I need to sum up the values for the last 7 days,so it should be the current plus the previous 6. This should happen for each row i.e. in each row the column value would be current + previous 6.
The case :-
(Note:- I will calculate the hours,by suming up the seconds).
I tried using the below query :-
select SUM([drivingTime]) OVER(PARTITION BY driverid ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW)
from [f.DriverHseCan]
The problem I face is I have to do grouping on driver,asset for a date
In the above case,the driving time should be sumed up and then,its previous 6 rows should be taken,
I cant do this using rank() because I need these rows as well as I have to show it in the report.
I tried doing this in SSRS and SQL both.
In short it is adding total driving time for current+ 6 previous days
Try the following query
SELECT
s.date
, s.driverid
, s.assetid
, s.drivingtime
, SUM(s2.drivingtime) AS total_drivingtime
FROM f.DriverHseCan s
JOIN (
SELECT date,driverid, SUM(drivingtime) drivingtime
FROM f.DriverHseCan
GROUP BY date,driverid
) AS s2
ON s.driverid = s2.driverid AND s2.date BETWEEN DATEADD(d,-6,s.date) AND s.date
GROUP BY
s.date
, s.driverid
, s.assetid
, s.drivingtime
If you have week start/end dates, there could be better performing alternatives to solve your problem, e.g. use the week number in SSRS expressions rather than do the self join on SQL server
I think aggregation does what you want:
select sum(sum([drivingTime])) over (partition by driverid
order by date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
)
from [f.DriverHseCan]
group by driverid, date
I guess you need to use CROSS APPLY.
Something like following? :
SELECT driverID,
date,
CA.Last6DayDrivingTime
FROM YourTable YT
CROSS APPLY
(
SELECT SUM(drivingTime) AS Last6DayDrivingTime
FROM YourTable CA ON CA.driverID=YT.driverID
WHERE CA.date BETWEEN DATEADD(DAY,-6,YT.date) AND YT.date)
) CA
Edit:
As you commented that cross apply slow down the performance, other option is to pre calculate the week values in temp table or using CTE and then use them in your main query.
Related
I need to use this SQL query for a software and get the time in a particular format hence the reason for the Time column however I need the query to insert the months that are missing with the value from the previous month. This is the query I currently have.
SELECT [accountnumber],SUM([postingamount]) AS Amount, [accountingdate],
convert(varchar(4),year(accountingdate))+'M'+ Format(DATEPART( MONTH, accountingdate) , '00')
AS [Time]
FROM [7 GL Detail MACL]
where [accountingdate]>='2019-01-01'
GROUP BY [accountingdate],[postingamount],[accountnumber]
Current Results
Expected Results
Since you didn't specify the RDBMS system you're using, I can't guarantee that this logic will work because every system uses slightly different SQL syntax.
However I used Rasgo datespine function to generate this SQL, as it is quite complex to wrap your head around, and tested it on Snowflake.
The main differences between Snowflake and other systems are: DATEADD and TABLE (GENERATOR())
In case you can't modify this to work in your system, here are the basic steps which you'll want to follow:
Select unique accountnumbers
Select unique dates (month beginnings?) This is where Snowflake uses GENERATOR but other systems might actually have a Calendar table you can select from
Cross Join (cartesian join) these to create every possible combination of accountnumber and date
Outer Join #3 to your data (might have to truncate your date to month-begin)
Filter out rows that dont apply. Like for instance you might have just inserted a row for 1/1/2019 for an account that didn't even begin until 12/12/2020.
WITH GLOBAL_SPINE AS (
SELECT
ROW_NUMBER() OVER (ORDER BY NULL) as INTERVAL_ID,
DATEADD('MONTH', (INTERVAL_ID - 1), '2019-01-01'::timestamp_ntz) as SPINE_START,
DATEADD('MONTH', INTERVAL_ID, '2022-06-01'::timestamp_ntz) as SPINE_END
FROM TABLE (GENERATOR(ROWCOUNT => 42))
),
GROUPS AS (
SELECT
accountnumber,
MIN(DESIRED_INTERVAL) AS LOCAL_START,
MAX(DESIRED_INTERVAL) AS LOCAL_END
FROM [7 GL Detail MACL]
GROUP BY
accountnumber
),
GROUP_SPINE AS (
SELECT
accountnumber,
SPINE_START AS GROUP_START,
SPINE_END AS GROUP_END
FROM GROUPS G
CROSS JOIN LATERAL (
SELECT
SPINE_START, SPINE_END
FROM GLOBAL_SPINE S
WHERE S.SPINE_START >= G.LOCAL_START
)
)
SELECT
G.accountnumber AS GROUP_BY_accountnumber,
GROUP_START,
GROUP_END,
T.*
FROM GROUP_SPINE G
LEFT JOIN {{ your_table }} T
ON DESIRED_INTERVAL >= G.GROUP_START
AND DESIRED_INTERVAL < G.GROUP_END
AND G.accountnumber = T.accountnumber;
You were also doing an aggregation step, but I figure once you get this complicated part down, you can figure out how to finally aggregate it the way you want it.
I am using Terdata SQL Assistant connected to an enterprise DW. I have written the query below to show an inventory of outstanding items as of a specific point in time. The table referenced loads and stores new records as changes are made to their state by load date (and does not delete historical records). The output of my query is 1 row for the specified date. Can I create a stored procedure or recursive query of some sort to build a history of these summary rows (with 1 new row per day)? I have not used such functions in the past; links to pertinent previously answered questions or suggestions on how I could get on the right track in researching other possible solutions are totally fine if applicable; just trying to bridge this gap in my knowledge.
SELECT
'2017-10-02' as Dt
,COUNT(DISTINCT A.RECORD_NBR) as Pending_Records
,SUM(A.PAY_AMT) AS Total_Pending_Payments
FROM DB.RECORD_HISTORY A
INNER JOIN
(SELECT MAX(LOAD_DT) AS LOAD_DT
,RECORD_NBR
FROM DB.RECORD_HISTORY
WHERE LOAD_DT <= '2017-10-02'
GROUP BY RECORD_NBR
) B
ON A.RECORD_NBR = B.RECORD_NBR
AND A.LOAD_DT = B.LOAD_DT
WHERE
A.RECORD_ORDER =1 AND Final_DT Is Null
GROUP BY Dt
ORDER BY 1 desc
Here is my interpretation of your query:
For the most recent load_dt (up until 2017-10-02) for record_order #1,
return
1) the number of different pending records
2) the total amount of pending payments
Is this correct? If you're looking for this info, but one row for each "Load_Dt", you just need to remove that INNER JOIN:
SELECT
load_Dt,
COUNT(DISTINCT record_nbr) AS Pending_Records,
SUM(pay_amt) AS Total_Pending_Payments
FROM DB.record_history
WHERE record_order = 1
AND final_Dt IS NULL
GROUP BY load_Dt
ORDER BY 1 DESC
If you want to get the summary info per record_order, just add record_order as a grouping column:
SELECT
load_Dt,
record_order,
COUNT(DISTINCT record_nbr) AS Pending_Records,
SUM(pay_amt) AS Total_Pending_Payments
FROM DB.record_history
WHERE final_Dt IS NULL
GROUP BY load_Dt, record_order
ORDER BY 1,2 DESC
If you want to get one row per day (if there are calendar days with no corresponding "load_dt" days), then you can SELECT from the sys_calendar.calendar view and LEFT JOIN the query above on the "load_dt" field:
SELECT cal.calendar_date, src.Pending_Records, src.Total_Pending_Payments
FROM sys_calendar.calendar cal
LEFT JOIN (
SELECT
load_Dt,
COUNT(DISTINCT record_nbr) AS Pending_Records,
SUM(pay_amt) AS Total_Pending_Payments
FROM DB.record_history
WHERE record_order = 1
AND final_Dt IS NULL
GROUP BY load_Dt
) src ON cal.calendar_date = src.load_Dt
WHERE cal.calendar_date BETWEEN <start_date> AND <end_date>
ORDER BY 1 DESC
I don't have access to a TD system, so you may get syntax errors. Let me know if that works or you're looking for something else.
I am trying to write a query that would get the customers with 7 consecutive transactions given a list of CustomerKeys.
I am currently doing a self join on Customer fact table that has 700 Million records in SQL Server 2008.
This is is what I came up with but its taking a long time to run. I have an clustered index as (CustomerKey, TranDateKey)
SELECT
ct1.CustomerKey,ct1.TranDateKey
FROM
CustomerTransactionFact ct1
INNER JOIN
#CRTCustomerList dl ON ct1.CustomerKey = dl.CustomerKey --temp table with customer list
INNER JOIN
dbo.CustomerTransactionFact ct2 ON ct1.CustomerKey = ct2.CustomerKey -- Same Customer
AND ct2.TranDateKey >= ct1.TranDateKey
AND ct2.TranDateKey <= CONVERT(VARCHAR(8), (dateadd(d, 6, ct1.TranDateTime), 112) -- Consecutive Transactions in the last 7 days
WHERE
ct1.LogID >= 82800000
AND ct2.LogID >= 82800000
AND ct1.TranDateKey between dl.BeginTranDateKey and dl.EndTranDateKey
AND ct2.TranDateKey between dl.BeginTranDateKey and dl.EndTranDateKey
GROUP BY
ct1.CustomerKey,ct1.TranDateKey
HAVING
COUNT(*) = 7
Please help make it more efficient. Is there a better way to write this query in 2008?
You can do this using window functions, which should be much faster. Assuming that TranDateKey is a number and you can subtract a sequential number from it, then the difference constant for consecutive days.
You can put this in a query like this:
SELECT CustomerKey, MIN(TranDateKey), MAX(TranDateKey)
FROM (SELECT ct.CustomerKey, ct.TranDateKey,
(ct.TranDateKey -
DENSE_RANK() OVER (PARTITION BY ct.CustomerKey, ct.TranDateKey)
) as grp
FROM CustomerTransactionFact ct INNER JOIN
#CRTCustomerList dl
ON ct.CustomerKey = dl.CustomerKey
) t
GROUP BY CustomerKey, grp
HAVING COUNT(*) = 7;
If your date key is something else, there is probably a way to modify the query to handle that, but you might have to join to the dimension table.
This would be a perfect task for a COUNT(*) OVER (RANGE ...), but SQL Server 2008 supports only a limited syntax for Windowed Aggregate Functions.
SELECT CustomerKey, MIN(TranDateKey), COUNT(*)
FROM
(
SELECT CustomerKey, TranDateKey,
dateadd(d,-ROW_NUMBER()
OVER (PARTITION BY CustomerKey
ORDER BY TranDateKey),TranDateTime) AS dummyDate
FROM CustomerTransactionFact
) AS dt
GROUP BY CustomerKey, dummyDate
HAVING COUNT(*) >= 7
The dateadd calculates the difference between the current TranDateTime and a Row_Number over all date per customer. The resulting dummyDatehas no actual meaning, but is the same meaningless date for consecutive dates.
I have a query:
;with date_cte as(
SELECT r.starburst_dept_name,r.monthly_past_date as PrevDate,x.monthly_past_date as CurrDate,r.starburst_dept_average - x.starburst_dept_average as Average
FROM
(
SELECT *,ROW_NUMBER() OVER(PARTITION BY starburst_dept_name ORDER BY monthly_past_date) AS rowid
FROM intranet.dbo.cse_reports_month
) r
JOIN
(
SELECT *,ROW_NUMBER() OVER(PARTITION BY starburst_dept_name ORDER BY monthly_past_date) AS rowid
FROM intranet.dbo.cse_reports_month
Where month(monthly_past_date) > month(DATEADD(m,-2,monthly_past_date))
) x
ON r.starburst_dept_name = x.starburst_dept_name AND r.rowid = x.rowid+1
Where r.starburst_dept_name is NOT NULL
)
Select *
From date_cte
Order by Average DESC
So doing some testing, I have alter some columns data, to see why it gives me certain information. I don't know why when I run the query it gives my a date column that should not be there from "january" (row 4) like the picture below:
The database has more data that has the same exact date '2014-01-25 00:00:00.000', so I'm not sure why it would only get that row and compare the average?
I did before I run the query alter the column in that row and change the date? But I'm not sure if that would have something to do with it.
UPDATE:
I have added the sqlfinddle,
What I would like to get it subtract the average
from last_month - last 2 month ago.
It Was actually working until I made a change and alter the data.
I made the changes to test a certain situation, which obviously lead
to learning that there are flaws to the query.
Based on your SQL Fiddle, this eliminates joins from prior than month-2 from showing up.
SELECT
thismonth.starburst_dept_name
,lastmonth.monthtly_past_date [PrevDate]
,thismonth.monthtly_past_date [CurrDate]
,thismonth.starburst_dept_average - lastmonth.starburst_dept_average as Average
FROM dbo.cse_reports thismonth
inner join dbo.cse_reports lastmonth on
thismonth.starburst_dept_name = lastmonth.starburst_dept_name
AND month(DATEADD(MONTH,-1,thismonth.monthtly_past_date))=month(lastmonth.monthtly_past_date)
WHERE MONTH(thismonth.monthtly_past_date)=month(DATEADD(MONTH,-1,GETDATE()))
Order by thismonth.starburst_dept_average - lastmonth.starburst_dept_average DESC
I have those two tables
1-Add to queue table
TransID , ADD date
10 , 10/10/2012
11 , 14/10/2012
11 , 18/11/2012
11 , 25/12/2012
12 , 1/1/2013
2-Removed from queue table
TransID , Removed Date
10 , 15/1/2013
11 , 12/12/2012
11 , 13/1/2013
11 , 20/1/2013
The TansID is the key between the two tables , and I can't modify those tables, what I want is to query the amount of time each transaction spent in the queue
It's easy when there is one item in each table , but when the item get queued more than once how do I calculate that?
Assuming the order TransIDs are entered into the Add table is the same order they are removed, you can use the following:
WITH OrderedAdds AS
( SELECT TransID,
AddDate,
[RowNumber] = ROW_NUMBER() OVER(PARTITION BY TransID ORDER BY AddDate)
FROM AddTable
), OrderedRemoves AS
( SELECT TransID,
RemovedDate,
[RowNumber] = ROW_NUMBER() OVER(PARTITION BY TransID ORDER BY RemovedDate)
FROM RemoveTable
)
SELECT OrderedAdds.TransID,
OrderedAdds.AddDate,
OrderedRemoves.RemovedDate,
[DaysInQueue] = DATEDIFF(DAY, OrderedAdds.AddDate, ISNULL(OrderedRemoves.RemovedDate, CURRENT_TIMESTAMP))
FROM OrderedAdds
LEFT JOIN OrderedRemoves
ON OrderedAdds.TransID = OrderedRemoves.TransID
AND OrderedAdds.RowNumber = OrderedRemoves.RowNumber;
The key part is that each record gets a rownumber based on the transaction id and the date it was entered, you can then join on both rownumber and transID to stop any cross joining.
Example on SQL Fiddle
DISCLAIMER: There is probably problem with this, but i hope to send you in one possible direction. Make sure to expect problems.
You can try in the following direction (which might work in some way depending on your system, version, etc) :
SELECT transId, (sum(add_date_sum) - sum(remove_date_sum)) / (1000*60*60*24)
FROM
(
SELECT transId, (SUM(UNIX_TIMESTAMP(add_date)) as add_date_sum, 0 as remove_date_sum
FROM add_to_queue
GROUP BY transId
UNION ALL
SELECT transId, 0 as add_date_sum, (SUM(UNIX_TIMESTAMP(remove_date)) as remove_date_sum
FROM remove_from_queue
GROUP BY transId
)
GROUP BY transId;
A bit of explanation: as far as I know, you cannot sum dates, but you can convert them to some sort of timestamps. Check if UNIX_TIMESTAMPS works for you, or figure out something else. Then you can sum in each table, create union by conveniently leaving the other one as zeto and then subtracting the union query.
As for that devision in the end of first SELECT, UNIT_TIMESTAMP throws out miliseconds, you devide to get days - or whatever it is that you want.
This all said - I would probably solve this using a stored procedure or some client script. SQL is not a weapon for every battle. Making two separate queries can be much simpler.
Answer 2: after your comments. (As a side note, some of your dates 15/1/2013,13/1/2013 do not represent proper date formats )
select transId, sum(numberOfDays) totalQueueTime
from (
select a.transId,
datediff(day,a.addDate,isnull(r.removeDate,a.addDate)) numberOfDays
from AddTable a left join RemoveTable r on a.transId = r.transId
order by a.transId, a.addDate, r.removeDate
) X
group by transId
Answer 1: before your comments
Assuming that there won't be a new record added unless it is being removed. Also note following query will bring numberOfDays as zero for unremoved records;
select a.transId, a.addDate, r.removeDate,
datediff(day,a.addDate,isnull(r.removeDate,a.addDate)) numberOfDays
from AddTable a left join RemoveTable r on a.transId = r.transId
order by a.transId, a.addDate, r.removeDate