Is is possible in MDX to combine results of two queries based on the same member of several dimensions?
In my case:
There are two types of reports BuyersReports and SellersReports, e.g
BuyersReports
Buyer Seller Amount
A B 10
B C 20
SellersReports
Seller Buyer Amount
B A 10
C B 15
Each company (A,B,C) coulb be both buyer and seller.
I need to achieve some kind of this:
Buy Sell-To (Diff1) Sell Buy-From (Diff2)
B 20 15 5 10 10 0
Currently I have two measures: [Buyings] and [Sellings], and two instances of the same dimension of companies: [Buyers] and [Sellers].
I can get both parts of the desired query for company "B":
SELECT
[Measure].[Buyings],[Meausure].[Sellings] ON COLUMNS,
[Buyers].[Name], [Sellers].[Name] ON ROWS
FROM
(
SELECT [Buyers].[Name].&[B] ON COLUMNS
FROM MyCube
)
gives me
B C 20 15
And
SELECT
[Measure].[Buyings],[Meausure].[Sellings] ON COLUMNS,
[Buyers].[Name], [Sellers].[Name] ON ROWS
FROM
(
SELECT [Sellers].[Name].&[B] ON COLUMNS
FROM MyCube
)
with result
A B 10 10
Is it possible to combine results of these two queries to achieve combined buyer-seller report for each company?
SELECT
[Measure].[Buyings],[Meausure].[Sellings] ON COLUMNS,
[Buyers].[Name], [Sellers].[Name] ON ROWS
FROM
(
SELECT {[Sellers].[Name].&[B],SELECT [Buyers].[Name].&[B]} ON COLUMNS
FROM MyCube
)
Related
I have a data frame containing two columns - ID and SHOP, and I want to find the count of unique Customer IDs that correspond to unique combination of shops in the Shop column. My original data frame is as follows
CustomerID
SHOP
1
A
2
A
3
B
1
C
2
D
4
E
The intended output should be as follows:
SHOP PAIR
CUSTOMERS
A-C
1
A-D
1
Is there a smart way to achieve this in R? Thanks for the help!
This question already has answers here:
Two SQL LEFT JOINS produce incorrect result
(3 answers)
Closed 12 months ago.
I am having some troubles with a count function. The problem is given by a left join that I am not sure I am doing correctly.
Variables are:
Customer_name (buyer)
Product_code (what the customer buys)
Store (where the customer buys)
The datasets are:
Customer_df (list of customers and product codes of their purchases)
Store1_df (list of product codes per week, for Store 1)
Store2_df (list of product codes per day, for Store 2)
Final output desired:
I would like to have a table with:
col1: Customer_name;
col2: Count of items purchased in store 1;
col3: Count of items purchased in store 2;
Filters: date range
My query looks like this:
SELECT
DISTINCT
C_customer_name,
C.product_code,
COUNT(S1.product_code) AS s1_sales,
COUNT(S2.product_code) AS s2_sales,
FROM customer_df C
LEFT JOIN store1_df S1 USING(product_code)
LEFT JOIN store2_df S2 USING(product_code)
GROUP BY
customer_name, product_code
HAVING
S1_sales > 0
OR S2_sales > 0
The output I expect is something like this:
Customer_name
Product_code
Store1_weekly_sales
Store2_weekly_sales
Luigi
120012
4
8
James
100022
6
10
But instead, I get:
Customer_name
Product_code
Store1_weekly_sales
Store2_weekly_sales
Luigi
120012
290
60
James
100022
290
60
It works when instead of COUNT(product_code) I do COUNT(DSITINCT product_code) but I would like to avoid that because I would like to be able to aggregate on different timespans (e.g. if I do count distinct and take into account more than 1 week of data I will not get the right numbers)
My hypothesis are:
I am joining the tables in the wrong way
There is a problem when joining two datasets with different time aggregations
What am I doing wrong?
The reason as Philipxy indicated is common. You are getting a Cartesian result from your data thus bloating your numbers. To simplify, lets consider just a single customer purchasing one item from two stores. The first store has 3 purchases, the second store has 5 purchases. Your total count is 3 * 5. This is because for each entry in the first is also joined by the same customer id in the second. So 1st purchase is joined to second store 1-5, then second purchase joined to second store 1-5 and you can see the bloat. So, by having each store pre-query the aggregates per customer will have AT MOST, one record per customer per store (and per product as per your desired outcome).
select
c.customer_name,
AllCustProducts.Product_Code,
coalesce( PQStore1.SalesEntries, 0 ) Store1SalesEntries,
coalesce( PQStore2.SalesEntries, 0 ) Store2SalesEntries
from
customer_df c
-- now, we need all possible UNIQUE instances of
-- a given customer and product to prevent duplicates
-- for subsequent queries of sales per customer and store
JOIN
( select distinct customerid, product_code
from store1_df
union
select distinct customerid, product_code
from store2_df ) AllCustProducts
on c.customerid = AllCustProducts.customerid
-- NOW, we can join to a pre-query of sales at store 1
-- by customer id and product code. You may also want to
-- get sum( SalesDollars ) if available, just add respectively
-- to each sub-query below.
LEFT JOIN
( select
s1.customerid,
s1.product_code,
count(*) as SalesEntries
from
store1_df s1
group by
s1.customerid,
s1.product_code ) PQStore1
on AllCustProducts.customerid = PQStore1.customerid
AND AllCustProducts.product_code = PQStore1.product_code
-- now, same pre-aggregation to store 2
LEFT JOIN
( select
s2.customerid,
s2.product_code,
count(*) as SalesEntries
from
store2_df s2
group by
s2.customerid,
s2.product_code ) PQStore2
on AllCustProducts.customerid = PQStore2.customerid
AND AllCustProducts.product_code = PQStore2.product_code
No need for a group by or having since all entries in their respective pre-aggregates will result in a maximum of 1 record per unique combination. Now, as for your needs to filter by date ranges. I would just add a WHERE clause within each of the AllCustProducts, PQStore1, and PQStore2.
I have two tables Medication and Inventory. I'm trying to SELECT all the below details from both tables but there are multiple listings of medication ids with different BRANCH_NO also in the INVENTORY table (the primary key in INVENTORY is actually BRANCH_NO, MEDICATION_ID composite key)
I need to total up the various medication_IDs and also join the tables in one SELECT command and display all the infomation for each med (there are 5) with a total sum of each med at the end of each row. But im getting all muddled trying Group by and Sum and at one point partition. Help please I'm new to this.
Below is the latest non working version - but it doesn't display
Medication Name
Medication Desc
Manufacturer
Pack Size
like i chanced it might.
SELECT I.MEDICATION_ID,
SUM(I.STOCK_LEVEL)
FROM INVENTORY I
INNER JOIN (SELECT MEDICATION_NAME, SUBSTR(MEDICATION_DESC,1,20) "Medication Description",
MANUFACTURER, PACK_SIZE FROM MEDICATION) M ON MEDICATION_ID=I.MEDICATION_ID
GROUP BY I.MEDICATION_ID;
For the data imagine I want this sort of output:
MEDICATION_ID MEDICATION_NAME STOCK_LEVEL OtherColumns.....
1 Alpha 10
2 Bravo 20
3 Charlie 20
1 Alpha 30
4 Delta 10
5 Echo 20
5 Echo 40
2 Bravo 10
grouping and totalling into this:
MEDICATION_ID MEDICATION_NAME STOCK_LEVEL OtherColumns.....
1 Alpha 40
2 Bravo 30
3 Charlie 20
4 Delta 10
5 Echo 60
I can get this when its just one table but when Im trying to join tables and also SELECT things its just not working.
Thanks in advance guys. I appreciate it may be a simple solution, but it will be a big help.
You need to write explicitly all non-aggregated columns into both SELECT and GROUP BY lists ( Btw, no need to use a nested query, and if it's the case MEDICATION_ID column is missing in it ) :
SELECT I.MEDICATION_ID, M.MEDICATION_NAME, SUM(I.STOCK_LEVEL) AS STOCK_LEVEL,
SUBSTR(M.MEDICATION_DESC,1,20) "Medication Description", M.MANUFACTURER, M.PACK_SIZE
FROM INVENTORY I
JOIN MEDICATION M ON M.MEDICATION_ID = I.MEDICATION_ID
GROUP BY I.MEDICATION_ID, M.MEDICATION_NAME, SUBSTR(M.MEDICATION_DESC,1,20),
M.MANUFACTURER, M.PACK_SIZE;
This way, you'll be able to return all the listed columns.
i have table that store questions each question have different answers and each answer have different weight and now i want to Calculation the rank but i don't now how do this.please help me
i use sql server
i have this table stored answers and weight of each answer
AdminQuesAns
=======================
Id QuesId Ans Value
10 1000 Yes 10
11 1000 somewhat 5
12 1000 No 0
10 1001 Yes 0
12 1001 No 10
and this table store Customer answers
AdminRank
==================================
Id SDId QuesId AnsValue
1 100 1000 10
2 100 1001 0
You can use the below query.
1.
Select SDId ,b.QuesId,
((sum(a.AnsValue) *100)/(Select sum(c.value)
from AdminQuesAns c where c.QuesId =b.QuesId))as'Rank'
from AdminRank a join AdminQuesAns b on a.QuesId=b.QuesId and value=AnsValue
group by SDId ,b.QuesId
This is how I'd go about it.
This has an inner query which gets the max value for each question, then the outer query pairs those with the values from the individual answers, sums across the questions and calculates one as a percentage of the other.
I'm also grouping by SDId, on the assumption that that is the ID of the person filling out the survey.
SELECT
ar.SDId,
100 * cast(sum(ar.AnsValue) as numeric(5,2)) / sum(mv.maxValue) as Rank
FROM
AdminRank ar
JOIN
(
SELECT
qa.QuesId,
max(qa.Value) as maxValue
FROM
AdminQuesAns qa
GROUP BY
qa.QuesId
) mv on ar.QuesId = mv.QuesId
GROUP BY
ar.SDId
Depending on your data types you may be able to remove the cast part.
I need a query to select a common record from four table based on single condition from a table
I used a query which returns 240 records but the condition returns only 2 result sets.
Reference no from all the given tables are same.
Select b.cdr_data
,a.cdr_data
,c.cdr_data
from itaukei_data_store b
,itaukei_data_store_key a
,ITAUKEI_BANK_ACCOUNT c
,payment_data_store d
where a.reference_no = b.reference_no
and a.reference_no=c.ITK_REFNO
and b.INDIVIDUAL_REFNO=d.INDIV_REF_NO
and d.remarks='Below 18 years';
But,
select * from payment_data_store where remarks='Below 18 years';
Returns 2 records alone.
You Try like this
Select b.cdr_data,a.cdr_data,c.cdr_data,d.cdr_data
from itaukei_data_store b,itaukei_data_store_key a,
ITAUKEI_BANK_ACCOUNT c,payment_data_store d
where a.reference_no = b.reference_no
and b.reference_no=c.ITK_REFNO
and b.INDIVIDUAL_REFNO=d.INDIV_REF_NO
and d.remarks='Below 18 years';