I have following query:
SELECT
*,
SUM(BalanceQty) OVER (PARTITION BY Item_Code ORDER BY [Date])
FROM
(SELECT
Date, Item_Code,
SUM(In_Quantity) AS In_Quantity,
SUM(Issue_Quantity) AS Issue_Quantity,
(SUM(In_Quantity) - SUM(issue_Quantity)) AS BalanceQty
FROM
(SELECT
tbl_add_product.Date as Date,
tbl_add_product.Item_Code,
tbl_add_product.In_Quantity,
0 as Issue_Quantity
FROM
tbl_add_product
WHERE
Item_Code = 'pen'
UNION ALL
SELECT
tbl_issue_product.Date as Date,
tbl_issue_product.Item_Code,
0 as In_Quantity,
Issue_Quantity
FROM
tbl_issue_product
WHERE
Item_Code = 'pen') X
GROUP BY
Item_Code, Date) o
It is working fine in SQL Server 2012 but it is causing an error in SQL server 2008. Please suggest solution to it.
if you want a solution which can work on both then try this :
;WITH cte
AS (SELECT Date,
Item_Code,
Sum(In_Quantity) AS In_Quantity,
Sum(Issue_Quantity) AS Issue_Quantity,
( Sum(In_Quantity) - Sum(issue_Quantity) ) AS BalanceQty
FROM (SELECT tbl_add_product.Date AS Date,
tbl_add_product.Item_Code,
tbl_add_product.In_Quantity,
0 AS Issue_Quantity
FROM tbl_add_product
WHERE Item_Code = 'pen'
UNION ALL
SELECT tbl_issue_product.Date AS Date,
tbl_issue_product.Item_Code,
0 AS In_Quantity,
Issue_Quantity
FROM tbl_issue_product
WHERE Item_Code = 'pen') X
GROUP BY Item_Code,Date)
SELECT *,(select SUM(BalanceQty) from cte c2 where c2.Date <=c1.Date)
FROM cte c1
you need to change the database compatibility mode in SQL SERVER 2008, Right click on database select properties, click on "Options" change "Compatibility Level:
You can do this with outer apply or a correlated subquery:
with t as (<your big subquery here>)
select t.*
(select sum(BalanceQty)
from t t2
where t2.Item_Code = t.Item_Code and t2.[Date] <= t.[Date]
) as RunningBalance
from t;
EDIT:
You can add the Item_Code = 'pen' to the outer query, if you want to limit the results to one item.
Related
I'm trying to find the percent change using row number with PostgreSQL but I'm running into an error where my "percent_change" column shows 0.
Here is what I have as my code.
WITH CTE AS (
SELECT date, sales, ROW_NUMBER() OVER (ORDER by date) AS rn
FROM sales_2019)
SELECT c1.date, c1.sales,
CAST(COALESCE (((c1.sales - c2.sales) * 1.0 / c2.sales) * 100, 0) AS INT) AS percent_change
FROM CTE AS c1
LEFT JOIN CTE AS c2
ON c1.date = c2.date AND c1.rn = c2.rn + 1
Here is my SQL table in case it's needed. Thank you in advance, I greatly appreciate it.
You can use LAG() for your requirement:
select
date,
sales,
round(coalesce((((sales-(lag(sales) over (order by date)))*1.0)/(lag(sales) over (order by date)))*100,0),2)
from sales_2019
or you can try with WITH clause
with cte as ( select
date,
sales,
coalesce(lag(sales) over (order by date),0) as previous_month
from sales_2019
)
select
date,
sales,
round( coalesce( (sales-previous_month)*1.0/nullif(previous_month,0),0 )*100,2)
from cte
DEMO
EDIT as per requirement in comment
with cte as ( select
date_,
sales,
ROW_NUMBER() OVER (ORDER by date_) AS rn1,
ROW_NUMBER() OVER (ORDER by date_)-1 AS rn2
from sales_2019
)
select t1.date_,
t1.sales,
round( coalesce( (t1.sales-t2.sales)*1.0/nullif(t2.sales,0),0 )*100,2)
from cte t1 left join cte t2 on t1.rn2=t2.rn1
DEMO
I'm trying to return the number of unique users that converted over time.
So I have the following query:
WITH CTE
As
(
SELECT '2020-04-01' as date,'userA' as user,1 as goals Union all
SELECT '2020-04-01','userB',0 Union all
SELECT '2020-04-01','userC',0 Union all
SELECT '2020-04-03','userA',1 Union all
SELECT '2020-04-05','userC',1 Union all
SELECT '2020-04-06','userC',0 Union all
SELECT '2020-04-06','userB',0
)
select
date,
COUNT(DISTINCT
IF
(goals >= 1,
user,
NULL)) AS cad_converters
from CTE
group by date
I'm trying to count distinct user but I need to find a way to apply the distinct count to the whole date. I probably need to do something like a cumulative some...
expected result would be something like this
date, goals, total_unique_converted_users
'2020-04-01',1,1
'2020-04-01',0,1
'2020-04-01',0,1
'2020-04-03',1,2
'2020-04-05',1,2
'2020-04-06',0,2
'2020-04-06',0,2
Below is for BigQuery Standard SQL
#standardSQL
SELECT t.date, t.goals, total_unique_converted_users
FROM `project.dataset.table` t
LEFT JOIN (
SELECT a.date,
COUNT(DISTINCT IF(b.goals >= 1, b.user, NULL)) AS total_unique_converted_users
FROM `project.dataset.table` a
CROSS JOIN `project.dataset.table` b
WHERE a.date >= b.date
GROUP BY a.date
)
USING(date)
I would approach this by tagging when the first goal is scored for each name. Then simply do a cumulative sum:
select cte.* except (seqnum), countif(seqnum = 1) over (order by date)
from (select cte.*,
(case when goals = 1 then row_number() over (partition by user, goals order by date) end) as seqnum
from cte
) cte;
I realize this can be expressed without the case in the subquery:
select cte.* except (seqnum), countif(seqnum = 1 and goals = 1) over (order by date)
from (select cte.*,
row_number() over (partition by user, goals order by date) as seqnum
from cte
) cte;
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 have some prices for the month of January.
Date,Price
1,100
2,100
3,115
4,120
5,120
6,100
7,100
8,120
9,120
10,120
Now, the o/p I need is a non-overlapping date range for each price.
price,from,To
100,1,2
115,3,3
120,4,5
100,6,7
120,8,10
I need to do this using SQL only.
For now, if I simply group by and take min and max dates, I get the below, which is an overlapping range:
price,from,to
100,1,7
115,3,3
120,4,10
This is a gaps-and-islands problem. The simplest solution is the difference of row numbers:
select price, min(date), max(date)
from (select t.*,
row_number() over (order by date) as seqnum,
row_number() over (partition by price, order by date) as seqnum2
from t
) t
group by price, (seqnum - seqnum2)
order by min(date);
Why this works is a little hard to explain. But if you look at the results of the subquery, you will see how the adjacent rows are identified by the difference in the two values.
SELECT Lag.price,Lag.[date] AS [From], MIN(Lead.[date]-Lag.[date])+Lag.[date] AS [to]
FROM
(
SELECT [date],[Price]
FROM
(
SELECT [date],[Price],LAG(Price) OVER (ORDER BY DATE,Price) AS LagID FROM #table1 A
)B
WHERE CASE WHEN Price <> ISNULL(LagID,1) THEN 1 ELSE 0 END = 1
)Lag
JOIN
(
SELECT [date],[Price]
FROM
(
SELECT [date],Price,LEAD(Price) OVER (ORDER BY DATE,Price) AS LeadID FROM [#table1] A
)B
WHERE CASE WHEN Price <> ISNULL(LeadID,1) THEN 1 ELSE 0 END = 1
)Lead
ON Lag.[Price] = Lead.[Price]
WHERE Lead.[date]-Lag.[date] >= 0
GROUP BY Lag.[date],Lag.[price]
ORDER BY Lag.[date]
Another method using ROWS UNBOUNDED PRECEDING
SELECT price, MIN([date]) AS [from], [end_date] AS [To]
FROM
(
SELECT *, MIN([abc]) OVER (ORDER BY DATE DESC ROWS UNBOUNDED PRECEDING ) end_date
FROM
(
SELECT *, CASE WHEN price = next_price THEN NULL ELSE DATE END AS abc
FROM
(
SELECT a.* , b.[date] AS next_date, b.price AS next_price
FROM #table1 a
LEFT JOIN #table1 b
ON a.[date] = b.[date]-1
)AA
)BB
)CC
GROUP BY price, end_date
I have a date column Order_date and I am looking for ways to calculate the date difference between customer last order date and his recent previous ( previous form last) order_date ....
Example
Customer : 1, 2 , 1 , 1
Order_date: 01/02/2007, 02/01/2015, 06/02/2014, 04/02/2015
As you can see customer # 1 has three orders.
I want to know the date difference between his recent order date (04/02/2015) and his recent previous (06/02/2014).
For SQL Server 2012 & 2014 you could use LAG with a DATEDIFF to see the number of days between them.
For older versions, a CTE would probably be your best bet:
;WITH CTE AS
(
SELECT CustomerID,
Order_Date,
rn = ROW_NUMBER() OVER (PARTITION BY CustomerID ORDER BY Order_Date DESC)
)
SELECT c1.CustomerID,
DATEDIFF(d, c1.Order_Date, c2.Order_Date)
FROM CTE c1
INNER JOIN CTE c2 ON c2.rn = c1.rn + 1
In SQL Server 2012+, you can use lag() to get the difference between any two dates:
select t.*,
datediff(day, lag(order_date) over (partition by customer order by order_date),
order_date) as days_dff
from table t;
If you have an older version, you can do something similar with correlated subqueries or outer apply.
EDIT:
If you just want the difference between the two most recent dates, use conditional aggregation instead:
select customer,
datediff(day, max(case when seqnum = 2 then order_date end),
max(case when seqnum = 1 then order_date end)
) as MostRecentDiff
from (select t.*,
row_number() over (partition by customer order by order_date desc) as seqnum
from table t
) t
group by customer;
If you're using SQL Server 2008 or later, you can try CROSS APPLY.
SELECT [customers].[customer_id], DATEDIFF(DAY, MIN([recent_orders].[order_date]), MAX([recent_orders].[order_date])) AS [elapsed]
FROM [customers]
CROSS APPLY (
SELECT TOP 2 [order_date]
FROM [orders]
WHERE ([orders].[customer_id] = [customers].[customer_id])
) [recent_orders]
GROUP BY [customers].[customer_id]
SELECT DATEDIFF(DAY, Y.PrevLastOrderDate, Y.LastOrderDate) AS PreviousDays
FROM
(
SELECT X.LastOrderDate
, (SELECT MAX(OrderDate) FROM dbo.Orders SO WHERE SO.CustomerID=1 AND SO.OrderDate < X.LastOrderDate) AS PrevLastOrderDate
FROM
(
select MAX(OrderDate) AS LastOrderDate
FROM dbo.Orders O
WHERE O.CustomerID=1
)X
)Y
drop table #Invoices
create table #Invoices ( OrderId int , OrderDate datetime )
insert into #Invoices (OrderId , OrderDate )
select 101, '01/01/2001' UNION ALL Select 202, '02/02/2002' UNION ALL Select 303, '03/03/2003'
UNION ALL Select 808, '08/08/2008' UNION ALL Select 909, '09/09/2009'
;
WITH
MyCTE /* http://technet.microsoft.com/en-us/library/ms175972.aspx */
( OrderId,OrderDate,ROWID) AS
(
SELECT
OrderId,OrderDate
, ROW_NUMBER() OVER ( ORDER BY OrderDate ) as ROWID
FROM
#Invoices inv
)
SELECT
OrderId,OrderDate
,(Select Max(OrderDate) from MyCTE innerAlias where innerAlias.ROWID = (outerAlias.ROWID-1) ) as PreviousOrderDate
,
[MyDiff] =
CASE
WHEN (Select Max(OrderDate) from MyCTE innerAlias where innerAlias.ROWID = (outerAlias.ROWID-1) ) iS NULL then 0
ELSE DATEDIFF (mm, OrderDate , (Select Max(OrderDate) from MyCTE innerAlias where innerAlias.ROWID = (outerAlias.ROWID-1) ) )
END
, ROWIDMINUSONE = (ROWID-1)
, ROWID as ROWID_SHOWN_FOR_KICKS , OrderDate as OrderDateASecondTimeForConvenience
FROM
MyCTE outerAlias
ORDER BY outerAlias.OrderDate Desc , OrderId