Our database has a bunch of records that have the same invoice number, but have different dates and different notes.
so you might have something like
invoice date notes
3622 1/3/2010 some notes
3622 9/12/2010 some different notes
3622 9/29/1010 Some more notes
4212 9/1/2009 notes
4212 10/10/2010 different notes
I need to select the distinct invoice numbers, dates and notes. for the record with the most recent date.
so my result should contain just
3622 9/29/1010 Some more notes
4212 10/10/2010 different notes
how is it possible to do this?
Thanks!
Use analytical functions :
WITH TT AS (
SELECT invoice, date, notes, RANK() OVER(PARTITION BY invoice ORDER BY date DESC) AS R
FROM table
)
SELECT invoice, date, notes
FROM TT
WHERE R = 1;
select invoice, date, notes
from table
inner join (select invoice, max(date) as date from table group by invoice) as max_date_table
on table.invoice = max_date_table.invoice and table.date = max_date_table.date
Try:
SELECT I.*
FROM MyInvoice AS I
INNER JOIN
(SELECT Invoice, MAX([Date]) AS MaxDate
FROM MyInvoice
GROUP BY Invoice
) AS M ON I.Date = M.MaxDate
AND I.Invoice = M.Invoice
Related
I'm trying to figure out how I can list out the most recent invoice date & invoice number for my customers. I have the basic structure as follows but can't figure out how to get this data. The two tables use the customer_id as the relationship
SELECT
c.customer_id
c.customer_name
( ? get most recent invoice number)
(?get most recent invoice date)
FROM
customer AS c
JOIN invoice as i on i.customer_id=c.customer_id
There are 2 common methods you can use. Common Table Expression (CTE) to rank all rows per customer_id order by invoice_date descending, and then you pick up date and number of the row ranked #1, or using CROSS APPLY to pick TOP 1 invoice per customer_id again, order by invoice_date descending.
Something like this
-- method #1 using CTE
;WITH cte AS (
SELECT
c.customer_id,
c.customer_name,
i.invoice_number,
i.invoce_date,
ROW_NUMBER() OVER (PARTITION BY c.Customer_id ORDER BY i.invoce_date DESC) rn
FROM
CUSTOMER c
INNER JOIN invoice i on i.customer_id=c.customer_id
)
SELECT cte.customer_id,
cte.customer_name,
cte.invoice_number,
cte.invoice_date
FROM cte
WHERE rm = 1
-- method #2 using CROSS APPLY
SELECT
c.customer_id,
c.customer_name,
ca.invoice_number,
ca.invoice_date
FROM
customer c
CROSS APPLY (
SELECT TOP 1 invoice_number, invoice_date
FROM invoice as i WHERE i.customer_id=c.customer_id
ORDER BY invoice_date DESC
) ca
Your requirement to list out the most recent invoice date & invoice number per each customer could be translated to: for each customer, retrieve the invoice record that there is not exists other invoice of the same customer which has more recent invoice date. The corresponding query should be:
SELECT
c.customer_id,
c.customer_name,
i.invoice_number,
i.invoice_date
FROM
customer c
INNER JOIN invoice i ON i.customer_id = c.customer_id
WHERE NOT EXISTS
(SELECT 1
FROM invoice i1
WHERE i1.invoice_number <> i.invoice_number
AND i1.customer_id = i.customer_id
AND i1.invoice_date > i.invoice_date)
I have 2 tables
sales table
weekly sales, store, date
store table
store, type, size
my sales table has multiple years, multiple stores and multiple types. I'm trying to get the avg sales by sqft for each store type per year. I have a sub query that shows the sales by sqft for each store but Im having trouble then rolling it up into my main query to get the avg by type
Anything jumps out with my final query?
SELECT
date_part('year', sales.date) AS year,
stores.type,
AVG(sales_by_sqft)
FROM
(SELECT
SUM((sales.weekly_sales)/stores.size) AS sales_by_sqft
FROM SALES
INNER JOIN stores ON sales.store = stores.store
GROUP BY sales.store) AS sq
FROM sales
INNER JOIN stores ON sales.store = stores.store
WHERE date_part('year', date) = 2012
GROUP BY year, stores.type;
getting a syntax error on the second FROM statement
I figured it out. AVG doesn't work on money. Once I changed that data type to integer, it all fell in place
SELECT
year,
type,
ROUND(AVG(sales_by_sqft),2)AS avg_sales_by_sqft
FROM
(SELECT
date_part('year', sales.date) AS year,
stores.type,
sales.store,
stores.size,
SUM(sales.weekly_sales) AS total_sales,
SUM(sales.weekly_sales)/ AVG(stores.size) AS sales_by_sqft
FROM sales
INNER JOIN stores ON sales.store = stores.store
GROUP BY year, stores.type, sales.store, stores.size) AS sq
GROUP BY 1,2
ORDER BY 1,3 DESC;
I have a Table that I am using to pull order details in SSRS that has when the price of a product number was changed. It has Data Changed and Updated Cost.
I am pairing up two different tables to create a report that is the cost of the package at the time of the order. Here is how I am pulling my data:
SELECT
WAREHOUSE.ActPkgCostHist.ItemNo AS [ActPkgCostHist ItemNo]
,WAREHOUSE.ActPkgCostHist.ActPkgCostDate
,WAREHOUSE.ActPkgCostHist.ActPkgCost
,ORDER.OrderHist.OrderNo
,ORDER.OrderHist.ItemNo AS [OrderHist ItemNo]
,ORDER.OrderHist.DispenseDt
FROM
WAREHOUSE.ActPkgCostHist
INNER JOIN ORDER.OrderHist
ON WAREHOUSE.ActPkgCostHist.ItemNo = ORDER.OrderHist.ItemNo
Catalog=ShippedOrders
ActPkgCostHist Table has What the cost of an Item was and what date the cost was changed.
OrderHist Table has the complete details of the order except the ActPkgCost at the time of the purchase.
I am attempting to create a table that Has order number, the date of the order and the package cost at the time of the order.
The ROW_NUMBER function is very useful for cases like this.
SELECT WAREHOUSE.ActPkgCostHist.ItemNo AS [ActPkgCostHist ItemNo]
,WAREHOUSE.ActPkgCostHist.ActPkgCostDate
,WAREHOUSE.ActPkgCostHist.ActPkgCost
,ORDER.OrderHist.OrderNo
,ORDER.OrderHist.ItemNo AS [OrderHist ItemNo]
,ORDER.OrderHist.DispenseDt
FROM ORDER.OrderHist
INNER JOIN (
SELECT ItemNo, ActPkgCostDate, ActPkgCost
, ROW_NUMBER() OVER (PARTITION BY ItemNo ORDER BY ActPkgCostDate DESC) as RN
FROM WAREHOUSE.ActPkgCostHist
--if there are future dated changes, limit ActPkgCostDate to be <= the current date
) ActPkgCostHist on ActPkgCostHist.ItemNo = OrderHist.ItemNo
WHERE RN = 1
What this subquery does is group the cost history by ItemNo. Then for each one, it ranks the changes by recency with the most recent change being 1. Then in the main query you filter it to just rows with a 1.
For each item in each order you have to find the latest cost date and use it when joining with the cost table
SELECT C.ItemNo AS [ActPkgCostHist ItemNo],
C.ActPkgCostDate,
C.ActPkgCost,
O.OrderNo,
O.ItemNo AS [OrderHist ItemNo],
O.DispenseDt
FROM WAREHOUSE.ActPkgCostHist AS C
-- JOIN order detail with cost table in order to define the cost date per item/order
INNER JOIN (SELECT Max(CH.ActPkgCostDate) AS ItemCostDate,
OH.OrderNo,
OH.ItemNo,
OH.DispenseDt
FROM WAREHOUSE.ActPkgCostHist AS CH
INNER JOIN ORDER.OrderHist AS OH
ON CH.ItemNo = OH.ItemNo
-- Get the latest cost date only from dates before order date
WHERE CH.ActPkgCostDate <= OH.DispenseDt
GROUP BY OH.OrderNo,
OH.ItemNo,
OH.DispenseDt) AS O
ON C.ItemNo = O.ItemNo
AND C.ActPkgCostDate = O.ItemCostDate
I have 2 tables which I need to compare to find missing data.
TableA: Definition table
Year, Week, cmp_code, [other columns]
TableB: Cash Receipts
Year, WeekNo, FranchiseID
TableA has all the possible combinations of ID week and year we should have data for. TableB is the data we actually have. I need to list out what we don't have yet, so the delta for B-A. How do I construct the query to find these missing values?
You can use NOT EXISTS
SELECT [Year], [Week], ID
FROM TableA AS a
WHERE NOT EXISTS
( SELECT 1
FROM TableB AS b
WHERE b.[Year] = a.[Year]
AND b.[Week] = a.[Week]
AND b.ID = a.ID
);
You can use theexceptset operator to return the difference between two sets:
SELECT [Year], [Week], cmp_code FROM TableA
EXCEPT
SELECT [Year], [WeekNo], FranchiseID FROM TableB
This will return the rows in TableA that doesn't have exact matches in TableB. The same result can be achieved using a correlatednot existsquery, or aleft join. Thenot existsshould perform best.
So far I have come up with the below:
WHERE (extract(month FROM orders)) =
(SELECT min(extract(month from orderdate))
FROM orders)
However, that will consequently return zero to many rows, and in my case, many, because many orders exist within that same earliest (minimum) month, i.e. 4th February, 9th February, 15th Feb, ...
I know that a WHERE clause can contain multiple columns, so why wouldn't the below work?
WHERE (extract(day FROM orderdate)), (extract(month FROM orderdate)) =
(SELECT min(extract(day from orderdate)), min(extract(month FROM orderdate))
FROM orders)
I simply get: SQL Error: ORA-00920: invalid relational operator
Any help would be great, thank you!
Sample data:
02-Feb-2012
14-Feb-2012
22-Dec-2012
09-Feb-2013
18-Jul-2013
01-Jan-2014
Output:
02-Feb-2012
14-Feb-2012
Desired output:
02-Feb-2012
I recreated your table and found out you just messed up the brackets a bit. The following works for me:
where
(extract(day from OrderDate),extract(month from OrderDate))
=
(select
min(extract(day from OrderDate)),
min(extract(month from OrderDate))
from orders
)
Use something like this:
with cte1 as (
select
extract(month from OrderDate) date_month,
extract(day from OrderDate) date_day,
OrderNo
from tablename
), cte2 as (
select min(date_month) min_date_month, min(date_day) min_date_day
from cte1
)
select cte1.*
from cte1
where (date_month, date_day) = (select min_date_month, min_date_day from cte2)
A common table expression enables you to restructure your data and then use this data to do your select. The first cte-block (cte1) selects the month and the day for each of your table rows. Cte2 then selects min(month) and min(date). The last select then combines both ctes to select all rows from cte1 that have the desired month and day.
There is probably a shorter solution to that, however I like common table expressions as they are almost all the time better to understand than the "optimal, shortest" query.
If that is really what you want, as bizarre as it seems, then as a different approach you could forget the extracts and the subquery against the table to get the minimums, and use an analytic approach instead:
select orderdate
from (
select o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
from orders o
)
where rn = 1;
ORDERDATE
---------
01-JAN-14
The row_number() effectively adds a pseudo-column to every row in your original table, based on the month and day in the order date. The rn values are unique, so there will be one row marked as 1, which will be from the earliest day in the earliest month. If you have multiple orders with the same day/month, say 01-Jan-2013 and 01-Jan-2014, then you'll still only get exactly one with rn = 1, but which is picked is indeterminate. You'd need to add further order by conditions to make it deterministic, but I have no idea what you might want.
That is done in the inner query; the outer query then filters so that only the records marked with rn = 1 is returned; so you get exactly one row back from the overall query.
This also avoids the situation where the earliest day number is not in the earliest month number - say if you only had 01-Jan-2014 and 02-Feb-2014; comparing the day and month separately would look for 01-Feb-2014, which doesn't exist.
SQL Fiddle (with Thomas Tschernich's anwer thrown in too, giving the same result for this data).
To join the result against your invoice table, you don't need to join to the orders table again - especially not with a cross join, which is skewing your results. You can do the join (at least) two ways:
SELECT
o.orderno,
to_char(o.orderdate, 'DD-MM-YYYY'),
i.invno
FROM
(
SELECT o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
FROM orders o
) o, invoices i
WHERE i.invno = o.invno
AND rn = 1;
Or:
SELECT
o.orderno,
to_char(o.orderdate, 'DD-MM-YYYY'),
i.invno
FROM
(
SELECT orderno, orderdate, invno
FROM
(
SELECT o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
FROM orders o
)
WHERE rn = 1
) o, invoices i
WHERE i.invno = o.invno;
The first looks like it does more work but the execution plans are the same.
SQL Fiddle with your pastebin-supplied query that gets two rows back, and these two that get one.