I added my dates with the query so you can so what dates im running. From these dates im trying to exclude 2 days 10/6/2016 and 10/7/2016
DECLARE #Startdate AS DATETIME
DECLARE #EndDate AS DATETIME
SET #Startdate = '10/1/2015'
SET #EndDate = '9/30/2016
SELECT A.agent_name, COUNT(*) AS CH, (CAST(SUM(reporting_call_matrix.talk_time) / COUNT(reporting_call_matrix.answer_time) AS float)
+ CAST(SUM(reporting_call_matrix.hold_time) AS float) / COUNT(reporting_call_matrix.answer_time)) +
CAST(SUM(reporting_call_matrix.work_time) AS float) / COUNT(reporting_call_matrix.answer_time) AS AHT,
answer_agent_id
FROM reporting_call_matrix INNER JOIN
reporting_agents AS A ON reporting_call_matrix.answer_agent_id = A.agent_id INNER JOIN
reporting_split_info ON reporting_call_matrix.split = reporting_split_info.split
WHERE (reporting_call_matrix.answer_agent_id IS NOT NULL) AND (reporting_call_matrix.split IN (9,23)) AND
(reporting_call_matrix.queued_time >= #StartDate) AND (reporting_call_matrix.queued_time < DATEADD(d, 1, #EndDate)) AND
(reporting_call_matrix.answer_time IS NOT NULL) AND
GROUP BY A.agent_name,answer_agent_id
No idea what you are actually trying to do here but I cleaned up this query so it is more legible. I also greatly simplified that nightmarish calculation. You don't have to cast everything to a float, just simply multiple it by 1.0. Also, float is probably not a great choice if you want accuracy because it is an approximate datatype where 1.0 will be numeric which is an exact datatype.
With some aliases and formatting this is so much easier to read.
SELECT A.agent_name
, COUNT(*) AS CH
, (SUM(rcm.talk_time) + SUM(rcm.hold_time) / COUNT(rcm.answer_time) * 1.0) + (SUM(rcm.work_time) / COUNT(rcm.answer_time) * 1.0) AS AHT
, answer_agent_id
FROM reporting_call_matrix rcm
INNER JOIN reporting_agents AS A ON rcm.answer_agent_id = A.agent_id
INNER JOIN reporting_split_info rsi ON rcm.split = rsi.split
WHERE rcm.answer_agent_id IS NOT NULL
AND rcm.split IN (9,23)
AND rcm.queued_time >= #StartDate
AND rcm.queued_time < DATEADD(day, 1, #EndDate)
AND rcm.answer_time IS NOT NULL
GROUP BY A.agent_name
, rcm.answer_agent_id
Now, what is the actual question here?
With your recent update I will hazard a guess that queued_time is a date datatype?
Why not simply add one more predicate to your where clause?
AND rcm.queued_time not in ('2016-10-06', '2016-10-07')
Related
This question already has answers here:
Left Outer Join Not Working?
(4 answers)
Closed 10 months ago.
I have a property rental site
So I want to know if property is available for a range of dates
First of all I defined the range of dates as:
DECLARE #AvailableRentalStartingDate DATETIME = '2022-04-11'
, #AvailableRentalEndingDate DATETIME = '2022-04-24'
Now the property rent like:
DECLARE #Rentals AS TABLE
(
[PropertyId] UNIQUEIDENTIFIER,
[StartingDate] DATE,
[EndingDate] DATE
)
INSERT INTO #Rentals ([PropertyId], [StartingDate], [EndingDate])
VALUES ('A5B2B505-EC6F-EC11-A004-00155E014807','2022-04-11 16:47:20.897', '2022-04-14 16:47:20.897'),
('A5B2B505-EC6F-EC11-A004-00155E014807','2022-04-16 16:47:20.897','2022-04-21 16:47:20.897')
As you can see we have available date 2022-04-15
Dates table
DECLARE #Dates AS TABLE
(
DateName DATE
)
DECLARE #TotalDays INT = 365;
WHILE #TotalDays > 0
BEGIN
INSERT INTO #Dates ([DateName])
SELECT DATEADD(DAY, #TotalDays, '2021-12-31');
SELECT #TotalDays = #TotalDays - 1;
END
Then the select
SELECT [R].[PropertyId], [D].[DateName], CASE WHEN [R].[StartingDate] IS NULL THEN 1 ELSE 0 END AS [IsAvailable]
FROM #Dates AS D
LEFT JOIN #Rentals R ON [D].[DateName] >= [R].[StartingDate] AND [D].[DateName] <= [R].[EndingDate]
WHERE [D].[DateName] BETWEEN #AvailableRentalStartingDate AND #AvailableRentalEndingDate
AND [R].[PropertyId] = 'A5B2B505-EC6F-EC11-A004-00155E014807'
ORDER BY [D].[DateName]
The problem is it does not identify the null on the available date 2022-04-15, it just return the not available dates.
I just want to know if that propertyId it's available, in this case it should be available because 2022-04-15 is available. How can I get only one row showing available true? Regards
your problem is the where clause of propertyid;
you should have that as a JOIN condition.
WHERE clause and ON conditions can be interchangeably used in INNER JOIN but in OUTER JOIN they impact the meaning.
demo link
SELECT [R].[PropertyId], [D].[DateName], CASE WHEN [R].[StartingDate] IS NULL THEN 1 ELSE 0 END AS [IsAvailable]
FROM #Dates AS D
LEFT JOIN #Rentals R ON [D].[DateName] >= [R].[StartingDate] AND [D].[DateName] <= [R].[EndingDate]
AND [R].[PropertyId] = 'A5B2B505-EC6F-EC11-A004-00155E014807'
WHERE [D].[DateName] BETWEEN #AvailableRentalStartingDate AND #AvailableRentalEndingDate
ORDER BY [D].[DateName]
Trying to convert the SQL with while loop code into DAX. Trying to build this query without using temp tables as access is an issue on the database and only have views to work with. I believe best option for me is to code it in DAX. Could someone help with it.
DECLARE #sd DATETIME
DECLARE #ed DATETIME
SELECT #sd = CONVERT(DATETIME, '2021-01-31')
SELECT #ed = GETDATE()
DECLARE #date DATETIME = EOMONTH(#sd)
WHILE ( (#date) <= #ed )
BEGIN
SELECT MONTH(#date) as Month, YEAR(#date) as Year, DAY(#date) as Day, A.*
FROM [people] A
WHERE A.effective_date = (SELECT MAX(B.effective_date)
FROM [people] B
WHERE B.employee_id = A.employee_id
AND B.record_id = A.record_id
AND B.effective_date <= #date)
AND A.effective_sequence = (SELECT MAX(C.effective_sequence)
FROM [people] C
WHERE C.employee_id = A.employee_id
AND C.record_id = A.record_id
AND C.effective_date = A.effective_date)
ORDER BY A.employee_id;
SET #date = EOMONTH(DATEADD(MONTH,1,#date))
END
While you could do this as a view, you would either have to hard-code the start and end dates, or filter them afterwards (which is likely to be inefficient). Instead you can do this as an inline Table Valued Function.
We can use a virtual tally-table (generated with a couple cross-joins) to generate a row for each month
We can use row-numbering instead of the two subqueries
CREATE FUNCTION dbo.GetData (#sd DATETIME, #ed DATETIME)
RETURNS TABLE AS RETURN
WITH L0 AS (
SELECT *
FROM (VALUES(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) v(n)
),
L1 AS (
SELECT 1 n FROM L0 a CROSS JOIN L0 b
)
SELECT
MONTH(m.Month) as Month,
YEAR(m.Month) as Year,
DAY(m.Month) as Day,
p.* -- specify columns
FROM (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY m.Month, p.employee_id, p.record_id ORDER BY p.effective_date, p.effective_sequence) AS rn
FROM [people] p
CROSS JOIN (
SELECT TOP (DATEDIFF(month, #sd, #ed) + 1)
DATEADD(month, ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) - 1, EOMONTH(#sd)) AS Month
FROM L1
) m
WHERE p.effective_date <= m.Month
) p
WHERE p.rn = 1
;
Then in PowerBI you can just do for example
SELECT *
FROM dbo.GetData ('2021-01-31', GETDATE()) d
ORDER BY
d.employee_id
Note that you cannot put the ORDER BY within the function, it doesn't work.
Im having a slight issue merging the following statements
declare #From DATE
SET #From = '01/01/2014'
declare #To DATE
SET #To = '31/01/2014'
--ISSUED SB
SELECT
COUNT(pm.DateAppIssued) AS Issued,
pm.Lender,
pm.AmountRequested,
p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE CaseTypeID = 2
AND (CONVERT(DATE,DateAppIssued, 103)
Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103))
And Lender > ''
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
--Paased
SELECT
COUNT(pm.DatePassed) AS Passed,
pm.Lender,
pm.AmountRequested,
p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE CaseTypeID = 2
AND (CONVERT(DATE,DatePassed, 103)
Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103))
And Lender > ''
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
--Received
SELECT
COUNT(pm.DateAppRcvd) AS Received,
pm.Lender,
pm.AmountRequested,
p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE CaseTypeID = 2
AND (CONVERT(DATE,DateAppRcvd, 103)
Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103))
And Lender > ''
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
--Offered
SELECT
COUNT(pm.DateOffered) AS Offered,
pm.Lender,
pm.AmountRequested,
p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE CaseTypeID = 2
AND (CONVERT(DATE,DateOffered, 103)
Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103))
And Lender > ''
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
Ideally I would like the result of theses query's to show as follows
Issued, Passed , Offered, Received,
All in one table
Any Help on this would be greatly appreciated
Thanks
Rusty
I'm fairly certain in this case the query can be written without the use of any CASE statements, actually:
DECLARE #From DATE = '20140101'
declare #To DATE = '20140201'
SELECT Mortgage.lender, Mortgage.amountRequested, Profile.caseTypeId,
COUNT(Issue.issued) as issued,
COUNT(Pass.passed) as passed,
COUNT(Receive.received) as received,
COUNT(Offer.offered) as offered
FROM BPS.dbo.tbl_Profile_Mortgage as Mortgage
JOIN BPS.dbo.tbl_Profile as Profile
ON Mortgage.fk_profileId = Profile.id
AND Profile.caseTypeId = 2
LEFT JOIN (VALUES (1, #From, #To)) Issue(issued, rangeFrom, rangeTo)
ON Mortgage.DateAppIssued >= Issue.rangeFrom
AND Mortgage.DateAppIssued < Issue.rangeTo
LEFT JOIN (VALUES (2, #From, #To)) Pass(passed, rangeFrom, rangeTo)
ON Mortgage.DatePassed >= Pass.rangeFrom
AND Mortgage.DatePassed < Pass.rangeTo
LEFT JOIN (VALUES (3, #From, #To)) Receive(received, rangeFrom, rangeTo)
ON Mortgage.DateAppRcvd >= Receive.rangeFrom
AND Mortgage.DateAppRcvd < Receive.rangeTo
LEFT JOIN (VALUES (4, #From, #To)) Offer(offered, rangeFrom, rangeTo)
ON Mortgage.DateOffered >= Offer.rangeFrom
AND Mortgage.DateOffered < Offer.rangeTo
WHERE Mortgage.lender > ''
AND (Issue.issued IS NOT NULL
OR Pass.passed IS NOT NULL
OR Receive.received IS NOT NULL
OR Offer.offered IS NOT NULL)
GROUP BY Mortgage.lender, Mortgage.amountRequested, Profile.caseTypeId
(not tested, as I lack a provided data set).
... Okay, some explanations are in order, because some of this is slightly non-intuitive.
First off, read this blog entry for tips about dealing with date/time/timestamp ranges (interestingly, this also applies to all other non-integral types). This is why I modified the #To date - so the range could be safely queried without needing to convert types (and thus ignore indices). I've also made sure to choose a safe format - depending on how you're calling this query, this is a non issue (ie, parameterized queries taking an actual Date type are essentially format-less).
......
COUNT(Issue.issued) as issued,
......
LEFT JOIN (VALUES (1, #From, #To)) Issue(issued, rangeFrom, rangeTo)
ON Mortgage.DateAppIssued >= Issue.rangeFrom
AND Mortgage.DateAppIssued < Issue.rangeTo
.......
What's the difference between COUNT(*) and COUNT(<expression>)? If <expression> evaluates to null, it's ignored. Hence the LEFT JOINs; if the entry for the mortgage isn't in the given date range for the column, the dummy table doesn't attach, and there's no column to count. Unfortunately, I'm not sure how the interplay between the dummy table, LEFT JOIN, and COUNT() here will appear to the optimizer - the joins should be able to use indices, but I don't know if it's smart enough to be able to use that for the COUNT() here too....
(Issue.issued IS NOT NULL
OR Pass.passed IS NOT NULL
OR Receive.received IS NOT NULL
OR Offer.offered IS NOT NULL)
This is essentially telling it to ignore rows that don't have at least one of the columns. They wouldn't be "counted" in any case (well, they'd likely have 0) - there's no data for the function to consider - but they would show up in the results, which probably isn't what you want. I'm not sure if the optimizer is smart enough to use this to restrict which rows it operates over - that is, turn the JOIN conditions into a way to restrict the various date columns, as if they were in the WHERE clause too. If the query runs slow, try adding the date restrictions to the WHERE clause and see if it helps.
You could either as Dan Bracuk states use a union, or you could use a case-statement.
declare #From DATE = '01/01/2014'
declare #To DATE = '31/01/2014'
select
sum(case when (CONVERT(DATE,DateAppIssued, 103) Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103)) then 1 else 0 end) as Issued
, sum(case when (CONVERT(DATE,DatePassed, 103) Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103)) then 1 else 0 end) as Passed
, sum(case when (CONVERT(DATE,DateAppRcvd, 103) Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103)) then 1 else 0 end) as Received
, sum(case when (CONVERT(DATE,DateOffered, 103) Between CONVERT(DATE,#From,103) and CONVERT(DATE,#To,103)) then 1 else 0 end) as Offered
, pm.Lender
, pm.AmountRequested
, p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE CaseTypeID = 2
And Lender > ''
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
Edit:
What I've done is looked at your queries.
All four queries have identical Where Clause, with the exception of the date comparison. Therefore I've created a new query, which selects all your data which might be used in one of the four counts.
The last clause; the data-comparison, is moved into a case statement, returning 1 if the row is between the selected date-range, and 0 otherwise. This basically indicates whether the row would be returned in your previous queries.
Therefore a sum of this column would return the equivalent of a count(*), with this date-comparison in the where-clause.
Edit 2 (After comments by Clockwork-muse):
Some notes on performance, (tested on MS-SQL 2012):
Changing BETWEEN to ">=" and "<" inside a case-statement does not affect the cost of the query.
Depending on the size of the table, the query might be optimized quite a lot, by adding the dates in the where clause.
In my sample data (~20.000.000 rows, spanning from 2001 to today), i got a 48% increase in speed by adding.
or (DateAppIssued BETWEEN #From and #to )
or (DatePassed BETWEEN #From and #to )
or (DateAppRcvd BETWEEN #From and #to )
or (DateOffered BETWEEN #From and #to )
(There were no difference using BETWEEN and ">=" and "<".)
It is also worth nothing that i got a 6% increase when changing the #From = '01/01/2014' to #From '2014-01-01' and thus omitting the convert().
Eg. an optimized query could be:
declare #From DATE = '2014-01-01'
declare #To DATE = '2014-01-31'
select
sum(case when (DateAppIssued >= #From and DateAppIssued < #To) then 1 else 0 end) as Issued
, sum(case when (DatePassed >= #From and DatePassed < #To) then 1 else 0 end) as Passed
, sum(case when (DateAppRcvd >= #From and DateAppRcvd < #To) then 1 else 0 end) as Received
, sum(case when (DateOffered >= #From and DateOffered < #To) then 1 else 0 end) as Offered
, pm.Lender
, pm.AmountRequested
, p.CaseTypeID
FROM BPS.dbo.tbl_Profile_Mortgage AS pm
INNER JOIN BPS.dbo.tbl_Profile AS p
ON pm.FK_ProfileId = p.Id
WHERE 1=1
and CaseTypeID = 2
and Lender > ''
and (
(DateAppIssued >= #From and DateAppIssued < #To)
or (DatePassed >= #From and DatePassed < #To)
or (DateAppRcvd >= #From and DateAppRcvd < #To)
or (DateOffered >= #From and DateOffered < #To)
)
GROUP BY pm.Lender,p.CaseTypeID,pm.AmountRequested;
I do however really like Clockwork-muse's answer, as I prefer joins to case-statements, where posible :)
The all-in-one queries here in other answers are certainly elegant, but if you are in a rush to get something working as a one-off, or if you agree the following approach is easy to read and maintain when you have to revisit it some time down the road (or someone else less skilled has to work out what's going on) - here's a skeleton of a Common Table Expression alternative which I believe is quite clear to read :
WITH Unioned_Four AS
( SELECT .. -- first select : Issued
UNION ALL
SELECT .. -- second : Passed
UNION ALL
SELECT .. -- Received
UNION ALL
SELECT .. -- Offered
)
SELECT
-- group fields
-- SUMs of the count fields
FROM Unioned_Four
GROUP BY .. -- etc
Obviously the fields have to match in the 4 parts of the UNION, requiring dummy fields returning zero in each one.
So you could have kept the simple approach that you started with, but wrapped it up as a derived table using the CTE syntax to allow you to have the four counts all on one row per GROUPing. Also if you have to add extra filtering to specific queries of the four, then it's easier to meddle with the individual SELECTs - the flipside being (of course) that further requirements for all four would need to be duplicated!
I have inherited a stored procedure and am having problems with it takes a very long time to run (around 3 minutes). I have played around with it, and without the where clause it actually only takes 12 seconds to run. None of the tables it references have a lot of data in them, can anybody see any reason why adding the main where clause below makes it take so much longer?
ALTER Procedure [dbo].[MissingReadingsReport] #SiteID INT,
#FormID INT,
#StartDate Varchar(8),
#EndDate Varchar(8)
As
If #EndDate > GetDate()
Set #EndDate = Convert(Varchar(8), GetDate(), 112)
Select Dt.FormID,
DT.FormDAte,
DT.Frequency,
Dt.DayOfWeek,
DT.NumberOfRecords,
Dt.FormName,
dt.OrgDesc,
Dt.CDesc
FROM (Select MeterForms.FormID,
MeterForms.FormName,
MeterForms.SiteID,
MeterForms.Frequency,
DateTable.FormDate,
tblOrganisation.OrgDesc,
CDesc = ( COMPANY.OrgDesc ),
DayOfWeek = CASE Frequency
WHEN 'Day' THEN DatePart(dw, DateTable.FormDate)
WHEN 'WEEK' THEN
DatePart(dw, MeterForms.FormDate)
END,
NumberOfRecords = CASE Frequency
WHEN 'Day' THEN (Select TOP 1 RecordID
FROM MeterReadings
Where
MeterReadings.FormDate =
DateTable.FormDate
And MeterReadings.FormID =
MeterForms.FormID
Order By RecordID DESC)
WHEN 'WEEK' THEN (Select TOP 1 ( FormDate )
FROM MeterReadings
Where
MeterReadings.FormDate >=
DateAdd(d
, -4,
DateTable.FormDate)
And MeterReadings.FormDate
<=
DateAdd(d, 3,
DateTable.FormDate)
AND MeterReadings.FormID =
MeterForms.FormID)
END
FROM MeterForms
INNER JOIN DateTable
ON MeterForms.FormDate <= DateTable.FormDate
INNER JOIN tblOrganisation
ON MeterForms.SiteID = tblOrganisation.pkOrgId
INNER JOIN tblOrganisation COMPANY
ON tblOrganisation.fkOrgID = COMPANY.pkOrgID
/*this is what makes the query run slowly*/
Where DateTable.FormDAte >= #StartDAte
AND DateTable.FormDate <= #EndDate
AND MeterForms.SiteID = ISNULL(#SiteID, MeterForms.SiteID)
AND MeterForms.FormID = IsNull(#FormID, MeterForms.FormID)
AND MeterForms.FormID > 0)DT
Where ( Frequency = 'Day'
And dt.NumberofRecords IS NULL )
OR ( ( Frequency = 'Week'
AND DayOfWeek = DATEPART (dw, Dt.FormDate) )
AND ( FormDate <> NumberOfRecords
OR dt.NumberofRecords IS NULL ) )
Order By FormID
Based on what you've already mentioned, it looks like the tables are properly indexed for columns in the join conditions but not for the columns in the where clause.
If you're not willing to change the query, it may be worth it to look into indexes defined on the where clause columns, specially that have the NULL check
Try replacing your select with this:
FROM
(select siteid, formid, formdate from meterforms
where siteid = isnull(#siteid, siteid) and
meterforms.formid = isnull(#formid, formid) and formid >0
) MeterForms
INNER JOIN
(select formdate from datetable where formdate >= #startdate and formdate <= #enddate) DateTable
ON MeterForms.FormDate <= DateTable.FormDate
INNER JOIN tblOrganisation
ON MeterForms.SiteID = tblOrganisation.pkOrgId
INNER JOIN tblOrganisation COMPANY
ON tblOrganisation.fkOrgID = COMPANY.pkOrgID
/*this is what makes the query run slowly*/
)DT
I would be willing to bet that if you moved the Meterforms where clauses up to the from statement:
FROM (select [columns] from MeterForms WHERE SiteID= ISNULL [etc] ) MF
INNER JOIN [etc]
It would be faster, as the filtering would occur before the join. Also, having your INNER JOIN on your DateTable doing a <= down in your where clause may be returning more than you'd like ... try moving that between up to a subselect as well.
Have you run an execution plan on this yet to see where the bottleneck is?
Random suggestion, coming from an Oracle background:
What happens if you rewrite the following:
AND MeterForms.SiteID = ISNULL(#SiteID, MeterForms.SiteID)
AND MeterForms.FormID = IsNull(#FormID, MeterForms.FormID)
...to
AND (#SiteID is null or MeterForms.SiteID = #SiteID)
AND (#FormID is null or MeterForms.FormID = #FormID)
I am using this query:
SELECT D.Generic, D.Ww, D.Dd, D.Plan, c.TotalScan, D.Plan - c.TotalScan AS Balance
FROM TableA D
LEFT JOIN (
SELECT COUNT(a.Specific) AS TotalScan,
b.Generic, a.Dd,a.Ww
FROM TableB a
INNER JOIN TableC b
ON a.Specific = b.Specific
GROUP
BY b.Generic,a.Dd,a.Ww
WHERE DATEDIFF(DAY, a.TransactionDate, GETDATE()) = 0
) c
ON c.Generic = D.Generic
AND D.Ww = c.Ww
AND c.Dd = D.Dd
WHERE DATEDIFF(DAY, c.TransactionDate, GETDATE()) = 0;
to filter all records that is a insert in my sqlserver database.
Now i am having a hard time how can i do it ms access.
1. DATEDIFF(Day, TransactionDate, GetDate()) = 0 -- Not Work on MS Access(Which Filter all Records inserted in current Date)
2. Cant display TotalScan from subquery
Example Output Date:
TransactionDate
3/21/2011 7:26:24 AM
3/21/2011 7:26:24 AM
3/22/2011 7:26:24 AM --
3/22/2011 7:26:28 AM --
3/22/2011 7:26:30 AM --
3/22/2011 7:26:32 AM --
3/22/2011 7:26:35 AM --
if my date today is 3/22/2011 5 records will be displayed.
Thanks in Regards
GetDate() is SQL Server specific, Access has Now() instead.
The DateDiff() function also exists in Access, but the parameter for the interval is different:
DateDiff("d", TransactionDate, Now())
Equivalent of:
DATEDIFF(DAY, c.TransactionDate, GETDATE()) = 0
DATEDIFF("d", c.TransactionDate, Now()) = 0
Regards