I have a table which contain _id, underSubheadId, wefDate, price.
Whenever a product is created or price is edited an entry is made in this table also.
What I want is if I enter a date, I get the latest price of all distinct UnderSubheadIds before the date (or on that date if no entry found)
_id underHeadId wefDate price
1 1 2016-11-01 5
2 2 2016-11-01 50
3 1 2016-11-25 500
4 3 2016-11-01 20
5 4 2016-11-11 30
6 5 2016-11-01 40
7 3 2016-11-20 25
8 5 2016-11-15 52
If I enter 2016-11-20 as date I should get
1 5
2 50
3 25
4 30
5 52
I have achieved the result using ROW NUMBER function in SQL SERVER, but I want this result in Sqlite which don't have such function.
Also if a date like 2016-10-25(which have no entries) is entered I want the price of the date which is first.
Like for 1 we will get price as 5 as the nearest and the 1st entry is 2016-11-01.
This is the query for SQL SERVER which is working fine. But I want it for Sqlite which don't have ROW_NUMBER function.
select underSubHeadId,price from(
select underSubHeadId,price, ROW_NUMBER() OVER (Partition By underSubHeadId order by wefDate desc) rn from rates
where wefDate<='2016-11-19') newTable
where newTable.rn=1
Thank You
This is a little tricky, but here is one way:
select t.*
from t
where t.wefDate = (select max(t2.wefDate)
from t t2
where t2.underSubHeadId = t.underSubHeadId and
t2.wefdate <= '2016-11-20'
);
select underHeadId, max(price)
from t
where wefDate <= "2016-11-20"
group by underHead;
Related
Right now I'm in the testing phase of this query so I'm only testing it on two Queries. I've gotten stuck on the final part where I want to left join everything (this will have to be extended to 12 separate queries). The problem is basically as the title suggests--I want to join 12 queries on the created Row_Num column using the WITH() statement, instead of creating 12 separate tables and saving them as table in a database.
WITH Jan_Table AS
(SELECT ROW_NUMBER() OVER (ORDER BY a.SALE_DATE) as Row_ID, a.SALE_DATE, sum(a.revenue) as Jan_Rev
FROM ba.SALE_TABLE a
WHERE a.SALE_DATE BETWEEN '2015-01-01' and '2015-01-31'
GROUP BY a.SALE_DATE)
SELECT ROW_NUMBER() OVER (ORDER BY a.SALE_DATE) as Row_ID, a.SALE_DATE, sum(a.revenue) as Jun_Rev, j.Jan_Rev
FROM ba.SALE_TABLE a
LEFT JOIN Jan_Table j
on "j.Row_ID" = a.Row_ID
WHERE a.SALE_DATE BETWEEN '2015-06-01' and '2015-06-30'
GROUP BY a.SALE_DATE
And then I get this error message:
ERROR: column "j.Row_ID" does not exist
I put in the "j.Row_ID" because the previous message was:
ERROR: column a.row_id does not exist Hint: Perhaps you meant to
reference the column "j.row_id".
Each query works individually without the JOIN and WITH functions. I have one for every month of the year and want to join 12 of these together eventually.
The output should be a single column with ROW_NUM and 12 Monthly Revenues columns. Each row should be a day of the month. I know not every month has 31 days. So, for example, Feb only has 28 days, meaning I'd want days 29, 30, and 31 as NULLs. The query above still has the dates--but I will remove the "SALE_DATE" column after I can just get these two queries to join.
My initially thought was just to create 12 tables but I think that'd be a really bad use of space and not the most logical solution to this problem if I were to extend this solution.
edit
Below are the separate outputs of the two qaruies above and the third table is what I'm trying to make. I can't give you the raw data. Everything above has been altered from the actual column names and purposes of the data that I'm using. And I don't know how to create a dataset--that's too above my head in SQL.
Jan_Table (first five lines)
Row_Num Date Jan_Rev
1 2015-01-01 20
2 2015-01-02 20
3 2015-01-03 20
4 2015-01-04 20
5 2015-01-05 20
Jun_Table (first five lines)
Row_Num Date Jun_Rev
1 2015-06-01 30
2 2015-06-02 30
3 2015-06-03 30
4 2015-06-04 30
5 2015-06-05 30
JOINED_TABLE (first five lines)
Row_Num Date Jun_Rev Date Jan_Rev
1 2015-06-01 30 2015-01-01 20
2 2015-06-02 30 2015-01-02 20
3 2015-06-03 30 2015-01-03 20
4 2015-06-04 30 2015-01-04 20
5 2015-06-05 30 2015-01-05 20
It seems like you can just use group by and conditional aggregation for your full query:
select day(sale_date),
max(case when month(sale_date) = 1 then sale_date end) as jan_date,
max(case when month(sale_date) = 1 then revenue end) as jan_revenue,
max(case when month(sale_date) = 2 then sale_date end) as feb_date,
max(case when month(sale_date) = 2 then revenue end) as feb_revenue,
. . .
from sale_table s
group by day(sale_date)
order by day(sale_date);
You haven't specified the database you are using. DAY() is a common function to get the day of the month; MONTH() is a common function to get the months of the year. However, those particular functions might be different in your database.
I have been searching the forum and found a single post that is a little smilair to my problem here: Calculate average for Top n combined with SQL Group By.
My situation is:
I have a table tblWEIGHT that contains: ID, Date, idPONR, Weight
I have a second table tblSALES that contains: ID, Date, Sales, idPONR
I have a third table tblPONR that contains: ID, PONR, idProduct
And a fouth table tblPRODUCT that contais: ID, Product
The linking:
tblWEIGHT.idPONR = tblPONR.ID
tblSALES.idPONR = tblPONR.ID
tblPONR.idProduct = tblPRODUCT.ID
The maintable of my query is tblSALES. I want to all my sales listed, with the moving average of the top5
weights of the PRODUCT where the date of the weight is less than the sales date, and the product is the same as the sold product. Its IMPORTANT that the result isn't grouped by the date. I need all the records of tblSALES.
i have gotten as far as to get the top 1 weight, but im not able to get the moving average instread.
The query that gest the top 1 is the following, and i am guessing that the query i need is going to look a lot like it.
SELECT tblSALES.ID, tblSALES.Dato, tblPONR.idPRODUCT,
(
SELECT top 1 Weight FROM tblWEIGHT INNER JOIN tblPONR ON tblWeight.idPONR = tblPONR.ID
WHERE tblPONR.idPRODUCT = idPRODUCT AND
SALES.Date > tblWEIGHT.Date
ORDER BY tblWEIGHT.Date desc
) AS LatestWeight
FROM tblSALES INNER JOIN VtblPONR ON tblSALES.idPONR = tblPONR.ID
this is not my exact query since im danish and i wouldnt make sense. I know im not supposed to use Date as a fieldname.
i imagine the filan query would be something like:
SELECT tblSALES.ID..... avg(SELECT TOP 5 weight .........)
but doing this i keep getting error at max 1 record can be returned by this subquery
Final Question.
How do i make a query that creates a moving average of the top 5 weights of my sold product, where the date of the weight is earlier than the date i sold the product?
EDIT Sampledata:
DATEFORMAT: dd/mm/yyyy
tblWEIGHT
ID Date idPONR Weight
1 01-01-2020 1 100
2 02-01-2020 2 200
3 03-01-2020 3 200
4 04-01-2020 3 400
5 05-01-2020 2 250
6 06-01-2020 1 150
7 07-01-2020 2 200
tblSALES
ID Date Sales(amt) idPONR
1 05-01-2020 30 1
2 06-01-2020 15 2
3 10-01-2020 20 3
tblPONR
ID PONR(production Number) idProduct
1 2521 1
2 1548 1
3 5484 2
tblPRODUCT
ID Product
1 Bricks
2 Tiles
Desired outcome read comments for AvgWeight
tblSALES.ID tblSALES.Date tblSales.Sales(amt) AvgWeigt
1 05-01-2020 30 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<05-01-2020)
2 06-01-2020 15 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<06-01-2020)
3 10-01-2020 20 123 -->avg(top 5 newest weight of idPONR 3 since thats the only idPONR with that product, and where tblWeight.Date<10-01-2020)
Consider:
Query1
SELECT tblWeight.ID AS WeightID, tblWeight.Date AS WtDate,
tblWeight.idPONR, tblPONR.PONR, tblPONR.idProduct, tblWeight.Weight, tblSales.SalesAmt,
tblSales.ID AS SalesID, tblSales.Date AS SalesDate
FROM (tblPONR INNER JOIN tblWeight ON tblPONR.ID = tblWeight.idPONR)
INNER JOIN tblSales ON tblPONR.ID = tblSales.idPONR;
Query2
SELECT * FROM Query1 WHERE WeightID IN (
SELECT TOP 5 WeightID FROM Query1 AS Dupe WHERE Dupe.idProduct = Query1.idProduct
AND Dupe.WtDate<Query1.SalesDate ORDER BY Dupe.WtDate);
Query3
SELECT Query2.SalesID, Query2.SalesDate, Query2.SalesAmt,
First(DAvg("Weight","Query2","idProduct=" & [idProduct] & " AND WtDate<#" & [SalesDate] & "#")) AS AvgWt
FROM Query2
GROUP BY Query2.SalesID, Query2.SalesDate, Query2.SalesAmt;
This is my table:
id user_id date balance
1 1 2016-05-10 10
2 1 2016-05-10 30
3 2 2017-04-24 5
4 2 2017-04-27 10
5 3 2017-11-10 40
I want to group the rows by user_id and sum the balance, but so that the sum is equal or less than 30. Moreover, I need to display the minimum date in the group. It should look like this:
id balance date_start
1-1 10 2016-05-10
1-2 30 2016-05-10
2-1 15 2017-04-24
Excuse for my language. Thanks.
You should be able to do so by using group by & having, here is an example of what may solve your case :
SELECT id, user_id, SUM(balance) as balance, data_start
FROM your_table
GROUP BY user_id
HAVING SUM(balance) >= 30
AND MIN(date_start)
This is a good way to do it with one query, but it is a complex query and you should be careful if using it on a very large tables.
I have the below table. I want to select 30 pieces of Product Code 011A from the table. Each row contains a number of pieces, in the column PCS. I want to select the 30 pieces in FIFO order based on date, and return the number of pieces selected from each row, so I'll need to know the primary key value for each row that has pieces selected from it. For example, from this data:
Key Product Code PCS Date
1 011A 10 2015-07-01
2 011B 20 2015-07-01
3 011C 20 2015-07-01
4 011A 12 2015-07-02
5 011A 40 2015-07-03
6 011D 60 2015-07-04
7 011A 20 2015-07-04
Selecting 30 pieces of product code "011A" should give an output table like:
Key Product Code PCS DATE
1 011A 10 2015-07-01
4 011A 12 2015-07-02
5 011A 8 2015-07-03
You can see that the total number of pieces is 30, and that the maximum number of pieces were selected from the rows with primary key 1 and 4, because they're the first dates. Only 8 were selected from row #5, because it's the next in date order, and only 8 is needed to reach 30 total. Row #7 wasn't needed, so it doesn't show up in the result.
How can I write a query to accomplish this?
In SQL Server 2012, you can use cumulative sum:
select t.*
from (select t.*,
sum(pcs) over (partition by productcode order by date) as cumepcs
from thetable t
where productcode = '011A'
) t
where cumepcs - pcs < 30;
Doing a cumulative sum in SQL Server 2008 is a bit more work. Here is one way:
select t.*
from (select t.*,
(select sum(t2.pcs)
from thetable t2
where t2.productcode = t.productcode and
t2.date <= t.date
) as cumepcs
from thetable t
where productcode = '011A'
) t
where cumepcs - pcs < 30;
EDIT:
If you want the allocated amounts from each bucket, you need to tweak the size of the last bucket. Change the select to:
select t.*,
(case when cume_pcs <= 30 then pcs
else 30 - (cumepcs - pcs)
end) as allocated_pcs
. . .
I am using a query in oracle which gives the below result (its a kind of month-wise transaction report):
Month Total Submitted Approved
--------------------------------------
DEC-14 2 2 0
APR-15 17 12 5
SEP-14 1 1 0
FEB-15 7 4 3
JUL-15 1 1 0
JAN-15 18 4 14
MAR-15 2 1 1
OCT-14 2 (null) (null)
JUN-15 136 91 45
JUN-14 1 1 0
MAY-15 179 63 116
I want to get the result in a sorted format, like JUN-14,SEP-14,OCT-14,DEC-14,JAN-15....so on. Thanks in advance.
order by date_column desc where date_column is the column that holds the date. This will order by the date_column in descending order.
Use asc to order in ascending order.
If month data type in character format you have to use
select * from table_name
order by to_char(to_date(month,'mm/yy'),'yy') asc,to_char(to_date(month,'mm/yy'),'mm') asc
if it is in date
select * from table_name
order by to_char(month,'yy') asc,to_char(month,'mm') asc
i assumed that you were using the following for displaying month column data.
TO_char(hiredate,'mon-yy')
if you used this then it will be easy for sorting them.
select your column list from table order by source_date_column asc;
for reference use the link