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问题:
I receive reports in which the data is ETL
to the DB automatically. I extract and transform some of that data to load it somewhere else. One thing I need to do is a DATEDIFF
but the year needs to be exact (i.e., 4.6 years instead of rounding up to five years.
The following is my script:
select *, DATEDIFF (yy, Begin_date, GETDATE()) AS 'Age in Years'
from Report_Stage;
The 'Age_In_Years'
column is being rounded. How do I get the exact date in years?
回答1:
Have you tried getting the difference in months instead and then calculating the years that way? For example 30 months / 12 would be 2.5 years.
Edit: This SQL query contains several approaches to calculate the date difference:
SELECT CONVERT(date, GetDate() - 912) AS calcDate
,DATEDIFF(DAY, GetDate() - 912, GetDate()) diffDays
,DATEDIFF(DAY, GetDate() - 912, GetDate()) / 365.0 diffDaysCalc
,DATEDIFF(MONTH, GetDate() - 912, GetDate()) diffMonths
,DATEDIFF(MONTH, GetDate() - 912, GetDate()) / 12.0 diffMonthsCalc
,DATEDIFF(YEAR, GetDate() - 912, GetDate()) diffYears
回答2:
All datediff()
does is compute the number of period boundaries crossed between to dates. For instance
datediff(yy,'31 Dec 2013','1 Jan 2014')
returns 1.
You'll get a more accurate result if you compute the difference between the two dates in days and divide by the mean length of a calendar year in days over a 400 year span (365.2425):
datediff(day,{start-date},{end-date},) / 365.2425
For instance,
select datediff(day,'1 Jan 2000' ,'18 April 2014') / 365.2425
return 14.29461248
— just round it to the desired precision.
回答3:
I think that division by 365.2425 is not a good way to do this. No division can to this completely accurately (using 365.25 also has issues).
I know the following script calculates an accurate date difference (though might not be the most speedy way):
declare @d1 datetime ,@d2 datetime
--set your dates eg:
select @d1 = '1901-03-02'
select @d2 = '2016-03-01'
select DATEDIFF(yy, @d1, @d2) -
CASE WHEN MONTH(@d2) < MONTH(@d1) THEN 1
WHEN MONTH(@d2) > MONTH(@d1) THEN 0
WHEN DAY(@d2) < DAY(@d1) THEN 1
ELSE 0 END
-- = 114 years
For comparison:
select datediff(day,@d1 ,@d2) / 365.2425
-- = 115 years => wrong!
You might be able to calculate small ranges with division, but why take a chance??
The following script can help to test yeardiff functions (just swap cast(datediff(day,@d1,@d2) / 365.2425 as int) to whatever the function is):
declare @d1 datetime set @d1 = '1900-01-01'
while(@d1 < '2016-01-01')
begin
declare @d2 datetime set @d2 = '2016-04-01'
while(@d2 >= '1900-01-01')
begin
if (@d1 <= @d2 and dateadd(YEAR, cast(datediff(day,@d1,@d2) / 365.2425 as int) , @d1) > @d2)
begin
select 'not a year!!', @d1, @d2, cast(datediff(day,@d1,@d2) / 365.2425 as int)
end
set @d2 = dateadd(day,-1,@d2)
end
set @d1 = dateadd(day,1,@d1)
end
回答4:
I have found a better solution. This makes the assumption that the first date is less than or equal to the second date.
declare @dateTable table (date1 datetime, date2 datetime)
insert into @dateTable
select '2017-12-31', '2018-01-02' union
select '2017-01-03', '2018-01-02' union
select '2017-01-02', '2018-01-02' union
select '2017-01-01', '2018-01-02' union
select '2016-12-01', '2018-01-02' union
select '2016-01-03', '2018-01-02' union
select '2016-01-02', '2018-01-02' union
select '2016-01-01', '2018-01-02'
select date1, date2,
case when ((DATEPART(year, date1) < DATEPART(year, date2)) and
((DATEPART(month, date1) <= DATEPART(month, date2)) and
(DATEPART(day, date1) <= DATEPART(day, date2)) ))
then DATEDIFF(year, date1, date2)
when (DATEPART(year, date1) < DATEPART(year, date2))
then DATEDIFF(year, date1, date2) - 1
when (DATEPART(year, date1) = DATEPART(year, date2))
then 0
end [YearsOfService]
from @dateTable
date1 date2 YearsOfService
----------------------- ----------------------- --------------
2016-01-01 00:00:00.000 2018-01-02 00:00:00.000 2
2016-01-02 00:00:00.000 2018-01-02 00:00:00.000 2
2016-01-03 00:00:00.000 2018-01-02 00:00:00.000 1
2016-12-01 00:00:00.000 2018-01-02 00:00:00.000 1
2017-01-01 00:00:00.000 2018-01-02 00:00:00.000 1
2017-01-02 00:00:00.000 2018-01-02 00:00:00.000 1
2017-01-03 00:00:00.000 2018-01-02 00:00:00.000 0
2017-12-31 00:00:00.000 2018-01-02 00:00:00.000 0