GROUP BY

Description

GROUP BY GROUPING SETS ｜ CUBE ｜ ROLLUP is an extension of the GROUP BY clause. It can realize the aggregation of groups of multiple sets in a GROUP BY clause. The result is equivalent to the UNION operation of multiple corresponding GROUP BY clauses.

GROUP BY clause is a special case of GROUP BY GROUPING SETS containing only one element. For example, the GROUPING SETS statement:

  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );

The query result is equivalent to:

  SELECT a, b, SUM( c ) FROM tab1 GROUP BY a, b
  UNION
  SELECT a, null, SUM( c ) FROM tab1 GROUP BY a
  UNION
  SELECT null, b, SUM( c ) FROM tab1 GROUP BY b
  UNION
  SELECT null, null, SUM( c ) FROM tab1

GROUPING(expr) indicates whether a column is an aggregate column. If it is an aggregate column, it is 0, otherwise it is 1.

GROUPING_ID(expr [ , expr [ , ... ] ]) is similar to GROUPING. GROUPING_ ID calculates the bitmap value of a column list according to the specified column order, and each bit is the value of GROUPING.

GROUPING_ID() function returns the decimal value of the bit vector.

Syntax

  SELECT ...
  FROM ...
  [ ... ]
  GROUP BY [
      , ... |
      GROUPING SETS [, ...] (  groupSet [ , groupSet [ , ... ] ] ) |
      ROLLUP(expr  [ , expr [ , ... ] ]) |
      expr  [ , expr [ , ... ] ] WITH ROLLUP |
      CUBE(expr  [ , expr [ , ... ] ]) |
      expr  [ , expr [ , ... ] ] WITH CUBE
      ]
  [ ... ]

Parameters

groupSet represents a set composed of columns, aliases or expressions in the select list. groupSet ::= { ( expr [ , expr [ , ... ] ] )}

expr indicates the column, alias or expression in the select list.

Note

CelerData supports syntax like PostgreSQL. The syntax examples are as follows:

  SELECT a, b, SUM( c ) FROM tab1 GROUP BY GROUPING SETS ( (a, b), (a), (b), ( ) );
  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY ROLLUP(a,b,c)
  SELECT a, b,c, SUM( d ) FROM tab1 GROUP BY CUBE(a,b,c)

ROLLUP(a,b,c) is equivalent to the followingGROUPING SETS statement:

  GROUPING SETS (
  (a,b,c),
  ( a, b ),
  ( a),
  ( )
  )

CUBE ( a, b, c ) is equivalent to the followingGROUPING SETS statement:

  GROUPING SETS (
  ( a, b, c ),
  ( a, b ),
  ( a,    c ),
  ( a       ),
  (    b, c ),
  (    b    ),
  (       c ),
  (         )
  )

Examples

The following is an example of actual data:

  > SELECT * FROM t;
  +------+------+------+
  | k1   | k2   | k3   |
  +------+------+------+
  | a    | A    |    1 |
  | a    | A    |    2 |
  | a    | B    |    1 |
  | a    | B    |    3 |
  | b    | A    |    1 |
  | b    | A    |    4 |
  | b    | B    |    1 |
  | b    | B    |    5 |
  +------+------+------+
  8 rows in set (0.01 sec)

  > SELECT k1, k2, SUM(k3) FROM t GROUP BY GROUPING SETS ( (k1, k2), (k2), (k1), ( ) );
  +------+------+-----------+
  | k1   | k2   | sum(`k3`) |
  +------+------+-----------+
  | b    | B    |         6 |
  | a    | B    |         4 |
  | a    | A    |         3 |
  | b    | A    |         5 |
  | NULL | B    |        10 |
  | NULL | A    |         8 |
  | a    | NULL |         7 |
  | b    | NULL |        11 |
  | NULL | NULL |        18 |
  +------+------+-----------+
  9 rows in set (0.06 sec)

  > SELECT k1, k2, GROUPING_ID(k1,k2), SUM(k3) FROM t GROUP BY GROUPING SETS ((k1, k2), (k1), (k2), ());
  +------+------+---------------+----------------+
  | k1   | k2   | grouping_id(k1,k2) | sum(`k3`) |
  +------+------+---------------+----------------+
  | a    | A    |             0 |              3 |
  | a    | B    |             0 |              4 |
  | a    | NULL |             1 |              7 |
  | b    | A    |             0 |              5 |
  | b    | B    |             0 |              6 |
  | b    | NULL |             1 |             11 |
  | NULL | A    |             2 |              8 |
  | NULL | B    |             2 |             10 |
  | NULL | NULL |             3 |             18 |
  +------+------+---------------+----------------+
  9 rows in set (0.02 sec)
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