I am retrieving the results of the mlog table and calculate the subtotal of the qtyn with the help of following code 1. I am stuck with how to join my second code criteria with the first.
Thanks for any help
1.
SELECT autn, date, itcode, qtyn, out,
date, phstock,
qtyn + COALESCE(
(SELECT SUM(qtyn) FROM dbo.mlog b
WHERE b.autn < a.autn
AND itcode = '40'), 0) AS balance
FROM dbo.mlog a
WHERE (itcode = '40')
ORDER BY autn
2.
date >=(SELECT MAX([date]) FROM mlog)
To append a condition to the code, use AND or OR. EG:
SELECT a.autn, a.date, a.itcode, a.qtyn, a.out,
a.date, a.phstock,
a.qtyn + COALESCE(
(SELECT SUM(b.qtyn) FROM dbo.mlog b
WHERE b.autn < a.autn
AND b.itcode = '40'), 0) AS balance
FROM dbo.mlog a
WHERE (a.itcode = '40' AND a.date >= (SELECT MAX([c.date]) FROM mlog c) )
ORDER BY a.autn
Not tested, but should do what you want
I have heard that SQL Server is rather inefficient with coalesce(), because it runs the first part twice. Here is an alternative way of writing this:
with ml as (
SELECT ml.autn, ml.date, ml.itcode, ml.qtyn, ml.out, ml.date, ml.phstock
FROM dbo.mlog ml
WHERE ml.itcode = '40' AND ml.date >= (SELECT MAX(ml1.date]) FROM mlog ml1)
)
select ml.*,
(select sum(m1l.qtyn) from ml ml1 where ml1.autn <= ml.autn) as balance
from ml
ORDER BY ml.autn
I also wonder if the where clause would be more efficient as:
WHERE ml.itcode = '40' AND ml.date = (SELECT top 1 ml1.date FROM mlog ml1 order by ml1.date desc)
Related
Hello I am trying to calculate the time difference of 2 consecutive rows for Date (either in hours or Days), as attached in the image
Highlighted in Yellow is the result I want which is basically the difference of the date in that row and 1 above.
How can we achieve it in the SQL? Attached is my complex code which has the rest of the fields in it
with cte
as
(
select m.voucher_no, CONVERT(VARCHAR(30),CONVERT(datetime, f.action_Date, 109),100) as action_date,f.col1_Value,f.col3_value,f.col4_value,f.comments,f.distr_user,f.wf_status,f.action_code,f.wf_user_id
from attdetailmap m
LEFT JOIN awftaskfin f ON f.oid = m.oid and f.client ='PC'
where f.action_Date !='' and action_date between '$?datef' and '$?datet'
),
.*select *, ROW_NUMBER() OVER(PARTITION BY action_Date,distr_user,wf_Status,wf_user_id order by action_Date,distr_user,wf_Status,wf_user_id ) as row_no_1 from cte
cte2 as
(
select *, ROW_NUMBER() OVER(PARTITION BY voucher_no,action_Date,distr_user,wf_Status,wf_user_id order by voucher_no ) as row_no_1 from cte
)
select distinct(v.dim_value) as resid,c.voucher_no,CONVERT(datetime, c.action_Date, 109) as action_Date,c.col4_value,c.comments,c.distr_user,v.description,c.wf_status,c.action_code, c.wf_user_id,v1.description as name,r.rel_value as pay_office,r1.rel_value as site
from cte2 c
LEFT OUTER JOIN aagviuserdetail v ON v.user_id = c.distr_user
LEFT OUTER JOIN aagviuserdetail v1 ON v1.user_id = c.wf_user_id
LEFT OUTER JOIN ahsrelvalue r ON r.resource_id = v.dim_Value and r.rel_Attr_id = 'P1' and r.period_to = '209912'
LEFT OUTER JOIN ahsrelvalue r1 ON r1.resource_id = v.dim_Value and r1.rel_Attr_id = 'Z1' and r1.period_to = '209912'
where c.row_no_1 = '1' and r.rel_value like '$?site1' and voucher_no like '$?trans'
order by voucher_no,action_Date
The key idea is lag(). However, date/time functions vary among databases. So, the idea is:
select t.*,
(date - lag(date) over (partition by transaction_no order by date)) as diff
from t;
I should note that this exact syntax might not work in your database -- because - may not even be defined on date/time values. However, lag() is a standard function and should be available.
For instance, in SQL Server, this would look like:
select t.*,
datediff(second, lag(date) over (partition by transaction_no order by date), date) / (24.0 * 60 * 60) as diff_days
from t;
I have the following problem.
Part of a task is to determine the visitor(s) with the most money spent between 2000 and 2020.
It just looks like this.
SELECT UserEMail FROM Visitor
JOIN Ticket ON Visitor.UserEMail = Ticket.VisitorUserEMail
where Ticket.Date> date('2000-01-01') AND Ticket.Date < date ('2020-12-31')
Group by Ticket.VisitorUserEMail
order by SUM(Price) DESC;
Is it possible to output more than one person if both have spent the same amount?
Use rank():
SELECT VisitorUserEMail
FROM (SELECT VisitorUserEMail, SUM(PRICE) as sum_price,
RANK() OVER (ORDER BY SUM(Price) DESC) as seqnum
FROM Ticket t
WHERE t.Date >= date('2000-01-01') AND Ticket.Date <= date('2021-01-01')
GROUP BY t.VisitorUserEMail
) t
WHERE seqnum = 1;
Note: You don't need the JOIN, assuming that ticket buyers are actually visitors. If that assumption is not true, then use the JOIN.
Use a CTE that returns all the total prices for each email and with NOT EXISTS select the rows with the top total price:
WITH cte AS (
SELECT VisitorUserEMail, SUM(Price) SumPrice
FROM Ticket
WHERE Date >= '2000-01-01' AND Date <= '2020-12-31'
GROUP BY VisitorUserEMail
)
SELECT c.VisitorUserEMail
FROM cte c
WHERE NOT EXISTS (
SELECT 1 FROM cte
WHERE SumPrice > c.SumPrice
)
or:
WITH cte AS (
SELECT VisitorUserEMail, SUM(Price) SumPrice
FROM Ticket
WHERE Date >= '2000-01-01' AND Date <= '2020-12-31'
GROUP BY VisitorUserEMail
)
SELECT VisitorUserEMail
FROM cte
WHERE SumPrice = (SELECT MAX(SumPrice) FROM cte)
Note that you don't need the function date() because the result of date('2000-01-01') is '2000-01-01'.
Also I think that the conditions in the WHERE clause should include the =, right?
I want to find records in date range 1/1/19-1/7/19 which increase amount
using table HISTORY:
DATE AMOUNT ID
(Date, number, varchar2(30))
I find IDs inside range correctly
assuming increase/decrease can happens only when having two records with same Id
with suspect as
(select id
from history
where t.createddate < to_date('2019-07-01', 'yyyy-mm-dd')
group by id
having count(1) > 1),
ids as
(select id
from history
join suspect
on history.id = suspect.id
where history.date > to_date('2019-01-01', 'yyyy-mm-dd')
and history.date < to_date('2019-07-01', 'yyyy-mm-dd'))
select count(distinct id)
from history a, history b
where a.id = b.id
and a.date < b.date
and a.amount < b.amount
The problem to find increase I need to find previous record which can be before time range
I can find last previous time before time range, but I failed to use it:
ids_prevtime as (
select history.*, max(t.date) over (partition by t.id) max_date
from history
join ids on history.userid = ids.id
where history.date < to_date('2019-01-01','yyyy-mm-dd' )
), ids_prev as (
select * from ids_prevtime where createdate=max_date
)
I see that you found solution, but maybe you could do it simpler, using lag():
select count(distinct id)
from (select id, date_, amount,
lag(amount) over (partition by id order by date_) prev_amt
from history)
where date_ between date '2019-01-01' and date '2019-07-01'
and amount > prev_amt;
dbfiddle
Add union of last history records before range with records inside range
ids_prev as
(select ID, DATE, AMOUNT
from id_before_rangetime
where createddate = max_date),
ids_in_range as
(select history.*
from history
join ids
on history.ID = ids.ID
where history.date > to_date('2019-01-01', 'yyyy-mm-dd')
and history.date < to_date('2019-07-01', 'yyyy-mm-dd')),
all_relevant as
(select * from ids_in_range union all select * from ids_prev)
and then count increases:
select count(distinct id)
from all_relevant a, all_relevant b
where a.id = b.id
and a.date < b.date
and a.amount < b.amount
I want to create a report, the report will have parameter for the user to select
-IsApprovedDate
-IsCatcheDate
I would like to know how to used the if else in the where clause.
Example if the user selects IsApprovedDate the report will lookup based on approved Date else will lookup based on catch date. In my query I will get top10 fish size base on award order weight here is my query.
;WITH CTE AS
(
select Rank() OVER (PARTITION BY c.trophyCatchCertificateTypeId order by c.catchWeight desc ) as rnk
,c.id,c.customerId, Cust.firstName + ' '+Cust.lastName as CustomerName
,CAST(CONVERT(varchar(10),catchWeightPoundsComponent)+'.'+CONVERT(varchar(10),catchWeightOuncesComponent) as numeric(6,2) ) WLBS
,c.catchGirth,c.catchLength,ct.description county
,t.description award--
,c.trophyCatchCertificateTypeId
,s.specificSpecies--
,c.speciesId
from Catches c
INNER JOIN TrophyCatchCertificateTypes t on c.trophyCatchCertificateTypeId = t.id
INNER JOIN Species s on c.speciesId = s.id
INNER JOIN Counties ct on c.countyId = ct.id
INNER JOIN Customers Cust on c.customerId = cust.id
Where c.bigCatchCertificateTypeId is not null
and c.catchStatusId =1
and c.speciesId =1 and c.isTrophyCatch =1
and c.catchDate >= #startDay and c.catchDate<=#endDay
)
Select * from CTE c1
Where rnk <=10
Just use conditional logic for this:
where . . . and
((#IsApprovedDate = 1 and c.ApprovedDate >= #startDay and c.ApprovedDate <= #endDay) or
(#IsCatchDate = 1 and c.catchDate >= #startDay and c.catchDate <= #endDay)
)
EDIT:
I would actually write this as:
where . . . and
((#IsApprovedDate = 1 and c.ApprovedDate >= #startDay and c.ApprovedDate < dateadd(day, 1 #endDay) or
(#IsCatchDate = 1 and c.catchDate >= #startDay and c.catchDate < dateadd(day, 1, #endDay))
)
This is a safer construct because it work when the date values have times and when they do not.
Performance will be much better if you build the WHERE clause dynamically in your code and then execute it.
I have a MS SQL table that contains stock data with the following columns: Id, Symbol, Date, Open, High, Low, Close.
I would like to self-join the table, so I can get a day-to-day % change for Close.
I must create a query that will join the table with itself in a way that every record contains also the data from the previous session (be aware, that I cannot use yesterday's date).
My idea is to do something like this:
select * from quotes t1
inner join quotes t2
on t1.symbol = t2.symbol and
t2.date = (select max(date) from quotes where symbol = t1.symbol and date < t1.date)
However I do not know if that's the correct/fastest way. What should I take into account when thinking about performance? (E.g. will putting UNIQUE index on a (Symbol, Date) pair improve performance?)
There will be around 100,000 new records every year in this table. I am using MS SQL Server 2008
One option is to use a recursive cte (if I'm understanding your requirements correctly):
WITH RNCTE AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY symbol ORDER BY date) rn
FROM quotes
),
CTE AS (
SELECT symbol, date, rn, cast(0 as decimal(10,2)) perc, closed
FROM RNCTE
WHERE rn = 1
UNION ALL
SELECT r.symbol, r.date, r.rn, cast(c.closed/r.closed as decimal(10,2)) perc, r.closed
FROM CTE c
JOIN RNCTE r on c.symbol = r.symbol AND c.rn+1 = r.rn
)
SELECT * FROM CTE
ORDER BY symbol, date
SQL Fiddle Demo
If you need a running total for each symbol to use as the percentage change, then easy enough to add an additional column for that amount -- wasn't completely sure what your intentions were, so the above just divides the current closed amount by the previous closed amount.
Something like this w'd work in SQLite:
SELECT ..
FROM quotes t1, quotes t2
WHERE t1.symbol = t2.symbol
AND t1.date < t2.date
GROUP BY t2.ID
HAVING t2.date = MIN(t2.date)
Given SQLite is a simplest of a kind, maybe in MSSQL this will also work with minimal changes.
Index on (symbol, date)
SELECT *
FROM quotes q_curr
CROSS APPLY (
SELECT TOP(1) *
FROM quotes
WHERE symbol = q_curr.symbol
AND date < q_curr.date
ORDER BY date DESC
) q_prev
You do something like this:
with OrderedQuotes as
(
select
row_number() over(order by Symbol, Date) RowNum,
ID,
Symbol,
Date,
Open,
High,
Low,
Close
from Quotes
)
select
a.Symbol,
a.Date,
a.Open,
a.High,
a.Low,
a.Close,
a.Date PrevDate,
a.Open PrevOpen,
a.High PrevHigh,
a.Low PrevLow,
a.Close PrevClose,
b.Close-a.Close/a.Close PctChange
from OrderedQuotes a
join OrderedQuotes b on a.Symbol = b.Symbol and a.RowNum = b.RowNum + 1
If you change the last join to a left join you get a row for the first date for each symbol, not sure if you need that.
You can use option with CTE and ROW_NUMBER ranking function
;WITH cte AS
(
SELECT symbol, date, [Open], [High], [Low], [Close],
ROW_NUMBER() OVER(PARTITION BY symbol ORDER BY date) AS Id
FROM quotes
)
SELECT c1.Id, c1.symbol, c1.date, c1.[Open], c1.[High], c1.[Low], c1.[Close],
ISNULL(c2.[Close] / c1.[Close], 0) AS perc
FROM cte c1 LEFT JOIN cte c2 ON c1.symbol = c2.symbol AND c1.Id = c2.Id + 1
ORDER BY c1.symbol, c1.date
For improving performance(avoiding sorting and RID Lookup) use this index
CREATE INDEX ix_symbol$date_quotes ON quotes(symbol, date) INCLUDE([Open], [High], [Low], [Close])
Simple demo on SQLFiddle
What you had is fine. I don't know if translating the sub-query into the join will help. However, you asked for it, so the way to do it might be to join the table to itself once more.
select *
from quotes t1
inner join quotes t2
on t1.symbol = t2.symbol and t1.date > t2.date
left outer join quotes t3
on t2.symbol = t3.symbol and t2.date > t3.date
where t3.date is null
You could do something like this:
DECLARE #Today DATETIME
SELECT #Today = DATEADD(DAY, 0, DATEDIFF(DAY, 0, CURRENT_TIMESTAMP))
;WITH today AS
(
SELECT Id ,
Symbol ,
Date ,
[OPEN] ,
High ,
LOW ,
[CLOSE],
DATEADD(DAY, -1, Date) AS yesterday
FROM quotes
WHERE date = #today
)
SELECT *
FROM today
LEFT JOIN quotes yesterday ON today.Symbol = yesterday.Symbol
AND today.yesterday = yesterday.Date
That way you limit your "today" results, if that's an option.
EDIT: The CTEs listed as other questions may work well, but I tend to be hesitant to use ROW_NUMBER when dealing with 100K rows or more. If the previous day may not always be yesterday, I tend to prefer to pull out the check for the previous day in its own query then use it for reference:
DECLARE #Today DATETIME, #PreviousDay DATETIME
SELECT #Today = DATEADD(DAY, 0, DATEDIFF(DAY, 0, CURRENT_TIMESTAMP));
SELECT #PreviousDay = MAX(Date) FROM quotes WHERE Date < #Today;
WITH today AS
(
SELECT Id ,
Symbol ,
Date ,
[OPEN] ,
High ,
LOW ,
[CLOSE]
FROM quotes
WHERE date = #today
)
SELECT *
FROM today
LEFT JOIN quotes AS previousday
ON today.Symbol = previousday.Symbol
AND previousday.Date = #PreviousDay