I have two tables. One is NAV where product daily new price is updated. Second is TDK table where item wise stock is available.
Now I want to get a summery report as per buyer name where all product wise total will come and from table one latest price will come.
I have tried below query...
SELECT dbo.TDK.buyer, dbo.NAV.Product_Name, sum(dbo.TDK.TD_UNITS) as Units, sum(dbo.TDK.TD_AMT) as 'Amount',dbo.NAV.NAValue
FROM dbo.TDK INNER JOIN
dbo.NAV
ON dbo.TDK.Products = dbo.NAV.Product_Name
group by dbo.TDK.buyer, dbo.NAV.Product_Name, dbo.NAV.NAValue
Imnportant: Common columns in both tables...
Table one NAV has column as Products
Table two TDK has column as Product_Name
If I have NAValue 4 records for one product then this query shows 4 lines with same total.
What I need??
I want this query to show only one line with latest NAValue price.
I want display one more line with Units*NAValue (latest) as "Latest Market Value".
Please guide.
What field contains the quote date? I am assuming you have a DATIME field, quoteDate, in dbo.NAV table and my other assumption is that you only store the Date part (i.e. mid-night, time = 00:00:00).
SELECT
t.buyer,
n.Product_Name,
sum(t.TD_UNITS) as Units,
sum(t.TD_AMT) as 'Amount',
n.NAValue
FROM dbo.TDK t
INNER JOIN dbo.NAV n
ON t.Products = n.Product_Name
AND n.quoteDate > getdate()-2
group by t.buyer, n.Product_Name, n.NAValue, n.QuoteDate
GetDate() will give you the current date and time. Subtracting 2 would get it before yesterday but after the day before yesterday.
Also, add n.quoteDate in your select and group by. Even though you don't need it, in case that one day you have a day of bad data with double record in NAV table, one with midnight time and another with 6 PM time.
Your code looks like SQL Server. I think you just want APPLY:
SELECT t.buyer, n.Product_Name, t.TD_UNITS as Units, t.TD_AMT as Amount, n.NAValue
FROM dbo.TDK t CROSS APPLY
(SELECT TOP (1) n.*
FROM dbo.NAV n
WHERE t.Products = n.Product_Name
ORDER BY ?? DESC -- however you define "latest"
) n;
Related
The problem statement is: I have a table (order_t) which has customer feedback (one column) and quarter number (as another column).
Using a CTE, I need to calculate the percentage of number of customer feedback in each category as well as the total number of customer feedback in each quarter.
After this happens, I need the percentage of different types of customer feedback (like good, bad, ok, very good, very bad) but using CTE.
How can I solve this statement?
I try to solve customer feedback as
WITH total_feedback AS
(
SELECT *
COUNT(CUSTOMER_FEEDBACK), QUARTER NUMBER
FROM
table1
GROUP BY
2
)
But I'm unable to calculate the first half portion, i.e. percentage of different types of customer feedback in each quarter using CTE.
How can I do that?
Find the file of the data
What you could do, and I'll keep the example as close to the code you provided as possible, is the following - using 2 CTE's:
WITH total_feedback AS (
SELECT COUNT(CUSTOMER_FEEDBACK) AS total_feedback, QUARTER_NUMBER
FROM table1
GROUP BY 2
),
category_feedback AS (
SELECT COUNT(CUSTOMER_FEEDBACK) AS feedback_count, CUSTOMER_FEEDBACK, QUARTER_NUMBER
FROM table1
GROUP BY 2, 3
)
SELECT
category_feedback.CUSTOMER_FEEDBACK,
category_feedback.QUARTER_NUMBER,
(feedback_count / total_feedback.total_feedback) * 100 AS feedback_percentage
FROM category_feedback
INNER JOIN total_feedback
ON category_feedback.QUARTER_NUMBER = total_feedback.QUARTER_NUMBER
My dataset is about sales, each line corresponds to an invoice. It is possible to have 2 registers in the same day for the same customer, if he had bought twice in that day.
As you can see in the image below, the blue square shows us that customer 355122 (id_cliente = customer_id) bought twice (275831N and 275826N invoice's id) in the same day (2020-12-19) (penult_data = second-last date). This query is meant to be a support table, to left join the main table and bring those results.
First of all, i've created a row number just over customer_id (blue arrow, aux), so that I could just join with aux = 2 (that should be the second-last register), but in cases that the customer bought twice that day, the second-last invoice is not the second-last date he bought. I need the second-last DATE. He can buy 1,2,3,4,5 times a day, so I cannot assume a correct aux number to filter.
Then, for some reason, I also created an aux2, it's a row number over customer and date, but it really didn't help. I needed something that would repeat the index for the same date, so that index = 2 would be the second-last date.
I cannot use group by because i'm retrieving the salesman id (penult_vend), the store id (penult_empe), and so on from the second-last date
This is the output of part of the query I'm using (as I said, the support table to left join the main table). I'm filtering to this customer's id.
Does somebody knows any function or method to make this work?
I'm using google big query.
Thanks
Assuming the column penult_data has only date information without time of the day, you can find the second to last "date" and then the last "invoice" on that date by using the DENSE_RANK() and ROW_NUMBER() functions:
dense_rank() over(partition by id_cliente
order by penult_data desc) as rnd,
row_number() over(partition by id_cliente, penult_data
order by penult_nf desc) as rnf,
Then, you can use the filtering condition:
where rnd = 2 and rnf = 1
I'm trying to put together a query that will fetch the date, purchase amount, and number of transactions of the last time each user made a purchase. I am pulling from a user day table that contains a row for each time a user does anything in the app, purchase or not. Basically all I am trying to get is the most recent date in which the number of transactions field was greater than zero. The below query returns all days of purchase made by a particular user when all I'm looking for is the last purchase so just the 1st row shown in the attached screenshot is what I am trying to get.
screen shot of query and result set
select tuid, max(event_day),
purchases_day_rev as last_dop_rev,
purchases_day_num as last_dop_quantity,
purchases_day_rev/nullif(purchases_day_num,0) as last_dop_spend_pp
from
(select tuid, event_day,purchases_day_rev,purchases_day_num
from
app.user_day
where purchases_day_num > 0
and tuid='122d665e-1d71-4319-bb0d-05c7f37a28b0'
group by 1,2,3,4) a
group by 1,3,4,5
I'm not going to comment on the logic of your query... if all you want is the first row of your result set, you can try:
<your query here> ORDER BY 2 DESC LIMIT 1 ;
Where ORDER BY 2 DESC orders the result set on max(event_day) and LIMIT 1 extracts only the first row.
I don't know all of the ins and outs of your data, but I don't understand why you are grouping within the subquery without any aggregate function (sum, average, min, max, etc). With that said, I would try something like this:
select tuid
,event_day
,purchases_day_rev as last_dop_rev
,purchases_day_num as last_dop_quantity
,purchases_day_rev/nullif(purchases_day_num,0) as last_day_spend_pp
from app.user_day a
inner join
(
select tuid
,max(event_day) as MAX_DAY
from app.user_day
where purchases_day_num > 0
and tuid='122d665e-1d71-4319-bb0d-05c7f37a28b0'
group by 1
) b
on a.tuid = b.tuid
and a.event_day = b.max_day;
I'm trying to compare data from an Access 2010 database based on a date interval. Example I have items from various purchase orders and I want to maintain the history of these item's delivery to a warehouse. So my purchase order has a request for a quantity of 10 of a material, for example, and it can be partially delivered in many deliveries and I want to know how this delivery varied in a date interval. To fill the date field the criteria used is the following: if the item had an update in the QtyPending field, I copy the current row deactivating it with a booelan field, create a new entry with the current update date updating the QtyPending field, so the active record is the actual state of the item. So I have a table that holds informations about these items like that
PO POItem QtyPending Date Active
4500000123 10 10 01/09/2014 FALSE
4500000123 10 8 05/09/2014 TRUE
4500000122 30 5 03/09/2014 FALSE
4500000122 30 1 04/09/2014 TRUE
With this example, for the first item, it means that from date 01/09 to 04/09 the QtyPending field didn't suffer a variation, meaning that the supplier didn't make any delivery to me, but from 01/09 to 05/08 he delivered me a qty of 2 of a material. For the second one, from date 03/09 to 04/09 the supplier delivered me a qty of 4 of a material. So, if I were to be making a report query from 02/09/2014 to 04/09/2014, the expected output is like this:
PO POItem QtyDelivered
4500000123 10 0
4500000122 30 4
And a report from 31/08/2014 to 10/09/2014, would have this output
PO POItem QtyDelivered
4500000123 10 2
4500000122 30 4
I'm not coming up with a query to make this report. Can anyone help me?
There are many ways of solving this. The easiest one would be to simply make a query of all the necessary records between two dates, loop over them and insert into a temporary table the result. This temporary table can then be the source of your report. A lot of people will scream at you for not using a big query instead but getting the result that you want in the fastest and simplest way should be your priority.
Your problem with your schema is that you don't have the QtyDelivered stored for each record. If you would have it, it would be an easy thing to sum over it in order to get needed result. By not storing this value, you have transformed a simple and fast query into a much harder and slower one because you need to recalculate this value in some way or other and you must do this without forgetting the fact that it's possible to have more than two records.
For calculating this value, you can either use a sub-query to retrieve the value from the previous row or a Left join do to the same. Once you have this value, you can subtract these two to get the needed difference; allowing for the possibility of Null value if there is no previous row. Once you have these values, you can now sum over them to get the final result with a Group By. Notice that in order to perform these calculations, you need to have one or two more levels of subquery. The first query should be something like:
Select PO, POItem, QtyPending, (Select Top 1 QtyPending from MyTable T2 where T1.PO = T2.PO and T2.Date < T1.Date And (T2.Date between #Date1 and #Date2) Order by T2.Date Desc) as QtyPending2 from MyTable T1 Where T1.Date between #Date1 and #Date2) ...
With this as either another subquery or as a View, you can then compute the desired difference by comparing the values of QtyPending and QtyPending2; without forgetting that QtyPendin2 may be Null. The remaining steps are easy to do.
Notice that the above example is for SQL-Server, you might have to change it a little for Access. In any case, you can find here many examples on how to compare two rows under Access. As noted earlier, you can also use a Left Join instead of a subquery to compare your rows.
I came up with this query that solved the problem, it wasn't that simple
SELECT
ItmDtIni.PO
,ItmDtIni.POItem AS [PO Item]
,ROUND(ItmDtIni.QtyPending - ItmDtEnd.QtyPending, 3) AS [Qty Delivered]
,ROUND((ItmDtIni.QtyPending - ItmDtEnd.QtyPending) * ItmDtEnd.Price, 2) AS [Value delivered(US$)]
//Filtering subqueries to bring only the items in the date interval to make a self join
FROM (((SELECT
PO
,POItem
,QtyPending
,MIN(Date) AS MinDate
FROM Item
WHERE Date BETWEEN FORMAT(begin_date, 'dd/mm/yyyy') AND FORMAT(end_date, 'dd/mm/yyyy')
GROUP BY
PO
,POItem
,QtyPending) AS ItmDtIni
//Self join filtering to bring only items in the date interval with the previously filtered table
INNER JOIN (SELECT
PO
,POItem
,QtyPending
,Price
,MAX(Date) AS MaxDate
FROM Item
WHERE Date BETWEEN FORMAT(begin_date, 'dd/mm/yyyy') AND FORMAT(end_date, 'dd/mm/yyyy')
GROUP BY
PO
,POItem
,QtyPending
,Price) AS ItmDtEnd
ON ItmDtIni.PO = ItmDtEnd.PO
AND ItmDtIni.POItem = ItmDtEnd.POItem)
INNER JOIN PO
ON ItmDtEnd.PO = PO.Numero)
WHERE
//Showing only items that had a variation in the date interval
ROUND(ItmDtIni.QtyPending - ItmDtEnd.QtyPending, 3) <> 0
//Anchoring min date in the interval for each item found by the first subquery
AND ItmDtIni.MinDate = (SELECT MIN(Item.Date)
FROM Item
WHERE
ItmDtIni.PO = Item.PO
AND ItmDtIni.POItem = Item.POItem
AND Date BETWEEN FORMAT(begin_date, 'dd/mm/yyyy') AND FORMAT(end_date, 'dd/mm/yyyy'))
//Anchoring max date in the interval for each item found by the second subquery
AND ItmDtEnd.MaxDate = (SELECT MAX(Item.Date)
FROM Item
WHERE
ItmDtEnd.PO = Item.PO
AND ItmDtEnd.POItem = Item.POItem
AND Date BETWEEN FORMAT(begin_date, 'dd/mm/yyyy') AND FORMAT(end_date, 'dd/mm/yyyy'))
I'm working on an Ruby-on-Rails app which contains a list type of report. Two columns within that table are an aggregation from a transactional table.
So let's say we have these two tables:
**items**
id
name
group
price
**transactions**
id
item_id
type
date
qty
These two tables are connected with item_id in the transactions table.
Now I want to show some set of lines within the items table in a table and have two calculated columns within that table:
Calculated column 1 (Sparkline data):
Sparkline for transactions for the item with type="actuals" for the last 12 months. The result from the database should be text with aggregated qty for each month seperated by comma. Example:
15,20,0,12,44,33,6,4,33,23,11,65
Calculated column 2 (6m total sale):
Total qty for the item multiplied by sale for the last 6 months.
So the results would how columns like these:
Item name - Sparkline data - 6m total sale
So the result could by many thousand of lines, but would probably be paged.
So the question is, how is the most straightforward way of doing this in Rails models which doesn't sacrifice to much performance? Although this is a ruby-on-rails question it might contain more of a sql type solution.
The core sql could be something similar:
select
i.id,
i.name,
y.sparkline,
i.price*s.sum totalsale6m
from
items i left join
(select
x.item_id,
GROUP_CONCAT(x.sumqtd order by datemonth asc SEPARATOR ',') sparkline
from
(select
t.item_id,
date_format(date, '%m') datemonth,
sum(qtd) sumqtd
from
transactions t
where
t.type='actuals' and
t.date>date_sub(now(), interval 1 year)
group by
t.item_id, datemonth
) x
group by
x.item_id
) y on i.id=y.item_id
left join
(select
t.item_id,
sum(qtd) sumqtd
from
transactions t
where
t.date>date_sub(now(), interval 6 month)
group by
t.item_id
) s on i.id=s.item_id
group by
i.id, i.name
A few comments:
I wasn't able to test it without real data.
If there are gaps in the sales, I mean no sales in a given month, then the list will not contain 12 elements. In this case you need to adjust x,y tables
If you need the result only for a given few items, then probably you can put the item id filter deeper into the subqueries sparing time.