SQl Query get data very slow from different tables - sql

I am writing a sql query to get data from different tables but it is getting data from different tables very slowly.
Approximately above 2 minutes to complete.
What i am doing is here :
1. I am getting data differences and on behalf of date difference i am getting account numbers
2. I am comparing tables to get exact data i need.
here is my query
select T.accountno,
MAX(T.datetxn) as MxDt,
datediff(MM,MAX(T.datetxn), '2011-6-30') as Diffs,
max(P.Name) as POName
from Account_skd A,
AccountTxn_skd T,
POName P
where A.AccountNo = T.AccountNo and
GPOCode = A.OfficeCode and
Code = A.POCode and
A.servicecode = T.ServiceCode
group by T.AccountNo
order by len(T.AccountNo) DESC
please help that how i can use joins or any other way to get data within very less time say 5-10 seconds.

Since it appears you are getting EVERY ACCOUNT, and performance is slow, I would try by creating a prequery by just account, then do a single join to the other join tables something like..
select
T.Accountno,
T.MxDt,
datediff(MM, T.MxDt, '2011-6-30') as Diffs,
P.Name as POName
from
( select T1.AccountNo,
Max( T1.DateTxn ) MxDt
from AccontTxn_skd T1
group by T1.AccountNo ) T
JOIN Account_skd A
on T.AccountNo = A.AccountNo
JOIN POName P
on A.POCode = P.Code <-- GUESSING as you didn't qualify alias.field
AND A.OfficeCode = P.GPOCode <-- in your query for these two fields
order by
len(T.AccountNo) DESC
You had other elements based on the T.ServiceCode matching, but since you are only grouping on the account number anyhow, did it matter which service code was used? Otherwise, you would need to group by both the account AND service code (which I would have added the service code into the prequery and added as join condition to the account table too).

Related

Previous Record With Cross Apply Syntax

I have a table called ArchiveActivityDetails which shows the history of a Customer Repair Order. 1 Repair Order will have many visits (ActivityID) with a Technician allocated depending on who is available for that planned visit.
The system automatically allocates the time that is required for a job but sometimes a job requires longer so we manually ammend jobs.
My initial query from the customer was to pull the manually ammended jobs (ie: jobs where PlannedDuration >=60 minutes) and shows the Technician linked to that manually ammended job.
This report works fine.
My most recent request from the customer is to now ADD a column showing WHO WAS THE PREVIOUS TECHNICIAN linked that the Repair Order.
My collegues suggested I do a Cross Apply going back to the ArchiveActivityDetails table and then show "Previous Tech" but I have not used Cross Apply before and I am struggling with the syntax and unable to get the results I want. In my Cross Apply I used LAG to work out the 'PrevTech' but when pulling it into my main report, I get NULL. So I assume I am not doing the Cross Apply correctly.
DECLARE #DateFrom as DATE = '2019-05-20'
DECLARE #DATETO AS DATE = '2019-07-23'
----------------------------------------------------------------------------------
SELECT
AAD.Date
,ASM.ASM
,A.ASM as PrevASM
,ASM.KDGID2
,R.ResourceName
,R.ID_ResourceID
,A.ServiceOrderNumber
,CONCAT(EN.TECHVORNAME, ' ' , EN.TECHNACHNAME) as TechName
,A.PrevTech
,EN.TechnicianID
,AAD.ID_ActivityID
,SO.ServiceOrderNumber
,AAD.VisitNumber
,AAD.PlannedDuration
,AAD.ActualDuration
,AAD.PlannedDuration-AAD.ActualDuration as DIFF
,DR.Original_Duration
FROM
[Easy].[ASMTrans] AS ASM
INNER JOIN
[FS_OTBE].[EngPayrollNumbers] AS EN
ON ASM.KDGID2 = EN.KDGID2
INNER JOIN
[OFSA].[ResourceID] AS R
ON EN.TechnicianID = Try_cast(R.ResourceName as int)
INNER JOIN
[OFSDA].[ArchiveActivityDetails] as [AAD]
ON R.[ID_ResourceID] = AAD.ID_ResourceID
INNER JOIN
[OFSA].[ServiceOrderNumber] SO
ON SO.ID_ServiceOrderNumber = AAD.ID_ServiceOrderNumber
LEFT JOIN
[OFSE].[DurationRevision] DR
on DR.ID_ActivityID = AAD.ID_ActivityID
CROSS APPLY
(
SELECT
AD.Date
,AD.ID_CountryCode
,AD.ID_Status
,Activity_TypeID
,AD.ID_ActivityID
,AD.ID_ResourceID
,SO.ServiceOrderNumber
,ASM.ASM
,LAG(EN.TECHVORNAME+ ' '+EN.TECHNACHNAME) OVER (ORDER BY SO.ServiceOrderNumber,AD.ID_ActivityID) as PrevTech
,AD.VisitNumber
,AD.ID_ServiceOrderNumber
,AD.PlannedDuration
,AD.ActualDuration
,ROW_NUMBER() OVER (PARTITION BY AD.ID_ServiceOrderNumber Order by AD.ID_ActivityID,AD.Date) as ROWNUM
FROM
[Easy].[ASMTrans] AS ASM
INNER JOIN
[FS_OTBE].[EngPayrollNumbers] AS EN
ON ASM.KDGID2 = EN.KDGID2
INNER JOIN
[OFSA].[ResourceID] AS R
ON EN.TechnicianID = Try_cast(R.ResourceName as int)
INNER JOIN
[OFSDA].[ArchiveActivityDetails] as [AD]
ON R.[ID_ResourceID] = AD.ID_ResourceID
INNER JOIN
[OFSA].[ServiceOrderNumber] SO
ON SO.ID_ServiceOrderNumber = AD.ID_ServiceOrderNumber
WHERE
AAD.ID_ActivityID = AD.ID_ActivityID
AND
AD.ID_CountryCode = AAD.ID_CountryCode
AND AD.ID_Status = AAD.ID_Status
AND AD.ID_ResourceID = AAD.ID_ResourceID
AND AD.Activity_TypeID = AAD.Activity_TypeID
AND AD.ID_ServiceOrderNumber = AAD.ID_ServiceOrderNumber
AND AD.Date >= '2019-05-01'
) as A
WHERE
ASM.KDGID2
IN (50008323,50008326,50008329,50008332,50008335,50008338,50008341,50008344,50008347,50008350,50008353,50008356,50008359,50008362,50008365)
AND AAD.ID_Status = 1
AND AAD.ID_CountryCode = 7
AND AAD.Activity_TypeID=91
AND
(
AAD.[Date] BETWEEN IIF(#DateFrom < '20190520','20190520',#DateFrom) AND IIF(#DateTo < '20190520','20190520',#DateTo))
AND AAD.ActualDuration > 11
AND
(
(DR.Original_Duration >= 60)
OR
(DR.ID_ActivityID IS NULL AND AAD.PlannedDuration >= 60))
I expect to see the previous Tech and previous Area Sales Manager for the job that was Manually Ammended.
Business Reason: Managers want to see who initially requested for the job to be Manually Ammended. The time requested is being over estimated which is wasting time. To plan better they need to see who requests extra time at a job and try to reduce the time.
I will attach the ArchiveActivityDetail table showing the history of a Repair Order as well as expected results.
Your query results in the cross apply will appear as a table in your query, so you can use top(1) and order by descending to get the first row ordered by what you want (it looks like ActivityId? maybe VisitNumber?).
Simplifying to get at the root of the issue, say you have just one table with ServiceOrderNumber, ID_Activity, ASM, and TECH. To get the previous row for activity 2414073 you would do this:
select top(1) ASM, TECH
from OFSDA.ArchiveActivityDetails as AD
where ID_ServiceOrderNumber = 2370634229 -- same ServiceOrderNumber
and ID_Activity < 2414073 -- previous activities
order by ID_Activity desc -- highest activity less than 2414073
Instead of cross apply, you probably want to use outer apply. This is the same but you will get a row in your main query for the first activity, it will just have nulls for values in your apply. If you want the first row omitted from your results because it doesn't have a previous row, go ahead and use cross apply.
You can just put the above query into the parenthesis in outer apply() and add an alias (Previous). You link to the values for the current row in your main query, use top(1) to get the first row only, and order by ID_Activity descending to get the row with the highest ID_Activity.
select ASM, TECH,
PreviousASM, PreviousTECH
from OFSDA.ArchiveActivityDetails as AD
outer apply (
select top(1) ADInner.ASM as PreviousASM, ADInner.TECH as PreviousTECH
from OFSDA.ArchiveActivityDetails as ADInner
where ADInner.ID_ServiceOrderNumber = AD.ID_ServiceOrderNumber
and ADInner.ID_Activity < AD.ID_Activity
order by ADInnerID_Activity desc
) Previous
where ID_ServiceOrderNumber = 2370634229

Include missing years in Group By query

I am fairly new in Access and SQL programming. I am trying to do the following:
Sum(SO_SalesOrderPaymentHistoryLineT.Amount) AS [Sum Of PaymentPerYear]
and group by year even when there is no amount in some of the years. I would like to have these years listed as well for a report with charts. I'm not certain if this is possible, but every bit of help is appreciated.
My code so far is as follows:
SELECT
Base_CustomerT.SalesRep,
SO_SalesOrderT.CustomerId,
Base_CustomerT.Customer,
SO_SalesOrderPaymentHistoryLineT.DatePaid,
Sum(SO_SalesOrderPaymentHistoryLineT.Amount) AS [Sum Of PaymentPerYear]
FROM
Base_CustomerT
INNER JOIN (
SO_SalesOrderPaymentHistoryLineT
INNER JOIN SO_SalesOrderT
ON SO_SalesOrderPaymentHistoryLineT.SalesOrderId = SO_SalesOrderT.SalesOrderId
) ON Base_CustomerT.CustomerId = SO_SalesOrderT.CustomerId
GROUP BY
Base_CustomerT.SalesRep,
SO_SalesOrderT.CustomerId,
Base_CustomerT.Customer,
SO_SalesOrderPaymentHistoryLineT.DatePaid,
SO_SalesOrderPaymentHistoryLineT.PaymentType,
Base_CustomerT.IsActive
HAVING
(((SO_SalesOrderPaymentHistoryLineT.PaymentType)=1)
AND ((Base_CustomerT.IsActive)=Yes))
ORDER BY
Base_CustomerT.SalesRep,
Base_CustomerT.Customer;
You need another table with all years listed -- you can create this on the fly or have one in the db... join from that. So if you had a table called alltheyears with a column called y that just listed the years then you could use code like this:
WITH minmax as
(
select min(year(SO_SalesOrderPaymentHistoryLineT.DatePaid) as minyear,
max(year(SO_SalesOrderPaymentHistoryLineT.DatePaid) as maxyear)
from SalesOrderPaymentHistoryLineT
), yearsused as
(
select y
from alltheyears, minmax
where alltheyears.y >= minyear and alltheyears.y <= maxyear
)
select *
from yearsused
join ( -- your query above goes here! -- ) T
ON year(T.SO_SalesOrderPaymentHistoryLineT.DatePaid) = yearsused.y
You need a data source that will provide the year numbers. You cannot manufacture them out of thin air. Supposing you had a table Interesting_year with a single column year, populated, say, with every distinct integer between 2000 and 2050, you could do something like this:
SELECT
base.SalesRep,
base.CustomerId,
base.Customer,
base.year,
Sum(NZ(data.Amount)) AS [Sum Of PaymentPerYear]
FROM
(SELECT * FROM Base_CustomerT INNER JOIN Year) AS base
LEFT JOIN
(SELECT * FROM
SO_SalesOrderT
INNER JOIN SO_SalesOrderPaymentHistoryLineT
ON (SO_SalesOrderPaymentHistoryLineT.SalesOrderId = SO_SalesOrderT.SalesOrderId)
) AS data
ON ((base.CustomerId = data.CustomerId)
AND (base.year = Year(data.DatePaid))),
WHERE
(data.PaymentType = 1)
AND (base.IsActive = Yes)
AND (base.year BETWEEN
(SELECT Min(year(DatePaid) FROM SO_SalesOrderPaymentHistoryLineT)
AND (SELECT Max(year(DatePaid) FROM SO_SalesOrderPaymentHistoryLineT))
GROUP BY
base.SalesRep,
base.CustomerId,
base.Customer,
base.year,
ORDER BY
base.SalesRep,
base.Customer;
Note the following:
The revised query first forms the Cartesian product of BaseCustomerT with Interesting_year in order to have base customer data associated with each year (this is sometimes called a CROSS JOIN, but it's the same thing as an INNER JOIN with no join predicate, which is what Access requires)
In order to have result rows for years with no payments, you must perform an outer join (in this case a LEFT JOIN). Where a (base customer, year) combination has no associated orders, the rest of the columns of the join result will be NULL.
I'm selecting the CustomerId from Base_CustomerT because you would sometimes get a NULL if you selected from SO_SalesOrderT as in the starting query
I'm using the Access Nz() function to convert NULL payment amounts to 0 (from rows corresponding to years with no payments)
I converted your HAVING clause to a WHERE clause. That's semantically equivalent in this particular case, and it will be more efficient because the WHERE filter is applied before groups are formed, and because it allows some columns to be omitted from the GROUP BY clause.
Following Hogan's example, I filter out data for years outside the overall range covered by your data. Alternatively, you could achieve the same effect without that filter condition and its subqueries by ensuring that table Intersting_year contains only the year numbers for which you want results.
Update: modified the query to a different, but logically equivalent "something like this" that I hope Access will like better. Aside from adding a bunch of parentheses, the main difference is making both the left and the right operand of the LEFT JOIN into a subquery. That's consistent with the consensus recommendation for resolving Access "ambiguous outer join" errors.
Thank you John for your help. I found a solution which works for me. It looks quiet different but I learned a lot out of it. If you are interested here is how it looks now.
SELECT DISTINCTROW
Base_Customer_RevenueYearQ.SalesRep,
Base_Customer_RevenueYearQ.CustomerId,
Base_Customer_RevenueYearQ.Customer,
Base_Customer_RevenueYearQ.RevenueYear,
CustomerPaymentPerYearQ.[Sum Of PaymentPerYear]
FROM
Base_Customer_RevenueYearQ
LEFT JOIN CustomerPaymentPerYearQ
ON (Base_Customer_RevenueYearQ.RevenueYear = CustomerPaymentPerYearQ.[RevenueYear])
AND (Base_Customer_RevenueYearQ.CustomerId = CustomerPaymentPerYearQ.CustomerId)
GROUP BY
Base_Customer_RevenueYearQ.SalesRep,
Base_Customer_RevenueYearQ.CustomerId,
Base_Customer_RevenueYearQ.Customer,
Base_Customer_RevenueYearQ.RevenueYear,
CustomerPaymentPerYearQ.[Sum Of PaymentPerYear]
;

Timeout running SQL query

I'm trying to using the aggregation features of the django ORM to run a query on a MSSQL 2008R2 database, but I keep getting a timeout error. The query (generated by django) which fails is below. I've tried running it directs the SQL management studio and it works, but takes 3.5 min
It does look it's aggregating over a bunch of fields which it doesn't need to, but I wouldn't have though that should really cause it to take that long. The database isn't that big either, auth_user has 9 records, ticket_ticket has 1210, and ticket_watchers has 1876. Is there something I'm missing?
SELECT
[auth_user].[id],
[auth_user].[password],
[auth_user].[last_login],
[auth_user].[is_superuser],
[auth_user].[username],
[auth_user].[first_name],
[auth_user].[last_name],
[auth_user].[email],
[auth_user].[is_staff],
[auth_user].[is_active],
[auth_user].[date_joined],
COUNT([tickets_ticket].[id]) AS [tickets_captured__count],
COUNT(T3.[id]) AS [assigned_tickets__count],
COUNT([tickets_ticket_watchers].[ticket_id]) AS [tickets_watched__count]
FROM
[auth_user]
LEFT OUTER JOIN [tickets_ticket] ON ([auth_user].[id] = [tickets_ticket].[capturer_id])
LEFT OUTER JOIN [tickets_ticket] T3 ON ([auth_user].[id] = T3.[responsible_id])
LEFT OUTER JOIN [tickets_ticket_watchers] ON ([auth_user].[id] = [tickets_ticket_watchers].[user_id])
GROUP BY
[auth_user].[id],
[auth_user].[password],
[auth_user].[last_login],
[auth_user].[is_superuser],
[auth_user].[username],
[auth_user].[first_name],
[auth_user].[last_name],
[auth_user].[email],
[auth_user].[is_staff],
[auth_user].[is_active],
[auth_user].[date_joined]
HAVING
(COUNT([tickets_ticket].[id]) > 0 OR COUNT(T3.[id]) > 0 )
EDIT:
Here are the relevant indexes (excluding those not used in the query):
auth_user.id (PK)
auth_user.username (Unique)
tickets_ticket.id (PK)
tickets_ticket.capturer_id
tickets_ticket.responsible_id
tickets_ticket_watchers.id (PK)
tickets_ticket_watchers.user_id
tickets_ticket_watchers.ticket_id
EDIT 2:
After a bit of experimentation, I've found that the following query is the smallest that results in the slow execution:
SELECT
COUNT([tickets_ticket].[id]) AS [tickets_captured__count],
COUNT(T3.[id]) AS [assigned_tickets__count],
COUNT([tickets_ticket_watchers].[ticket_id]) AS [tickets_watched__count]
FROM
[auth_user]
LEFT OUTER JOIN [tickets_ticket] ON ([auth_user].[id] = [tickets_ticket].[capturer_id])
LEFT OUTER JOIN [tickets_ticket] T3 ON ([auth_user].[id] = T3.[responsible_id])
LEFT OUTER JOIN [tickets_ticket_watchers] ON ([auth_user].[id] = [tickets_ticket_watchers].[user_id])
GROUP BY
[auth_user].[id]
The weird thing is that if I comment out any two lines in the above, it runs in less that 1s, but it doesn't seem to matter which lines I remove (although obviously I can't remove a join without also removing the relevant SELECT line).
EDIT 3:
The python code which generated this is:
User.objects.annotate(
Count('tickets_captured'),
Count('assigned_tickets'),
Count('tickets_watched')
)
A look at the execution plan shows that SQL Server is first doing a cross-join on all the table, resulting in about 280 million rows, and 6Gb of data. I assume that this is where the problem lies, but why is it happening?
SQL Server is doing exactly what it was asked to do. Unfortunately, Django is not generating the right query for what you want. It looks like you need to count distinct, instead of just count: Django annotate() multiple times causes wrong answers
As for why the query works that way: The query says to join the four tables together. So say an author has 2 captured tickets, 3 assigned tickets, and 4 watched tickets, the join will return 2*3*4 tickets, one for each combination of tickets. The distinct part will remove all the duplicates.
what about this?
SELECT auth_user.*,
C1.tickets_captured__count
C2.assigned_tickets__count
C3.tickets_watched__count
FROM
auth_user
LEFT JOIN
( SELECT capturer_id, COUNT(*) AS tickets_captured__count
FROM tickets_ticket GROUP BY capturer_id ) AS C1 ON auth_user.id = C1.capturer_id
LEFT JOIN
( SELECT responsible_id, COUNT(*) AS assigned_tickets__count
FROM tickets_ticket GROUP BY responsible_id ) AS C2 ON auth_user.id = C2.responsible_id
LEFT JOIN
( SELECT user_id, COUNT(*) AS tickets_watched__count
FROM tickets_ticket_watchers GROUP BY user_id ) AS C3 ON auth_user.id = C3.user_id
WHERE C1.tickets_captured__count > 0 OR C2.assigned_tickets__count > 0
--WHERE C1.tickets_captured__count is not null OR C2.assigned_tickets__count is not null -- also works (I think with beter performance)

BigQuery - Shuffle By error

I have a table of about 5M rows. Note this is just a poc. Ultimately we will need to be in the TB range. I am doing a self join to find permutations of products for a market basket analysis.
I need to find the number of times the combination occurs in a basket, the ratio of occurrences to total baskets, and the number of times the item occurs in all baskets. This is pretty standard. BigQuery does not support selects in the predicate of another select so I needed to create another join I suppose. Here's what I came up with -
select twoItem.upc1,twoItem.upc2,twoItem.twoItemOccurrences, totalUpc.totalUpcCount
from
(
select purchase1.upc as upc1,purchase2.upc as upc2,count(upc1) as twoItemOccurrences
from
conagra.purchase as purchase1
join each conagra.purchase as purchase2
on purchase1.upc = purchase2.upc
group by upc1,upc2
) as twoItem
JOIN EACH
(
select purchase3.upc as upc3, count(*) as totalUpcCount
from conagra.purchase as purchase3
group by upc3
) as totalUpc
on totalUpc.upc3 = twoItem.upc1
LIMIT 50;
I get the following error:
SHUFFLE BY may only be applied to parallelizable queries, but query is not parallelizable: (SELECT * FROM (SELECT [purchase3.upc] AS [upc3], COUNT(*) AS [totalUpcCount]...
Maybe an unpublished limitation?
Any help would be appreciated.
Try running these with GROUP EACH BY on your inner queries. We'll improve the response message for queries like this.

SUM(a*b) not working

I have a PHP page running in postgres. I have 3 tables - workorders, wo_parts and part2vendor. I am trying to multiply 2 table column row datas together, ie wo_parts has a field called qty and part2vendor has a field called cost. These 2 are joined by wo_parts.pn and part2vendor.pn. I have created a query like this:
$scoreCostQuery = "SELECT SUM(part2vendor.cost*wo_parts.qty) as total_score
FROM part2vendor
INNER JOIN wo_parts
ON (wo_parts.pn=part2vendor.pn)
WHERE workorder=$workorder";
But if I add the costs of the parts multiplied by the qauntities supplied, it adds to a different number than what the script is doing. Help....I am new to this but if someone can show me in SQL I can modify it for postgres. Thanks
Without seeing example data, there's no way for us to know why you're query totals are coming out differently that when you do the math by hand. It could be a bad join, so you are getting more/less records than you expected. It's also possible that your calculations are off. Pick an example with the smallest number of associated records & compare.
My suggestion is to add a GROUP BY to the query:
SELECT SUM(p.cost * wp.qty) as total_score
FROM part2vendor p
JOIN wo_parts wp ON wp.pn = p.pn
WHERE workorder = $workorder
GROUP BY workorder
FYI: MySQL was designed to allow flexibility in the GROUP BY, while no other db I've used does - it's a source of numerous questions on SO "why does this work in MySQL when it doesn't work on db x...".
To Check that your Quantities are correct:
SELECT wp.qty,
p.cost
FROM WO_PARTS wp
JOIN PART2VENDOR p ON p.pn = wp.pn
WHERE p.workorder = $workorder
Check that the numbers are correct for a given order.
You could try a sub-query instead.
(Note, I don't have a Postgres installation to test this on so consider this more like pseudo code than a working example... It does work in MySQL tho)
SELECT
SUM(p.`score`) AS 'total_score'
FROM part2vendor AS p2v
INNER JOIN (
SELECT pn, cost * qty AS `score`
FROM wo_parts
) AS p
ON p.pn = p2v.pn
WHERE p2n.workorder=$workorder"
In the question, you say the cost column is in part2vendor, but in the query you reference wo_parts.cost. If the wo_parts table has its own cost column, that's the source of the problem.