Combining aggregate and non-aggregate values in SQL using Joins and Over clause

In SQL, combining aggregate and non-aggregate values is a common scenario, especially in reporting tasks. The OVER() clause, part of the window functions feature in many RDBMS systems, allows for this kind of operation.

Let's say we have the following sales table, and we want to report each sale along with the total sales for the corresponding salesperson:

salesperson | amount
------------|-------
John        | 100
John        | 200
Jane        | 150
Jane        | 50

We want a result like:

salesperson | amount | total_sales
------------|------- |------------
John        | 100    | 300
John        | 200    | 300
Jane        | 150    | 200
Jane        | 50     | 200

Here's how you can achieve this using the OVER() clause:

SELECT
    salesperson,
    amount,
    SUM(amount) OVER(PARTITION BY salesperson) as total_sales
FROM
    sales;

In this example:

SUM(amount) OVER(PARTITION BY salesperson) computes the sum of amount for each salesperson. The result of this computation is displayed on every row.
The PARTITION BY clause in the OVER() function ensures the sum is computed separately for each salesperson.

This provides a simple and efficient way to combine aggregate (the total sales) and non-aggregate values (each individual sale) in a single SQL query.

In cases where window functions aren't available or aren't the best fit, you might resort to joins, subqueries, or other techniques, but the OVER() clause is often the most elegant and performant solution for this type of requirement.

SQL combining aggregate and non-aggregate values example:
Consider a scenario where you want to find the total sales amount and the average price per product. You can achieve this with a query like:
```
SELECT product_id, 
       SUM(sales_amount) AS total_sales, 
       AVG(price) AS avg_price
FROM sales
GROUP BY product_id;
```
Joining tables with aggregate functions in SQL:
Suppose you have two tables, orders and order_items. You can join them and calculate the total quantity of items sold for each order:
```
SELECT o.order_id, 
       SUM(oi.quantity) AS total_quantity
FROM orders o
JOIN order_items oi ON o.order_id = oi.order_id
GROUP BY o.order_id;
```
Using Over clause to combine aggregate and non-aggregate values:
Using the OVER clause with window functions, you can calculate the total sales amount for each product along with the individual sales amounts:
```
SELECT product_id, 
       sales_amount,
       SUM(sales_amount) OVER (PARTITION BY product_id) AS total_sales
FROM sales;
```
Aggregate and non-aggregate values in the same SQL query:
Combining aggregate and non-aggregate values in the same query is common. For instance, finding the average price and the details of products with prices above the average:
```
SELECT product_id, 
       price,
       AVG(price) OVER () AS avg_price
FROM products
WHERE price > AVG(price) OVER ();
```

SQL join with group by and over clause:

Combining a join, GROUP BY, and OVER clause to get the average price per category:

SELECT p.category_id,
       AVG(p.price) OVER (PARTITION BY p.category_id) AS avg_price
FROM products p
JOIN categories c ON p.category_id = c.category_id;

Combining results of aggregate and non-aggregate queries:

Merging results from different queries using UNION:

SELECT product_id, AVG(price) AS avg_price
FROM products
GROUP BY product_id

UNION

SELECT NULL, AVG(price)
FROM products;

SQL window functions for combining aggregate and non-aggregate data:

Utilizing window functions for a cumulative sum of sales_amount per product:

SELECT product_id,
       sales_amount,
       SUM(sales_amount) OVER (PARTITION BY product_id ORDER BY sale_date) AS cumulative_sales
FROM sales;

Joining tables with different levels of aggregation in SQL:

Combining tables with different levels of aggregation, like getting the average price per category and the total sales per product:

SELECT p.product_id, 
       AVG(p.price) OVER (PARTITION BY p.category_id) AS avg_price,
       s.total_sales
FROM products p
JOIN (
   SELECT product_id, SUM(sales_amount) AS total_sales
   FROM sales
   GROUP BY product_id
) s ON p.product_id = s.product_id;

SQL combining aggregate and non-aggregate values in subqueries:
Using a subquery to find products with prices above the average:
```
SELECT product_id, price
FROM products
WHERE price > (SELECT AVG(price) FROM products);
```

Over clause with partition by in SQL for mixed aggregations:

Employing the OVER clause with PARTITION BY to calculate both the total sales and average price per product:

SELECT product_id,
       sales_amount,
       AVG(price) OVER (PARTITION BY product_id) AS avg_price,
       SUM(sales_amount) OVER (PARTITION BY product_id) AS total_sales
FROM sales;