Help Center/ Data Lake Insight/ SQL Syntax Reference (To Be Offline)/ Spark SQL Syntax Reference (Unavailable Soon)/ Grouping/ ROLLUP
Updated on 2023-11-03 GMT+08:00
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ROLLUP

Function

This statement is used to generate the aggregate row, super-aggregate row, and the total row. The statement can achieve multi-layer statistics from right to left and display the aggregation of a certain layer.

Syntax

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SELECT attr_expr_list FROM table_reference
  GROUP BY col_name_list
  WITH ROLLUP;

Keyword

ROLLUP is the expansion of GROUP BY. For example, SELECT a, b, c, SUM(expression) FROM table GROUP BY a, b, c WITH ROLLUP; can be transformed into the following query statements:
  • Counting the (a, b, c) combinations 
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    SELECT a, b, c, sum(expression) FROM table
  GROUP BY a, b, c;
  • Counting the (a, b) combinations 
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    SELECT a, b, NULL, sum(expression) FROM table
  GROUP BY a, b;
  • Counting the (a) combinations 
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    SELECT a, NULL, NULL, sum(expression) FROM table
  GROUP BY a;
  • Total 
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    SELECT NULL, NULL, NULL, sum(expression) FROM table;

Precautions

The to-be-grouped table must exist. If this statement is used to group a table that does not exist, an error is reported.

Example

To generate the aggregate row, super-aggregate row, and total row according to the group_id and job fields and return the total salary on each aggregation condition, run the following statement:

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SELECT group_id, job, SUM(salary) FROM group_test
  GROUP BY group_id, job
  WITH ROLLUP;
Parent topic: Grouping