I have a table which looks like this.
ID | Block | Flats | Ammount | Balance |
1 | 1 | GF-1 | 1000 | 500 |
2 | 1 | GF-2 | 1000 | 500 |
3 | 2 | GF-1 | 1000 | 500 |
4 | 2 | GF-2 | 1000 | 1000 |
5 | 2 | GF-2 | 1000 | 0 |
I want to execute sum query on this. I have tried
Select distinct A.Block,(Select Sum(Ammount) from t1 where block = A.block),(select Sum(Balance) from t1 where block = A.block) from t1 A
This query is working fine but its summing balance to 2500 but as ID 4 & 5 are of same Flat so I want it to sum latest of balance which should be 1500. I have tried to put a select statement inside sum function but that doesn't work . So how can I achieve this?
You can select the most recent id for each block/flats combo first (using row_number()) and then aggregate:
Select t1.Block, sum(amount)
from (select t1.*,
row_number() over (partition by block, flats order by id desc) as seqnum
from t1
) t1
where seqnum = 1
group by t1.Block;
You can use below query
Select A.Block, Sum(A.Ammount), Sum(A.Balance)
from t1 A group by A.Flats order by A.ID;
Order by clause is used to sort with respect to ID
I think you just want to SUM() group by block like
select Block, sum(amount) totalamount,
sum(case when balance <> 0 then balance end) totalbalance
from t1
group by Block;
You can use a SUM(DISTINCT ...)
select Block, sum(DISTINCT amount) totalamount,
sum(DISTINCT case when balance <> 0 then balance end) totalbalance
from t1
group by Block;
Related
I have the following data set:
| EMAIL | SIGNUP_DATE |
| A#ABC.COM | 1/1/2021 |
| B#ABC.COM | 1/2/2021 |
| C#ABC.COM | 1/3/2021 |
In order to find the running total of email signups as of a certain day, I ran the following sql query:
select
signup_date,
count(email) OVER (order by signup_date ASC) as running_total_signups
I got the following results:
| SIGNUP_DATE | RUNNING_TOTAL_SIGNUPS |
| 1/1/21 | 1 |
| 1/2/21 | 2 |
| 1/3/21 | 3 |
However for my next step, I want to be able to see not just the running total signups, but the actual signup names themselves. Therefore I want to run the same window function (count(email) OVER (order by signup_date ASC)) but instead of a count(email) just a select distinct email. This would hopefully result in the following output:
| SIGNUP_DATE | RUNNING_TOTAL_SIGNUPS |
| 1/1/21 | a#abc.com |
| 1/2/21 | a#abc.com |
| 1/2/21 | b#abc.com |
| 1/3/21 | a#abc.com |
| 1/3/21 | b#abc.com |
| 1/3/21 | c#abc.com |
How would I do this? I'm getting an error on this code:
select
signup_date,
distinct email OVER (order by signup_date ASC) as running_total_signups
One way would be to cross-join the results and filter the joined table having a total <= to the running total:
with counts as (
select *,
Count(*) over (order by SIGNUP_DATE asc) as tot
from t
)
select c1.EMAIL, c1.SIGNUP_DATE
from counts c1
cross join counts c2
where c2.tot <= c1.tot
I want to run the same window function (count(email) OVER (order by
signup_date ASC)) but instead of a count(email) just a select distinct
email
Why do you want COUNT() window function?
It has nothing to do with with your reqirement.
All you need is a simple self join:
SELECT t1.SIGNUP_DATE, t2.EMAIL
FROM tablename t1 INNER JOIN tablename t2
ON t2.SIGNUP_DATE <= t1.SIGNUP_DATE
ORDER BY t1.SIGNUP_DATE, t2.EMAIL;
which will work for your sample data, but just in case there are more than 1 rows for each day in your table you should use:
SELECT t1.SIGNUP_DATE, t2.EMAIL
FROM (SELECT DISTINCT SIGNUP_DATE FROM tablename) t1 INNER JOIN tablename t2
ON t2.SIGNUP_DATE <= t1.SIGNUP_DATE
ORDER BY t1.SIGNUP_DATE, t2.EMAIL;
See the demo.
It's actually slightly simpler than Stu proposed:
select
x2.signup_date,
x1.email
from
signups x1
INNER JOIN signups x2 ON x1.signup_date <= x2.signup_date
order by signup_date
If you join the table to itself but for any date that is less than or equal to, it causes a half cartesian explosion. The lowest dated row matches with only itself. The next one matches with itself and the earlier one, so one of the table aliases has its data repeated.. This continues adding more rows to the explosion as the dates increase:
In this resultset we can see we want the emails from x1, and the dates from x2
I have a table with user retail transactions. It includes sales and cancels. If Qty is positive - it sells, if negative - cancels. I want to attach cancels to the most appropriate sell. So, I have tables likes that:
| CustomerId | StockId | Qty | Date |
|--------------+-----------+-------+------------|
| 1 | 100 | 50 | 2020-01-01 |
| 1 | 100 | -10 | 2020-01-10 |
| 1 | 100 | 60 | 2020-02-10 |
| 1 | 100 | -20 | 2020-02-10 |
| 1 | 100 | 200 | 2020-03-01 |
| 1 | 100 | 10 | 2020-03-05 |
| 1 | 100 | -90 | 2020-03-10 |
User with ID 1 has the following actions: buy 50 -> return 10 -> buy 60 -> return 20 -> buy 200 -> buy 10 - return 90. For each cancel row (with negative Qty) I find the previous row (by Date) with positive Qty and greater than cancel Qty.
So I need to create BigQuery queries to create table likes this:
| CustomerId | StockId | Qty | Date | CancelQty |
|--------------+-----------+-------+------------+-------------|
| 1 | 100 | 50 | 2020-01-01 | -10 |
| 1 | 100 | 60 | 2020-02-10 | -20 |
| 1 | 100 | 200 | 2020-03-01 | -90 |
| 1 | 100 | 10 | 2020-03-05 | 0 |
Does anybody help me with these queries? I have created one candidate query (split cancel and sales, join them, and do some staff for removing), but it works incorrectly in the above case.
I use BigQuery, so any BQ SQL features could be applied.
Any ideas will be helpful.
You can use the following query.
;WITH result AS (
select t1.*,t2.Qty as cQty,t2.Date as Date_t2 from
(select *,ROW_NUMBER() OVER (ORDER BY qty DESC) AS [ROW NUMBER] from Test) t1
join
(select *,ROW_NUMBER() OVER (ORDER BY qty) AS [ROW NUMBER] from Test) t2
on t1.[ROW NUMBER] = t2.[ROW NUMBER]
)
select CustomerId,StockId,Qty,Date,ISNULL(cQty, 0) As CancelQty,Date_t2
from (select CustomerId,StockId,Qty,Date,case
when cQty < 0 then cQty
else NULL
end AS cQty,
case
when cQty < 0 then Date_t2
else NULL
end AS Date_t2 from result) t
where qty > 0
order by cQty desc
result: https://dbfiddle.uk
You can do this as a gaps-and-islands problem. Basically, add a grouping column to the rows based on a cumulative reverse count of negative values. Then within each group, choose the first row where the sum is positive. So:
select t.* (except cancelqty, grp),
(case when min(case when cancelqty + qty >= 0 then date end) over (partition by customerid grp) = date
then cancelqty
else 0
end) as cancelqty
from (select t.*,
min(cancelqty) over (partition by customerid, grp) as cancelqty
from (select t.*,
countif(qty < 0) over (partition by customerid order by date desc) as grp
from transactions t
) t
from t
) t;
Note: This works for the data you have provided. However, there may be complicated scenarios where this does not work. In fact, I don't think there is a simple optimal solution assuming that the returns are not connected to the original sales. I would suggest that you fix the data model so you record where the returns come from.
The below query seems to satisfy the conditions and the output mentioned.The solution is based on mapping the base table (t) and having the corresponding canceled qty row alongside from same table(t1)
First, a self join based on the customer and StockId is done since they need to correspond to the same customer and product.
Additionally, we are bringing in the canceled transactions t1 that happened after the base row in table t t.Dt<=t1.Dt and to ensure this is a negative qty t1.Qty<0 clause is added
Further we cannot attribute the canceled qty if they are less than the Original Qty. Therefore I am checking if the positive is greater than the canceled qty. This is done by adding a '-' sign to the cancel qty so that they can be compared easily. -(t1.Qty)<=t.Qty
After the Join, we are interested only in the positive qty, so adding a where clause to filter the other rows from the base table t with canceled quantities t.Qty>0.
Now we have the table joined to every other canceled qty row which is less than the transaction date. For example, the Qty 50 can have all the canceled qty mapped to it but we are interested only in the immediate one came after. So we first group all the base quantity values and then choose the date of the canceled Qty that came in first in the Having clause condition HAVING IFNULL(t1.dt, '0')=MIN(IFNULL(t1.dt, '0'))
Finally we get the rows we need and we can exclude the last column if required using an outer select query
SELECT t.CustomerId,t.StockId,t.Qty,t.Dt,IFNULL(t1.Qty, 0) CancelQty
,t1.dt dt_t1
FROM tbl t
LEFT JOIN tbl t1 ON t.CustomerId=t1.CustomerId AND
t.StockId=t1.StockId
AND t.Dt<=t1.Dt AND t1.Qty<0 AND -(t1.Qty)<=t.Qty
WHERE t.Qty>0
GROUP BY 1,2,3,4
HAVING IFNULL(t1.dt, '0')=MIN(IFNULL(t1.dt, '0'))
ORDER BY 1,2,4,3
fiddle
Consider below approach
with sales as (
select * from `project.dataset.table` where Qty > 0
), cancels as (
select * from `project.dataset.table` where Qty < 0
)
select any_value(s).*,
ifnull(array_agg(c.Qty order by c.Date limit 1)[offset(0)], 0) as CancelQty
from sales s
left join cancels c
on s.CustomerId = c.CustomerId
and s.StockId = c.StockId
and s.Date <= c.Date
and s.Qty > abs(c.Qty)
group by format('%t', s)
if applied to sample data in your question - output is
I am working on a query in database. Say i have a patient which travelled to 3 hospitals. Now i want to add the cost of his journey but want to show it only at his first journey ,the total cost.
file right now is like
Patient Hospital1 cost
A 1 200
A 2 400
A 3 100
B 1 200
I want the output as
Patient Hosptial Cost
A 1 700
A 2
A 3
B 1 200
Thanks
You can use window functions:
select t.*,
(case when row_number() over (partition by patient order by hospital1) = 1
then sum(cost) over (partition by patient)
end) as total_cost
from t
order by patient, hospital1;
CREATE TABLE MyTable(Patient varchar(20),Hospital int, Cost int)
INSERT INTO MyTable(Patient,Hospital,Cost) VALUES ('A',1,200),('A',2,400),
('A',3,100),
('B',1,200)
WITH CTE AS (SELECT Patient,SUM(Cost) AS Cost FROM MyTable
GROUP BY Patient)
SELECT M.Patient,M.Hospital,
CASE WHEN ROW_NUMBER() OVER (PARTITION BY M.Patient ORDER BY M.Hospital)=1 THEN CAST(C.Cost AS VARCHAR(255))
ELSE '' END AS Cost FROM CTE AS C
INNER JOIN Mytable AS M ON C.Patient=M.Patient
Patient | Hospital | Cost
:------ | -------: | :---
A | 1 | 700
A | 2 |
A | 3 |
B | 1 | 200
db<>fiddle here
If you had the records in a table, called PatientVisits, with the following data:
You could use this query:
SELECT PV.Patient, PV.Hospital, PVGroup.TotalCost
FROM PatientVisits PV
LEFT JOIN (
SELECT Patient, MIN(Hospital) as FirstVisit, SUM(Cost) as TotalCost
FROM PatientVisits
GROUP BY Patient) PVGroup ON
PV.Patient = PVGroup.Patient AND
PV.Hospital = PVGroup.FirstVisit
ORDER BY PV.Patient, PV.Hospital
The results would be:
I have a table called "payments" where I store all the payments of my costumers and I need to do a select to calculate the non-payment rate in a given month.
The costumers can have multiples payments in that month, but I should count him only once: 1 if any of the payments is done and 0 if any of the payment was made.
Example:
+----+------------+--------+
| ID | DATEDUE | AMOUNT |
+----+------------+--------+
| 1 | 2016-11-01 | 0 |
| 1 | 2016-11-15 | 20.00 |
| 2 | 2016-11-10 | 0 |
+----+------------+--------+
The result I expect is from the rate of november:
+----+------------+--------+
| ID | DATEDUE | AMOUNT |
+----+------------+--------+
| 1 | 2016-11-15 | 20.00 |
| 2 | 2016-11-10 | 0 |
+----+------------+--------+
So the rate will be 50%.
But if the select is:
SELECT * FROM payment WHERE DATEDUE BETWEEN '2016-11-01' AND '2016-11-30'
It will return me 3 rows and the rate will be 66%, witch is wrong. Ideas?
PS: This is a simpler example of the real table. The real query have a lot of columns, subselects, etc.
It sounds like you need to partition your results per customer.
SELECT TOP 1 WITH TIES
ID,
DATEDUE,
AMOUNT
ORDER BY ROW_NUMBER() OVER (PARTITION BY ID ORDER BY AMOUNT DESC)
WHERE DATEDUE BETWEEN '2016-11-01' AND '2016-11-30'
PS: The BETWEEN operator is frowned upon by some people. For clarity it might be better to avoid it:
What do BETWEEN and the devil have in common?
Try this
SELECT
id
, SUM(AMOUNT) AS AMOUNT
FROM
Payment
GROUP BY
id;
This might help if you want other columns.
WITH cte (
SELECT
id
, ROW_NUMBER() OVER (PARTITION BY ID ORDER BY AMOUNT DESC ) AS RowNum
-- other row
)
SELECT *
FROM
cte
WHERE
RowNum = 1;
To calculate the rate, you can use explicit division:
select 1 - count(distinct case when amount > 0 then id end) / count(*)
from payment
where . . .;
Or, in a way that is perhaps easier to follow:
select avg(flag * 1.0)
from (select id, (case when max(amount) > 0 then 0 else 1 end) as flag
from payment
where . . .
group by id
) i
Having Table1
id | productname | store | price
-----------------------------------
1 | name a | store 1 | 4
2 | name a | store 2 | 3
3 | name b | store 3 | 6
4 | name a | store 3 | 4
5 | name b | store 1 | 7
6 | name a | store 4 | 5
7 | name c | store 3 | 2
8 | name b | store 6 | 5
9 | name c | store 2 | 1
I need to get all columns but only the rows with the
lowest price.
Result needed:
id | productname | store | price
-----------------------------------
2 | name a | store 2 | 3
8 | name b | store 6 | 5
9 | name c | store 2 | 1
My best try is:
SELECT ProductName, MIN(Price) AS minPrice
FROM Table1
GROUP BY ProductName
But then I need the ID and STORE for each row.
Try this
select p.* from Table1 as p inner join
(SELECT ProductName, MIN(Price) AS minPrice FROM Table1 GROUP BY ProductName) t
on p.productname = t.ProductName and p.price = t.minPrice
Select ID,ProductName,minPrice
from
(
SELECT ProductName, MIN(Price) AS minPrice
FROM Table1
GROUP BY ProductName
) t
join Table1 t1 on t.ProductName = t1.ProductName
You didn't mention your SQL dialect, but most DBMSes support Standard SQL's "Windowed Aggregate Functions":
select *
from
( select t.*,
RANK() OVER (PARTITION BY ProductName ORDER BY Price) as rnk
from table1 as t
) as dt
where rnk = 1
If multiple stores got the same lowest price all of them will be returned. If you want only a single shop you have to switch to ROW_NUMBER instead of RANK or add column(s) to the ORDER BY.
I think this query should do:
select min(t.id) id
, t.productname
, t.price
from table1 t
join
( select min(price) min_price
, productname
from table1
group
by productname
) v
on v.productname = t.productname
and v.price = t.min_price
group
by t.productname
, t.price
It determines the lowest price per product and fetches every line in the base table (t). This avoids duplicates by grouping on the productname and selecting the lowest id.
This should work for you:
SELECT * FROM `Table1` AS `t1`
WHERE (
SELECT count(*) FROM `Table1` AS `t2` WHERE `t1`.`productName` = `t2`.`productName` AND `t2`.`price` < `t1`.`price`) < 1
Check SqlFiddle
But if you have same products with same minimum price in two stores, you will get both of them in result output