Additionally, all tuples with matching data in the grouping columns (i.e., all tuples that belong to the same group) will be combined. The values of the grouping columns are unchanged, and any other columns can be combined using an aggregate function (such as COUNT, SUM, AVG, etc.). The GROUP BY clause follows the WHERE clause in a SELECT statement and can precede the optional ORDER BY clause. Here is the basic syntax of the GROUP BY clause: 
SELECT column_list
FROM table_name
WHERE [ conditions ]
GROUP BY column1, column2....columnN
ORDER BY column1, column2....columnN
If your goal is to generate windowed calculation results strictly as append-only output, you can utilize the emit-on-window-close policy. This approach helps avoid unnecessary computations. For more information on the emit-on-window-close policy, please refer to Emit on window close. You can use more than one column in the GROUP BY clause. Basic GROUP BY example: 
-- compute the average salary per department per job_title
SELECT department, job_title, AVG(salary)
FROM employees
GROUP BY department, job_title;
This query results in a table with columns for department, job title, and average salary. Each row represents the average salary for a unique department and job title combination.

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GROUP BY GROUPING SETS()

With the GROUPING SETS() option, you can group data by multiple sets of columns in a single query. Each sublist of GROUPING SETS may specify zero or more columns or expressions and is interpreted the same way as though it were directly in the GROUP BY clause. With GROUPING SETS 
SELECT customer_id, product_category, SUM(order_amount) AS total_amount
FROM orders
GROUP BY GROUPING SETS ((customer_id, product_category), ());
Without GROUPING SETS 
SELECT customer_id, product_category, SUM(order_amount) AS total_amount
FROM orders
GROUP BY customer_id, product_category
UNION ALL
SELECT NULL, NULL, SUM(order_amount) AS total_amount
FROM orders;

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GROUP BY ROLLUP()

The GROUP BY ROLLUP() clause extends the functionality of the GROUP BY clause by providing a way to generate subtotals and grand totals for multiple levels of grouping. It creates a result set that includes rows representing different combinations of the specified grouping columns, along with subtotals and a grand total. The columns listed in the GROUP BY ROLLUP clause define the hierarchy of grouping levels, with the rightmost column being the most detailed level of grouping. 
SELECT product_category, product_subcategory, region, SUM(sales_amount) AS total_sales
FROM sales
GROUP BY ROLLUP (product_category, product_subcategory, region);
The results are like below:
product_categoryproduct_subcategoryregiontotal_sales
ElectronicsSmartphonesNorth1000
ElectronicsSmartphonesSouth1500
ElectronicsSmartphonesNULL2500
ElectronicsLaptopsNorth2000
ElectronicsLaptopsSouth0
ElectronicsLaptopsNULL2000
ElectronicsNULLNULL4500
FurnitureChairsNorth500
FurnitureChairsSouth700
FurnitureChairsNULL1200
FurnitureTablesNorth1000
FurnitureTablesSouth1200
FurnitureTablesNULL2200
FurnitureNULLNULL3400
NULLNULLNULL7900
In this example, there are subtotals for each combination of product_category, product_subcategory, and region. The NULL values in the grouping columns represent the grand total.

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GROUP BY CUBE()

The GROUP BY CUBE() clause generates multiple levels of grouping within a single query. It creates a result set that includes all possible combinations of the specified columns, generating a subtotal for each combination. The GROUP BY CUBE() clause is particularly useful when you need to analyze data across multiple dimensions and want to examine various levels of aggregation simultaneously. GROUP BY CUBE clause 
GROUP BY CUBE(c1,c2,c3)
Equivalent GROUP BY GROUPING SETS clause 
GROUP BY GROUPING SETS (
            (c1,c2,c3),
            (c1,c2),
            (c1,c3),
            (c2,c3),
            (c1),
            (c2),
            (c3),
            ()
        )
...