Description of grouping.eps follows

Provides insights into grouped data.



In the following example, which uses the sample tables hr.departments and hr.employees, if the GROUPING function returns 1 (indicating a superaggregate row rather than a regular row from the table), then the string “All Jobs” appears in the “JOB” column instead of the null that would otherwise appear:

DEPARTMENT JOB Total Empl Average Sal

Identifying Grouped Rows: GROUPING() is handy for identifying when a row is part of an aggregated group. This is particularly useful when dealing with roll-up or cube operations.

Useful in Roll-Up and Cube Operations: When performing roll-up or cube operations, GROUPING() helps distinguish between subtotal and grand total rows. This can be crucial for data analysis and reporting.

Conditional Aggregation: GROUPING() can be used in conjunction with conditional aggregation. For instance, you can sum a column only for the detailed rows and display “N/A” for the aggregated rows.

Enhanced Reporting: Improve the readability of your reports by incorporating GROUPING() into your SELECT statements. It allows you to present summarized data while maintaining visibility on the level of aggregation.

Working with NULL Values: GROUPING() is particularly useful when dealing with NULL values in grouped columns. It helps to differentiate between a NULL value in a grouped column and a NULL value that results from the aggregation.

Example of GROUP BY with GROUPING

SUM(sales) AS totalSales,
GROUPING(column1) AS isColumn1Grouped,
GROUPING(column2) AS isColumn2Grouped
FROM salesData
GROUP BY ROLLUP (column1, column2);

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