Grouping_ID

 GROUPING_ID function in Oracle is used to return a unique identifier for the combination of columns in a GROUP BY query. It helps in identifying whether a row in the result set corresponds to a regular data row or a summary row (such as subtotals or grand totals). This function is particularly useful when you are working with hierarchical data and using ROLLUP, CUBE, or GROUPING SETS to generate summary rows.

Here’s a detailed breakdown of the GROUPING_ID function:

 

1. What is GROUPING_ID?

The GROUPING_ID function generates an integer value that can be used to identify the grouping level of a particular row in the result set. This function is helpful in distinguishing between regular data rows and summary rows (like subtotals or grand totals), which are produced by grouping extensions like ROLLUP, CUBE, or GROUPING SETS.

• The value returned by GROUPING_ID is a bitwise identifier that corresponds to the combination of grouping columns in the GROUP BY clause.
• A value of 0 indicates a regular data row.
• A non-zero value indicates a summary row (such as a subtotal or grand total) and is unique for each combination of grouped columns.

 

2. Syntax of GROUPING_ID

The syntax for using the GROUPING_ID function is as follows:

GROUPING_ID(expr1, expr2, ..., exprN)

Where:

• expr1, expr2, ..., exprN are the expressions (usually column names) involved in the GROUP BY clause.

The function returns an integer value based on the grouping of the columns.

 

3. How does GROUPING_ID work?

The GROUPING_ID function returns a unique integer for each distinct combination of groupings. This value is determined by the bitwise representation of the GROUP BY expressions.

For example:

• If you use GROUP BY (column1, column2), GROUPING_ID will return 0 for regular rows and other non-zero integer values for summary rows.

Here’s how the bitwise representation works:

• Each grouping column gets a specific bit in the integer value.
• If a column is aggregated (i.e., a summary row), the corresponding bit is set to 1; otherwise, it is set to 0.

Example:

Consider this query with GROUPING_ID:

SELECT region, product, SUM(sales),

       GROUPING_ID(region, product) AS group_id

FROM sales_data

GROUP BY ROLLUP(region, product);

• A value of 0 in the group_id column represents a regular data row.
• A value of 1 represents a subtotal for product (the region value is null in the summary row).
• A value of 2 represents a subtotal for region (the product value is null).
• A value of 3 represents the grand total (both region and product values are null).

 

4. Example of GROUPING_ID in Action

Let's say you have a sales_data table with the following columns: region, product, and sales. If you want to generate subtotals for each region and product, and also a grand total, you can use GROUPING_ID to identify each type of row.

SELECT region, product, SUM(sales),

       GROUPING_ID(region, product) AS group_id

FROM sales_data

GROUP BY ROLLUP(region, product);

Sample Output:

region	product	SUM(sales)	group_id
North	A	100	0
North	B	200	0
North	NULL	300	1
South	A	150	0
South	B	250	0
South	NULL	400	1
NULL	NULL	700	3

• Regular Rows (data rows) have group_id = 0.
• Subtotal for region has group_id = 1 (since the product is null).
• Grand Total has group_id = 3 (since both region and product are null).

 

5. What does the GROUPING_ID Return?

The value returned by GROUPING_ID is an integer that represents a bitwise identifier for the groupings. Here's how to interpret the results:

• 0: Regular data row (no grouping).
• 1, 2, 3, ...: Summary rows corresponding to various levels of aggregation (subtotals, grand totals).

The bitwise integer can represent multiple grouping levels, depending on how many columns are used in the GROUP BY clause.

 

6. Using GROUPING_ID with CASE for Custom Labels

You can use GROUPING_ID in combination with a CASE statement to display custom labels for summary rows (subtotals and grand totals).

For example, to label the subtotals and grand total rows with meaningful names, you could modify the query as follows:

SELECT region, product, SUM(sales),

       CASE 

           WHEN GROUPING_ID(region, product) = 0 THEN 'Data Row'

           WHEN GROUPING_ID(region, product) = 1 THEN 'Subtotal for Product'

           WHEN GROUPING_ID(region, product) = 2 THEN 'Subtotal for Region'

           WHEN GROUPING_ID(region, product) = 3 THEN 'Grand Total'

       END AS row_label

FROM sales_data

GROUP BY ROLLUP(region, product);

In this query:

• GROUPING_ID(region, product) = 0 corresponds to regular data rows.
• GROUPING_ID(region, product) = 1 corresponds to subtotals for products.
• GROUPING_ID(region, product) = 2 corresponds to subtotals for regions.
• GROUPING_ID(region, product) = 3 corresponds to the grand total.

 

7. Performance Considerations

The GROUPING_ID function is usually fast, as it computes a bitwise identifier for each row, which is computationally inexpensive. However, performance can depend on:

• The complexity of the GROUP BY clause.
• The number of rows being grouped and aggregated.

If you’re working with very large datasets, it’s a good idea to ensure the query is optimized with appropriate indexing.

 

8. Handling NULL Values

The GROUPING_ID function works well with NULL values generated by grouping extensions like ROLLUP and CUBE. It identifies summary rows where the NULL values appear and provides an integer identifier for those rows.

For example:

• In a ROLLUP operation, rows where one or more columns are NULL (e.g., subtotals or grand totals) will receive a unique GROUPING_ID.

 

9. What is the Difference Between GROUPING_ID and GROUPING?

·        GROUPING_ID: Returns a unique integer that identifies the combination of groupings in a result set. It is used to distinguish between summary rows and regular rows and provides an integer identifier for each type of row.

·        GROUPING: Returns either 0 or 1 for each column in a GROUP BY query, indicating whether a column is aggregated (part of a summary row) or contains actual data (part of a regular data row).

 

10. Is GROUPING_ID Useful for Large Datasets?

Yes, GROUPING_ID is quite useful for large datasets where you're generating multiple levels of aggregation (e.g., subtotals, grand totals). It provides a clear and easy way to distinguish between regular data rows and summary rows.

 

Conclusion

The GROUPING_ID function is a powerful tool in Oracle SQL, particularly when dealing with ROLLUP, CUBE, or GROUPING SETS in complex aggregation queries. It helps identify the different grouping levels in a result set and makes it easier to apply custom labels or logic for summary rows (like subtotals and grand totals).