DammyField = #DammyVariable
, LastRowDateTime = #LastRowDateTime
, #LastRowDateTime = DateTimeStamp
option (maxdop 1)
For a call-rating system, I'm trying to split a telephone call duration into sub-durations for different tariff-periods. The calls are stored in a SQL Server database and have a starttime and total duration. Rates are different for night (0000 - 0800), peak (0800 - 1900) and offpeak (1900-235959) periods.
For example:
A call starts at 18:50:00 and has a duration of 1000 seconds. This would make the call end at 19:06:40, making it 10 minutes / 600 seconds in the peak-tariff and 400 seconds in the off-peak tariff.
Obviously, a call can wrap over an unlimited number of periods (we do not enforce a maximum call duration). A call lasting > 24 h can wrap all 3 periods, starting in peak, going through off-peak, night and back into peak tariff.
Currently, we are calculating the different tariff-periods using recursion in VB. We calculate how much of the call goes in the same tariff-period the call starts in, change the starttime and duration of the call accordingly and repeat this process till the full duration of the call has been reach (peakDuration + offpeakDuration + nightDuration == callDuration).
Regarding this issue, I have 2 questions:
Is it possible to do this effectively in a SQL Server statement? (I can think of subqueries or lots of coding in stored procedures, but that would not generate any performance improvement)
Will SQL Server be able to do such calculations in a way more resource-effective than the current VB scripts are doing it?
It seems to me that this is an operation with two phases.
Determine which parts of the phone call use which rates at which time.
Sum the times in each of the rates.
Phase 1 is trickier than Phase 2. I've worked the example in IBM Informix Dynamic Server (IDS) because I don't have MS SQL Server. The ideas should translate easily enough. The INTO TEMP clause creates a temporary table with an appropriate schema; the table is private to the session and vanishes when the session ends (or you explicitly drop it). In IDS, you can also use an explicit CREATE TEMP TABLE statement and then INSERT INTO temp-table SELECT ... as a more verbose way of doing the same job as INTO TEMP.
As so often in SQL questions on SO, you've not provided us with a schema, so everyone has to invent a schema that might, or might not, match what you describe.
Let's assume your data is in two tables. The first table has the call log records, the basic information about the calls made, such as the phone making the call, the number called, the time when the call started and the duration of the call:
CREATE TABLE clr -- call log record
(
phone_id VARCHAR(24) NOT NULL, -- billing plan
called_number VARCHAR(24) NOT NULL, -- needed to validate call
start_time TIMESTAMP NOT NULL, -- date and time when call started
duration INTEGER NOT NULL -- duration of call in seconds
CHECK(duration > 0),
PRIMARY KEY(phone_id, start_time)
-- other complicated range-based constraints omitted!
-- foreign keys omitted
-- there would probably be an auto-generated number here too.
);
INSERT INTO clr(phone_id, called_number, start_time, duration)
VALUES('650-656-3180', '650-794-3714', '2009-02-26 15:17:19', 186234);
For convenience (mainly to save writing the addition multiple times), I want a copy of the clr table with the actual end time:
SELECT phone_id, called_number, start_time AS call_start, duration,
start_time + duration UNITS SECOND AS call_end
FROM clr
INTO TEMP clr_end;
The tariff data is stored in a simple table:
CREATE TABLE tariff
(
tariff_code CHAR(1) NOT NULL -- code for the tariff
CHECK(tariff_code IN ('P','N','O'))
PRIMARY KEY,
rate_start TIME NOT NULL, -- time when rate starts
rate_end TIME NOT NULL, -- time when rate ends
rate_charged DECIMAL(7,4) NOT NULL -- rate charged (cents per second)
);
INSERT INTO tariff(tariff_code, rate_start, rate_end, rate_charged)
VALUES('N', '00:00:00', '08:00:00', 0.9876);
INSERT INTO tariff(tariff_code, rate_start, rate_end, rate_charged)
VALUES('P', '08:00:00', '19:00:00', 2.3456);
INSERT INTO tariff(tariff_code, rate_start, rate_end, rate_charged)
VALUES('O', '19:00:00', '23:59:59', 1.2345);
I debated whether the tariff table should use TIME or INTERVAL values; in this context, the times are very similar to intervals relative to midnight, but intervals can be added to timestamps where times cannot. I stuck with TIME, but it made things messy.
The tricky part of this query is generating the relevant date and time ranges for each tariff without loops. In fact, I ended up using a loop embedded in a stored procedure to generate a list of integers. (I also used a technique that is specific to IBM Informix Dynamic Server, IDS, using the table ID numbers from the system catalog as a source of contiguous integers in the range 1..N, which works for numbers from 1 to 60 in version 11.50.)
CREATE PROCEDURE integers(lo INTEGER DEFAULT 0, hi INTEGER DEFAULT 0)
RETURNING INT AS number;
DEFINE i INTEGER;
FOR i = lo TO hi STEP 1
RETURN i WITH RESUME;
END FOR;
END PROCEDURE;
In the simple case (and the most common case), the call falls in a single-tariff period; the multi-period calls add the excitement.
Let's assume we can create a table expression that matches this schema and covers all the timestamp values we might need:
CREATE TEMP TABLE tariff_date_time
(
tariff_code CHAR(1) NOT NULL,
rate_start TIMESTAMP NOT NULL,
rate_end TIMESTAMP NOT NULL,
rate_charged DECIMAL(7,4) NOT NULL
);
Fortunately, you haven't mentioned weekend rates, so you charge the customers the same
rates at the weekend as during the week. However, the answer should adapt to such
situations if at all possible. If you were to get as complex as giving weekend rates on
public holidays, except that at Christmas or New Year, you charge peak rate instead of
weekend rate because of the high demand, then you would be best off storing the rates in a permanent tariff_date_time table.
The first step in populating tariff_date_time is to generate a list of dates which are relevant to the calls:
SELECT DISTINCT EXTEND(DATE(call_start) + number, YEAR TO SECOND) AS call_date
FROM clr_end,
TABLE(integers(0, (SELECT DATE(call_end) - DATE(call_start) FROM clr_end)))
AS date_list(number)
INTO TEMP call_dates;
The difference between the two date values is an integer number of days (in IDS).
The procedure integers generates values from 0 to the number of days covered by the call and stores the result in a temp table. For the more general case of multiple records, it might be better to calculate the minimum and maximum dates and generate the dates in between rather than generate dates multiple times and then eliminate them with the DISTINCT clause.
Now use a cartesian product of the tariff table with the call_dates table to generate the rate information for each day. This is where the tariff times would be neater as intervals.
SELECT r.tariff_code,
d.call_date + (r.rate_start - TIME '00:00:00') AS rate_start,
d.call_date + (r.rate_end - TIME '00:00:00') AS rate_end,
r.rate_charged
FROM call_dates AS d, tariff AS r
INTO TEMP tariff_date_time;
Now we need to match the call log record with the tariffs that apply. The condition is a standard way of dealing with overlaps - two time periods overlap if the end of the first is later than the start of the second and if the start of the first is before the end of the second:
SELECT tdt.*, clr_end.*
FROM tariff_date_time tdt, clr_end
WHERE tdt.rate_end > clr_end.call_start
AND tdt.rate_start < clr_end.call_end
INTO TEMP call_time_tariff;
Then we need to establish the start and end times for the rate. The start time for the rate is the later of the start time for the tariff and the start time of the call. The end time for the rate is the earlier of the end time for the tariff and the end time of the call:
SELECT phone_id, called_number, tariff_code, rate_charged,
call_start, duration,
CASE WHEN rate_start < call_start THEN call_start
ELSE rate_start END AS rate_start,
CASE WHEN rate_end >= call_end THEN call_end
ELSE rate_end END AS rate_end
FROM call_time_tariff
INTO TEMP call_time_tariff_times;
Finally, we need to sum the times spent at each tariff rate, and take that time (in seconds) and multiply by the rate charged. Since the result of SUM(rate_end - rate_start) is an INTERVAL, not a number, I had to invoke a conversion function to convert the INTERVAL into a DECIMAL number of seconds, and that (non-standard) function is iv_seconds:
SELECT phone_id, called_number, tariff_code, rate_charged,
call_start, duration,
SUM(rate_end - rate_start) AS tariff_time,
rate_charged * iv_seconds(SUM(rate_end - rate_start)) AS tariff_cost
FROM call_time_tariff_times
GROUP BY phone_id, called_number, tariff_code, rate_charged,
call_start, duration;
For the sample data, this yielded the data (where I'm not printing the phone number and called number for compactness):
N 0.9876 2009-02-26 15:17:19 186234 0 16:00:00 56885.760000000
O 1.2345 2009-02-26 15:17:19 186234 0 10:01:11 44529.649500000
P 2.3456 2009-02-26 15:17:19 186234 1 01:42:41 217111.081600000
That's a very expensive call, but the telco will be happy with that. You can poke at any of the intermediate results to see how the answer is derived. You can use fewer temporary tables at the cost of some clarity.
For a single call, this will not be much different than running the code in VB in the client. For a lot of calls, this has the potential to be more efficient. I'm far from convinced that recursion is necessary in VB - straight iteration should be sufficient.
kar_vasile(id,vid,datein,timein,timeout,bikari,tozihat)
{
--- the bikari field is unemployment time you can delete any where
select
id,
vid,
datein,
timein,
timeout,
bikari,
hourwork =
case when
timein <= timeout
then
SUM
(abs(DATEDIFF(mi, timein, timeout)) - bikari)/60 --
calculate Hour
else
SUM(abs(DATEDIFF(mi, timein, '23:59:00:00') + DATEDIFF(mi, '00:00:00', timeout) + 1) - bikari)/60 --
calculate
minute
end
,
minwork =
case when
timein <= timeout
then
SUM
(abs(DATEDIFF(MI, timein, timeout)) - bikari)%60 --
calclate Hour
starttime is later
than endtime
else
SUM(abs(DATEDIFF(mi, timein, '23:59:00:00') + DATEDIFF(mi, '00:00:00', timeout) + 1) - bikari)%60--
calculate minute
starttime is later
than
endtime
end, tozihat
from kar_vasile
group
by id, vid, datein, timein, timeout, tozihat, bikari
}
Effectively in T-SQL? I suspect not, with the schema as described at present.
It might be possible, however, if your rate table stores the three tariffs for each date. There is at least one reason why you might do this, apart from the problem at hand: it's likely at some point that rates for one period or another might change and you may need to have the historic rates available.
So say we have these tables:
CREATE TABLE rates (
from_date_time DATETIME
, to_date_time DATETIME
, rate MONEY
)
CREATE TABLE calls (
id INT
, started DATETIME
, ended DATETIME
)
I think there are three cases to consider (may be more, I'm making this up as I go):
a call occurs entirely within one
rate period
a call starts in one
rate period (a) and ends in the next (b)
a call spans at least one complete
rate period
Assuming rate is per second, I think you might produce something like the following (completely untested) query
SELECT id, DATEDIFF(ss, started, ended) * rate /* case 1 */
FROM rates JOIN calls ON started > from_date_time AND ended < to_date_time
UNION
SELECT id, DATEDIFF(ss, started, to_date_time) * rate /* case 2a and the start of case 3 */
FROM rates JOIN calls ON started > from_date_time AND ended > to_date_time
UNION
SELECT id, DATEDIFF(ss, from_date_time, ended) * rate /* case 2b and the last part of case 3 */
FROM rates JOIN calls ON started < from_date_time AND ended < to_date_time
UNION
SELECT id, DATEDIFF(ss, from_date_time, to_date_time) * rate /* case 3 for entire rate periods, should pick up all complete periods */
FROM rates JOIN calls ON started < from_date_time AND ended > to_date_time
You could apply a SUM..GROUP BY over that in SQL or handle it in your code. Alternatively, with carefully-constructed logic, you could probably merge the UNIONed parts into a single WHERE clause with lots of ANDs and ORs. I thought the UNION showed the intent rather more clearly.
HTH & HIW (Hope It Works...)
This is a thread about your problem we had over at sqlteam.com. take a look because it includes some pretty slick solutions.
Following on from Mike Woodhouse's answer, this may work for you:
SELECT id, SUM(DATEDIFF(ss, started, ended) * rate)
FROM rates
JOIN calls ON
CASE WHEN started < from_date_time
THEN DATEADD(ss, 1, from_date_time)
ELSE started > from_date_time
AND
CASE WHEN ended > to_date_time
THEN DATEADD(ss, -1, to_date_time)
ELSE ended END
< ended
GROUP BY id
An actual schema for the relevant tables in your database would have been very helpful. I'll take my best guesses. I've assumed that the Rates table has start_time and end_time as the number of minutes past midnight.
Using a calendar table (a VERY useful table to have in most databases):
SELECT
C.id,
R.rate,
SUM(DATEDIFF(ss,
CASE
WHEN C.start_time < R.rate_start_time THEN R.rate_start_time
ELSE C.start_time
END,
CASE
WHEN C.end_time > R.rate_end_time THEN R.rate_end_time
ELSE C.end_time
END)) AS
FROM
Calls C
INNER JOIN
(
SELECT
DATEADD(mi, Rates.start_time, CAL.calendar_date) AS rate_start_time,
DATEADD(mi, Rates.end_time, CAL.calendar_date) AS rate_end_time,
Rates.rate
FROM
Calendar CAL
INNER JOIN Rates ON
1 = 1
WHERE
CAL.calendar_date >= DATEADD(dy, -1, C.start_time) AND
CAL.calendar_date <= C.start_time
) AS R ON
R.rate_start_time < C.end_time AND
R.rate_end_time > C.start_time
GROUP BY
C.id,
R.rate
I just came up with this as I was typing, so it's untested and you will very likely need to tweak it, but hopefully you can see the general idea.
I also just realized that you use a start_time and a duration for your calls. You can just replace C.end_time wherever you see it with DATEADD(ss, C.start_time, C.duration) assuming that the duration is in seconds.
This should perform pretty quickly in any decent RDBMS assuming proper indexes, etc.
Provided that you calls last less than 100 days:
WITH generate_range(item) AS
(
SELECT 0
UNION ALL
SELECT item + 1
FROM generate_range
WHERE item < 100
)
SELECT tday, id, span
FROM (
SELECT tday, id,
DATEDIFF(minute,
CASE WHEN tbegin < clbegin THEN clbegin ELSE tbegin END,
CASE WHEN tend < clend THEN tend ELSE clend END
) AS span
FROM (
SELECT DATEADD(day, item, DATEDIFF(day, 0, clbegin)) AS tday,
ti.id,
DATEADD(minute, rangestart, DATEADD(day, item, DATEDIFF(day, 0, clbegin))) AS tbegin,
DATEADD(minute, rangeend, DATEADD(day, item, DATEDIFF(day, 0, clbegin))) AS tend
FROM calls, generate_range, tariff ti
WHERE DATEADD(day, 1, DATEDIFF(day, 0, clend)) > DATEADD(day, item, DATEDIFF(day, 0, clbegin))
) t1
) t2
WHERE span > 0
I'm assuming you keep your tariffs ranges in minutes from midnight and count lengths in minutes too.
The big problem with performing this kind of calculation at the database level is that it takes resource away from your database while it's going on, both in terms of CPU and availability of rows and tables via locking. If you were calculating 1,000,000 tariffs as part of a batch operation, then that might run on the database for a long time and during that time you'd be unable to use the database for anything else.
If you have the resource, retrieve all the data you need with one transaction and do all the logic calculations outside the database, in a language of your choice. Then insert all the results. Databases are for storing and retrieving data, and any business logic they perform should be kept to an absolute bare minimum at all times. Whilst brilliant at some things, SQL isn't the best language for date or string manipulation work.
I suspect you're already on the right lines with your VBA work, and without knowing more it certainly feels like a recursive, or at least an iterative, problem to me. When done correctly recursion can be a powerful and elegant solution to a problem. Tying up the resources of your database very rarely is.