I'm looking to see if there is a way to get the total daily inventory for open items in the past few months. Basically, each record has a start date and an end date. The start date is always the same. The end date will be null until it has been processed. Once processed, it is updated with a process date. Getting one day is fine, but I need to get the total volume, everyday, for a the last few months.
My current method of doing this is putting the results in an aggregate table. I can run the results one time through a while loop, then each day run whatever open volume there is from a stored procedure. This method works, but seems messy.
DECLARE #D AS DATE = '04/01/2019'
WHILE #D <= CAST(GETDATE() AS DATE)
BEGIN
INSERT INTO DBO.OPEN_INVENTORY
SELECT
#D OPEN_DATE
,COUNT(1) OPEN_VOLUME
FROM
DBO.INVENTORY_RECORDS
WHERE
#D BETWEEN START_DATE AND ISNULL(END_DATE,'12/31/2199')
SET #D = DATEADD(D,+1,#D)
END
I would like to reproduce these results without having to store the volumes into an aggregate table. Is there a way to accomplish this in a single select?
Yes, the best way would be to use what's known as a "Tally Table". They are extremely quick are building large sets of sequential data, and unlike a WHILE, CURSOR or rCTE, aren't recursive.
This is a big of a stab in the dark, as I have no sample data, but I think this is what you're after.
DECLARE #D AS DATE = '20190104';
WITH N AS(
SELECT N
FROM (VALUES(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL)) N(N)),
Tally AS(
SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) -1 AS I
FROM N N1, N N2, N N3), --1000 rows should be enough?
Dates AS(
SELECT DATEADD(DAY, T.I, #D) AS CalendarDate
FROM Tally T
WHERE DATEADD(DAY, T.I, #D) <= GETDATE())
SELECT D.CalendarDate,
COUNT(IR.YourIDColumn) AS OPEN_VOLUMNE
FROM Dates D
LEFT JOIN DBO.INVENTORY_RECORDS IR ON D.Date >= IR.START_DATE
AND (D.Date <= IR.END_DATE OR IR.END_DATE IS NULL)
GROUP BY D.CalendarDate;
If not, try to troubleshoot it yourself, and then supply sample and expected results if not.
Related
I'm not sure if there should be a loop for this or what the easiest approach would be.
My data consists of a list of people participating in our program. They have various start and end dates, but the following equation is able to capture the number of people who participated on a specific date:
DECLARE #PopulationDate DATETIME = '2018-06-01 05:00:00';
select count(People)
FROM Program_Log
WHERE
START_TIME <= #PopulationDate
AND (END_TIME >= #PopulationDate OR END_TIME IS NULL)`
Is there a way I can loop in different date values to get the number of program participants each day for an entire year?
Multiple years?
One simple way is to use a CTE to generate the dates and then a left join to bring in the data. For instance, the following gets the counts as of the first of the month for this year:
with dates as (
select cast('2018-01-01' as date) as dte
union all
select dateadd(month, 1, dte)
from dates
where dte < getdate()
)
select d.dte, count(pl.people)
from dates d left join
program_log pl
on pl.start_time <= d.dte and (pl.end_time >= d.dte or pl.end_time is null)
group by d.dte
order by d.dte;
Note that this will work best for a handful of dates. If you want more than 100, you need to add option (maxrecursion 0) to the end of the query.
Also, count(people) is highly suspicious. Perhaps you mean sum(people) or something similar.
Between a date range 2017-02-01 - 2017-02-10, i'm calculating a running balance.
I have days where we have missing data, how would I include these missing dates with the previous days balance ?
Example data:
we are missing data for 2017-02-04,2017-02-05 and 2017-02-06, how would i add a row in the query with the previous balance?
The date range is a parameter, so could change....
Can i use something like the lag function?
I would be inclined to use a recursive CTE and then fill in the values. Here is one approach using outer apply:
with dates as (
select mind as dte, mind, maxd
from (select min(date) as mind, max(date) as maxd from t) t
union all
select dateadd(day, 1, dte), mind, maxd
from dates
where dte < maxd
)
select d.dte, t.balance
from dates d outer apply
(select top 1 t.*
from t
where t.date <= d.dte
order by t.date desc
) t;
You can generate dates using tally table as below:
Declare #d1 date ='2017-02-01'
Declare #d2 date ='2017-02-10'
;with cte_dates as (
Select top (datediff(D, #d1, #d2)+1) Dates = Dateadd(day, Row_Number() over (order by (Select NULL))-1, #d1) from
master..spt_values s1, master..spt_values s2
)
Select * from cte_dates left join ....
And do left join to your table and get running total
Adding to the date range & CTE solutions, I have created Date Dimension tables in numerous databases where I just left join to them.
There are free scripts online to create date dimension tables for SQL Server. I highly recommend them. Plus, it makes aggregation by other time periods much more efficient (e.g. Quarter, Months, Year, etc....)
I have a table in SQL server
And I want to generate each presentation day between StartDate and EndDate. Normally, I have to create a script, declare a cursor and loop through the cursor to create each individual date. But using cursor slows thing down considerably.
I wonder if anyone has a better idea using join
I am successful in generating date based on a startdate and enddate
SELECT d."CalendarDay" AS "PresenttionDate",
DATEPART(dw,d."CalendarDay") AS "PresentationDay"
FROM
(
SELECT StartDate-1+number AS "CalendarDay"
FROM master..spt_values
where type='P' and number<= DateDiff(day,StartDate,EndDate)
)d
I just do not know how to tie the StartDate and EndDate to the presentation table.
Basically, I am looking for the end results below:
without involving cursor. Is that possible?
Please advise.
I think this is sufficient:
with n as (
select row_number() over (order by (select null)) - 1 as n
from master..spt_values
)
select t.*, dateadd(day, n.n, t.startDate) as thedate
from t join
n
on dateadd(day, n.n, t.startDate) <= t.endDate;
I have a table with order information in an E-commerce store. Schema looks like this:
[Orders]
Id|SubTotal|TaxAmount|ShippingAmount|DateCreated
This table does only contain data for every Order. So if a day goes by without any orders, no sales data is there for that day.
I would like to select subtotal-per-day for the last 30 days, including those days with no sales.
The resultset would look like this:
Date | SalesSum
2009-08-01 | 15235
2009-08-02 | 0
2009-08-03 | 340
2009-08-04 | 0
...
Doing this, only gives me data for those days with orders:
select DateCreated as Date, sum(ordersubtotal) as SalesSum
from Orders
group by DateCreated
You could create a table called Dates, and select from that table and join the Orders table. But I really want to avoid that, because it doesn't work good enough when dealing with different time zones and things...
Please don't laugh. SQL is not my kind of thing... :)
Create a function that can generate a date table as follows:
(stolen from http://www.codeproject.com/KB/database/GenerateDateTable.aspx)
Create Function dbo.fnDateTable
(
#StartDate datetime,
#EndDate datetime,
#DayPart char(5) -- support 'day','month','year','hour', default 'day'
)
Returns #Result Table
(
[Date] datetime
)
As
Begin
Declare #CurrentDate datetime
Set #CurrentDate=#StartDate
While #CurrentDate<=#EndDate
Begin
Insert Into #Result Values (#CurrentDate)
Select #CurrentDate=
Case
When #DayPart='year' Then DateAdd(yy,1,#CurrentDate)
When #DayPart='month' Then DateAdd(mm,1,#CurrentDate)
When #DayPart='hour' Then DateAdd(hh,1,#CurrentDate)
Else
DateAdd(dd,1,#CurrentDate)
End
End
Return
End
Then, join against that table
SELECT dates.Date as Date, sum(SubTotal+TaxAmount+ShippingAmount)
FROM [fnDateTable] (dateadd("m",-1,CONVERT(VARCHAR(10),GETDATE(),111)),CONVERT(VARCHAR(10),GETDATE(),111),'day') dates
LEFT JOIN Orders
ON dates.Date = DateCreated
GROUP BY dates.Date
declare #oldest_date datetime
declare #daily_sum numeric(18,2)
declare #temp table(
sales_date datetime,
sales_sum numeric(18,2)
)
select #oldest_date = dateadd(day,-30,getdate())
while #oldest_date <= getdate()
begin
set #daily_sum = (select sum(SubTotal) from SalesTable where DateCreated = #oldest_date)
insert into #temp(sales_date, sales_sum) values(#oldest_date, #daily_sum)
set #oldest_date = dateadd(day,1,#oldest_date)
end
select * from #temp
OK - I missed that 'last 30 days' part. The bit above, while not as clean, IMHO, as the date table, should work. Another variant would be to use the while loop to fill a temp table just with the last 30 days and do a left outer join with the result of my original query.
including those days with no sales.
That's the difficult part. I don't think the first answer will help you with that. I did something similar to this with a separate date table.
You can find the directions on how to do so here:
Date Table
I have a Log table table with LogID an index which i never delete any records. it has index from 1 to ~10000000. Using this table I can write
select
s.ddate, SUM(isnull(o.SubTotal,0))
from
(
select
cast(datediff(d,LogID,getdate()) as datetime) AS ddate
from
Log
where
LogID <31
) s right join orders o on o.orderdate = s.ddate
group by s.ddate
I actually did this today. We also got a e-commerce application. I don't want to fill our database with "useless" dates. I just do the group by and create all the days for the last N days in Java, and peer them with the date/sales results from the database.
Where is this ultimately going to end up? I ask only because it may be easier to fill in the empty days with whatever program is going to deal with the data instead of trying to get it done in SQL.
SQL is a wonderful language, and it is capable of a great many things, but sometimes you're just better off working the finer points of the data in the program instead.
(Revised a bit--I hit enter too soon)
I started poking at this, and as it hits some pretty tricky SQL concepts it quickly grew into the following monster. If feasible, you might be better off adapting THEn's solution; or, like many others advise, using application code to fill in the gaps could be preferrable.
-- A temp table holding the 30 dates that you want to check
DECLARE #Foo Table (Date smalldatetime not null)
-- Populate the table using a common "tally table" methodology (I got this from SQL Server magazine long ago)
;WITH
L0 AS (SELECT 1 AS C UNION ALL SELECT 1), --2 rows
L1 AS (SELECT 1 AS C FROM L0 AS A, L0 AS B),--4 rows
L2 AS (SELECT 1 AS C FROM L1 AS A, L1 AS B),--16 rows
L3 AS (SELECT 1 AS C FROM L2 AS A, L2 AS B),--256 rows
Tally AS (SELECT ROW_NUMBER() OVER(ORDER BY C) AS Number FROM L3)
INSERT #Foo (Date)
select dateadd(dd, datediff(dd, 0, dateadd(dd, -number + 1, getdate())), 0)
from Tally
where Number < 31
Step 1 is to build a temp table containint the 30 dates that you are concerned with. That abstract wierdness is about the fastest way known to build a table of consecutive integers; add a few more subqueries, and you can populate millions or more in mere seconds. I take the first 30, and use dateadd and the current date/time to convert them into dates. If you already have a "fixed" table that has 1-30, you can use that and skip the CTE entirely (by replacing table "Tally" with your table).
The outer two date function calls remove the time portion of the generated string.
(Note that I assume that your order date also has no time portion -- otherwise you've got another common problem to resolve.)
For testing purposes I built table #Orders, and this gets you the rest:
SELECT f.Date, sum(ordersubtotal) as SalesSum
from #Foo f
left outer join #Orders o
on o.DateCreated = f.Date
group by f.Date
I created the Function DateTable as JamesMLV pointed out to me.
And then the SQL looks like this:
SELECT dates.date, ISNULL(SUM(ordersubtotal), 0) as Sales FROM [dbo].[DateTable] ('2009-08-01','2009-08-31','day') dates
LEFT JOIN Orders ON CONVERT(VARCHAR(10),Orders.datecreated, 111) = dates.date
group by dates.date
SELECT DateCreated,
SUM(SubTotal) AS SalesSum
FROM Orders
GROUP BY DateCreated
I feel like I've seen this question asked before, but neither the SO search nor google is helping me... maybe I just don't know how to phrase the question. I need to count the number of events (in this case, logins) per day over a given time span so that I can make a graph of website usage. The query I have so far is this:
select
count(userid) as numlogins,
count(distinct userid) as numusers,
convert(varchar, entryts, 101) as date
from
usagelog
group by
convert(varchar, entryts, 101)
This does most of what I need (I get a row per date as the output containing the total number of logins and the number of unique users on that date). The problem is that if no one logs in on a given date, there will not be a row in the dataset for that date. I want it to add in rows indicating zero logins for those dates. There are two approaches I can think of for solving this, and neither strikes me as very elegant.
Add a column to the result set that lists the number of days between the start of the period and the date of the current row. When I'm building my chart output, I'll keep track of this value and if the next row is not equal to the current row plus one, insert zeros into the chart for each of the missing days.
Create a "date" table that has all the dates in the period of interest and outer join against it. Sadly, the system I'm working on already has a table for this purpose that contains a row for every date far into the future... I don't like that, and I'd prefer to avoid using it, especially since that table is intended for another module of the system and would thus introduce a dependency on what I'm developing currently.
Any better solutions or hints at better search terms for google? Thanks.
Frankly, I'd do this programmatically when building the final output. You're essentially trying to read something from the database which is not there (data for days that have no data). SQL isn't really meant for that sort of thing.
If you really want to do that, though, a "date" table seems your best option. To make it a bit nicer, you could generate it on the fly, using i.e. your DB's date functions and a derived table.
I had to do exactly the same thing recently. This is how I did it in T-SQL (
YMMV on speed, but I've found it performant enough over a coupla million rows of event data):
DECLARE #DaysTable TABLE ( [Year] INT, [Day] INT )
DECLARE #StartDate DATETIME
SET #StartDate = whatever
WHILE (#StartDate <= GETDATE())
BEGIN
INSERT INTO #DaysTable ( [Year], [Day] )
SELECT DATEPART(YEAR, #StartDate), DATEPART(DAYOFYEAR, #StartDate)
SELECT #StartDate = DATEADD(DAY, 1, #StartDate)
END
-- This gives me a table of all days since whenever
-- you could select #StartDate as the minimum date of your usage log)
SELECT days.Year, days.Day, events.NumEvents
FROM #DaysTable AS days
LEFT JOIN (
SELECT
COUNT(*) AS NumEvents
DATEPART(YEAR, LogDate) AS [Year],
DATEPART(DAYOFYEAR, LogDate) AS [Day]
FROM LogData
GROUP BY
DATEPART(YEAR, LogDate),
DATEPART(DAYOFYEAR, LogDate)
) AS events ON days.Year = events.Year AND days.Day = events.Day
Create a memory table (a table variable) where you insert your date ranges, then outer join the logins table against it. Group by your start date, then you can perform your aggregations and calculations.
The strategy I normally use is to UNION with the opposite of the query, generally a query that retrieves data for rows that don't exist.
If I wanted to get the average mark for a course, but some courses weren't taken by any students, I'd need to UNION with those not taken by anyone to display a row for every class:
SELECT AVG(mark), course FROM `marks`
UNION
SELECT NULL, course FROM courses WHERE course NOT IN
(SELECT course FROM marks)
Your query will be more complex but the same principle should apply. You may indeed need a table of dates for your second query
Option 1
You can create a temp table and insert dates with the range and do a left outer join with the usagelog
Option 2
You can programmetically insert the missing dates while evaluating the result set to produce the final output
WITH q(n) AS
(
SELECT 0
UNION ALL
SELECT n + 1
FROM q
WHERE n < 99
),
qq(n) AS
(
SELECT 0
UNION ALL
SELECT n + 1
FROM q
WHERE n < 99
),
dates AS
(
SELECT q.n * 100 + qq.n AS ndate
FROM q, qq
)
SELECT COUNT(userid) as numlogins,
COUNT(DISTINCT userid) as numusers,
CAST('2000-01-01' + ndate AS DATETIME) as date
FROM dates
LEFT JOIN
usagelog
ON entryts >= CAST('2000-01-01' AS DATETIME) + ndate
AND entryts < CAST('2000-01-01' AS DATETIME) + ndate + 1
GROUP BY
ndate
This will select up to 10,000 dates constructed on the fly, that should be enough for 30 years.
SQL Server has a limitation of 100 recursions per CTE, that's why the inner queries can return up to 100 rows each.
If you need more than 10,000, just add a third CTE qqq(n) and cross-join with it in dates.