# GROUPING()

Use the `GROUPING()` clause with `ROLLUP` to determine whether null values are the result of a `ROLLUP` operation or part of your dataset. `GROUPING()` returns 1 if the null value is a subtotal generated by a rollup. It returns 0 otherwise.

This example uses the `GROUPING()` function and `CASE` statements together to label the subtotal and grand total categories. The first case checks for a null value generated by the rollup in the `Category` field. If true, then the query labels the field "All Categories." Similarly, the second case checks whether a `Sub-Category` field is null. If true, the query labels the field "All Sub-Categories."

```nolang
SELECT
(CASE WHEN GROUPING("Category") = 1 THEN 'All Categories' ELSE "Category" END) as "Category",
(CASE WHEN GROUPING("Sub_Category") = 1 THEN 'All Sub-Categories' ELSE "Sub_Category" END) as "SubCategory",
SUM("Sales") as "sum_sales"
FROM "Superstore"
GROUP BY ROLLUP("Category", "Sub_Category");
```

| Category        | Sub-Category       | sum_sales    |
| --------------- | ------------------ | ------------ |
| Furniture       | Bookcases          | 114,880      |
|                 | Chairs             | 328,449.1    |
|                 | Furnishings        | 91,705.16    |
|                 | Tables             | 206,965.53   |
|                 | All Sub-Categories | 741,999.8    |
| Office Supplies | Appliances         | 107,532.16   |
|                 | Art                | 27,118.73    |
|                 | Binders            | 203,412.73   |
|                 | Envelopes          | 16,476.4     |
|                 | Fasteners          | 3,024.28     |
|                 | Labels             | 12,486.31    |
|                 | Paper              | 78,479.21    |
|                 | Storage            | 223,843.61   |
|                 | Supplies           | 46,673.544   |
|                 | All Sub-Categories | 719,047.03   |
| Technology      | Accessories        | 167,380.32   |
|                 | Copiers            | 149,528.03   |
|                 | Machines           | 189,238.63   |
|                 | Phones             | 330,007.05   |
|                 | All Sub-Categories | 838,154.03   |
| All Categories  | All Sub-Categories | 2,297,200.86 |