Combine and fuse the results of two SQL queries with UNION - sql

I am writing two seperate SQL queries to get data for two different dates like so:
SELECT number, sum(sales) as sales, sum(discount) sa discount, sum(margin) as margin
FROM table_a
WHERE day = '2019-08-09'
GROUP BY number
SELECT number, sum(sales) as sales, sum(discount) sa discount, sum(margin) as margin
FROM table_a
WHERE day = '2018-08-10'
GROUP BY number
I tried fusing them like so to get the results for the same number in one row from two different dates:
SELECT number, sum(sales) as sales, sum(discount) sa discount, sum(margin) as margin, 0 as sales_n1, 0 as discount_n1, 0 as margin_n1
FROM table_a
WHERE day = '2019-08-09'
GROUP BY number
UNION
SELECT number, 0 as sales, 0 as discount, 0 as margin, sum(sales_n1) as sales_n1, sum(discount_n1) as discount_n1, sum(margin_n1) as margin_n1
FROM table_a
WHERE day = '2018-08-10'
GROUP BY number
But it didn't work as I get the rows for the first query with zeroes for the columns defined as zero followed by the columns of the second query in the same fashion.
How can I correct this to have the desired output ?

Use conditional aggregation:
SELECT number,
sum(case when day = '2019-08-09' then sales end) as sales_20190809,
sum(case when day = '2019-08-09' then discount end) sa discount, sum(margin) as margin_20190810,
sum(case when day = '2019-08-10' then sales end) as sales_20190809,
sum(case when day = '2019-08-10' then discount end) sa discount, sum(margin) as margin_20190810
FROM table_a
WHERE day IN ('2019-08-09', '2019-08-10')
GROUP BY number;
If you want the numbers in different rows (which you don't seem to), then use aggregation:
SELECT day, number, sum(sales) as sales, sum(discount) as discount, sum(margin) as margin
FROM table_a
WHERE day IN ('2019-08-09', '2019-08-10')
GROUP BY day, number

Related

Combine different results of "group by" queries in the same table

I need to make some comparation between 2 years: sales by product, sales by category, etc.
How can I have this in one table having 3 columns:
first column = product, category, etc
second column = sales in 2021
third column = sales in 2022
Sample of queries that must be combined in one single table as the one below
select product_code, sum(amount)
from product
where year = '2021'
group by product_code
select product_code, sum(amount)
from product
where year = '2022'
group by product_code
select category_code, sum(amount)
from category
where year = '2021'
group by category_code
select category_code, sum(amount)
from category
where year = '2022'
group by category_code
Please, see the final table
[1]: https://i.stack.imgur.com/smF7h.png
NOTE!
If for instance in 2021 there was no "product D", it will be 0 for "Sales_2021" or the "product A" is no longer present in 2022, it will be 0 for "Sales_2022".
Thank you
You need two things here:
Conditional aggregation (a CASE expression inside the aggregation function) in order to get 2021 and 2022 in one go.
A union of two intermediate result sets (product figures UNION ALL category figures).
And as any table - and a query result is again a table - is unordered, we need an ORDER BY at last to get products first and categories second and also the products ordered alphabetically and the categories, too.
The complete query:
select category_or_product, sales_2021, sales_2022
from
(
select
product_code as category_or_product,
sum(case when year = 2021 then amount else 0 end) as sales_2021,
sum(case when year = 2021 then amount else 0 end) as sales_2022,
1 as product_first
from product
group by product_code
union all
select
category_code as category_or_product,
sum(case when year = 2021 then amount else 0 end) as sales_2021,
sum(case when year = 2021 then amount else 0 end) as sales_2022,
2 as product_first
from category
group by category_code
) unioned
order by product_first, category_or_product;

Querying revenue by percentile in googlesql

I'm trying to group companies and their revenues by percentiles (>90% as Top, 50-90% as middle, < 50% as bottom, in googlesql.
Table format for revenue_table:
|company | product | revenue |
------------------------------
I'm trying out doing a cross join to split these companies up:
SELECT
company,
SUM(revenue) as revenue,
CASE
WHEN SUM(revenue) > Percentile90_Max THEN "Top"
WHEN SUM(revenue) >= Percentile50_Max THEN "Middle"
ELSE "Bottom"
END as percentile_section,
Percentile50_Max,
Percentile90_Max,
FROM revenue_table
CROSS JOIN
(SELECT
APPROX_QUANTILES(revenue,100)[offset(50)] As Percentile50_Max,
APPROX_QUANTILES(revenue,100)[offset(90)] As Percentile90_Max
FROM
(SELECT
company,
SUM(revenue) as revenue
FROM revenue_table
GROUP BY 1
)
)
GROUP BY 1,4,5
Order by 2 desc
The code above currently works, but gets broken once I change my main select statement to:
SELECT
company,
--SUM(revenue) as revenue,
CASE
WHEN SUM(revenue) > Percentile90_Max THEN "Top"
WHEN SUM(revenue) >= Percentile50_Max THEN "Middle"
ELSE "Bottom"
END as percentile_section,
--Percentile50_Max,
--Percentile90_Max,
... same code here
GROUP BY 1
Ideally my end result should just be Company + percentile_section.
How should I do this without doing another subquery? Or is subquery really the only way to go in terms of querying efficiency?
Thank you!
You should be able to calculate the quantiles as part of the aggregation, so no subquery should be necessary:
SELECT company, SUM(revenue) as revenue,
(CASE WHEN SUM(revenue) > (APPROX_QUANTILES(SUM(revenue), 100) OVER ())[offset(90)] THEN 'Top'
WHEN SUM(revenue) >= (APPROX_QUANTILES(SUM(revenue), 100) OVER ())[offset(50)] THEN 'Middle'
ELSE 'Bottom'
END) as percentile_section
FROM revenue_table
GROUP BY 1
Order by 2 desc

How to get the asked columns for each customers

I have this table called table a
I need to get the CustomerID, sum(Income) of 2015, sum(Income) of 2016, did he ever bought productId A (boolean), is the total sum(income)> 1000 (boolean), number of total InvoiceID
all that in one query and the results should be with 1 row per customer.
please help I don't even know how to start!
This is basically conditional aggregation:
select customerid,
sum(case when extract(year from date) = 2015 then sales end) as sales_2015,
sum(case when extract(year from date) = 2016 then sales end) as sales_2016,
max( product = 'A' ) as ever_bought_a,
sum(income) > 1000 as sum_exceeds_1000,
count(*) as num_invoices
from t
group by customerid;
You haven't specified a database, so this is really psuedocode. You'll need to adapt it for your particular database.

How can I add cumulative sum column?

I use SqlExpress
Following is the query using which I get the attached result.
SELECT ReceiptId, Date, Amount, Fine, [Transaction]
FROM (
SELECT ReceiptId, Date, Amount, 'DR' AS [Transaction]
FROM ReceiptCRDR
WHERE (Amount > 0)
UNION ALL
SELECT ReceiptId, Date, Amount, 'CR' AS [Transaction]
FROM ReceiptCR
WHERE (Amount > 0)
UNION ALL
SELECT strInvoiceNo AS ReceiptId, CONVERT(datetime, dtInvoiceDt, 103) AS Date, floatTotal AS Amount, 'DR' AS [Transaction]
FROM tblSellDetails
) AS t
ORDER BY Date
Result
want a new column which would show balance amount.
For example. 1 Row should show -2500, 2nd should -3900, 3rd should -700 and so on.
basically, it requires previous row' Account column's data and carry out calculation based on transaction type.
Sample Result
Well, that looks like SQL-Server , if you are using 2012+ , then use SUM() OVER() :
SELECT t.*,
SUM(CASE WHEN t.transactionType = 'DR'
THEN t.amount*-1
ELSE t.amount END)
OVER(PARTITION BY t.date ORDER BY t.receiptId,t.TransactionType DESC) as Cumulative_Col
FROM (YourQuery Here) t
This will SUM the value when its CR and the value*-1 when its DR
Right now I grouped by date, meaning each day will recalculate this column, if you want it for all time, replace the OVER() with this:
OVER(ORDER BY t.date,t.receiptId,t.TransactionType DESC) as Cumulative_Col
Also, I didn't understand why in the same date, for the same ReceiptId DR is calculated before CR , I've add it to the order by but if thats not what you want then explain the logic better.

adding a calculated/virtual column to an existing query

My query returns a sales column total for each month and a purchases total for each month, for certain categories.
SELECT theMonth,
sum(Sales) as sumSales,
sum(Saleswotax) as sumSaleswotax,
sum(Purchases) as sumPurchases,
sum(Purchaseswotax) as sumPurchaseswotax
FROM ( SELECT date_format(saledate, '%Y-%m') AS theMonth,
sales.cost as Sales,
ROUND(sales.cost*0.85, 2) AS Saleswotax,
0 AS Purchases,
0 AS Purchaseswotax
FROM sales, products
WHERE sales.product = products.name
AND category='Food'
UNION ALL
SELECT date_format(purchasedate, '%Y-%m') AS theMonth,
0 as Sales,
0 AS Saleswotax,
purchases.cost as Purchases,
ROUND(purchases.cost*0.85, 2) AS Purchaseswotax,
FROM purchases) AS all_costs
group by theMonth
I am trying to return a column(that does not actually exist in the table) in my query that is just a calculation of an existing table., ie the saleswotax and purchaseswotax columns.
I am using a function, and returning it AS a name...why is it not working?
In the union, you used 0 as sales and purchases columns, but didn't also do that for -wotax columns. They need to match up for the union to work properly (I think you know that, since you did it for Sales and Purchases).
You need to remove the comma after AS Purchasewotax in the latter half of the UNION:
SELECT theMonth,
sum(Sales) as sumSales,
sum(Saleswotax) as sumSaleswotax,
sum(Purchases) as sumPurchases,
sum(Purchaseswotax) as sumPurchaseswotax
FROM ( SELECT date_format(saledate, '%Y-%m') AS theMonth,
sales.cost as Sales,
ROUND(sales.cost*0.85, 2) AS Saleswotax,
0 AS Purchases,
0 AS Purchaseswotax
FROM sales, products
WHERE sales.product = products.name
AND category='Food'
UNION ALL
SELECT date_format(purchasedate, '%Y-%m') AS theMonth,
0 as Sales,
0 AS Saleswotax,
purchases.cost as Purchases,
ROUND(purchases.cost*0.85, 2) AS Purchaseswotax
FROM purchases) AS all_costs
GROUP BY theMonth
Last time when I saw, there was no declarative support for computed fields in MySQL.
You would have to either add computed columns to your table and fill them using an UPDATE/INSERT trigger. Or create Views with additional computed columns.