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Query Syntax

GROUP BY

Groups rows with the same group-by-item expressions and computes aggregate functions for the resulting group. A GROUP BY expression can be:

  • A column name.

  • A number referencing a position in the SELECT list.

  • A general expression.

Extensions:

GROUP BY CUBE , GROUP BY GROUPING SETS , GROUP BY ROLLUP

Syntax

SELECT ...
  FROM ...
  [ ... ]
  GROUP BY groupItem [ , groupItem [ , ... ] ]
  [ ... ]
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SELECT ...
  FROM ...
  [ ... ]
  GROUP BY ALL
  [ ... ]
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Where:

GROUP BY groupItem [ , groupItem [ , ... ] ]

Specifies the column aliases, positions, or expressions to use for grouping. For each groupItem, use the following syntax:

groupItem ::= { <column_alias> | <position> | <expr> }
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Where:

  • column_alias specifies the column alias appearing in the query block’s SELECT list.

  • position specifies the position of an expression in the SELECT list.

  • expr specifies any expression on tables in the current scope.

GROUP BY ALL

Specifies that all items in the SELECT list that do not use aggregate functions should be used for grouping.

For examples, refer to Group By All Columns.

Usage Notes

  • A GROUP BY clause can reference expressions in the projection clause by name or by position. If the GROUP BY clause references by name, then each reference is resolved as follows:

    • If the query contains a database object (e.g. table or view) with a matching column name, then the reference is resolved to the column name.

    • Otherwise, if the projection clause of the SELECT contains an expression alias with a matching name, then the reference is resolved to the alias.

    For an example, see Demonstrate Precedence When a Column Name and an Alias Match.

  • If all SELECT items use aggregate functions, specifying GROUP BY ALL is equivalent to specifying the statement without the GROUP BY clause.

    For example, the following statement only has SELECT items that use aggregate functions:

    SELECT SUM(amount)
      FROM mytable
      GROUP BY ALL;
    
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    The statement above is equivalent to not specifying the GROUP by clause:

    SELECT SUM(amount)
      FROM mytable;
    
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Examples

The following sections provide examples of using the GROUP BY clause:

Note that the examples in each section use the data that you set up in Setting Up the Data for the Examples.

Setting Up the Data for the Examples

The examples in this section use a table named sales and a table named product. To create these tables and insert the data needed for the example, execute the following statements:

CREATE TABLE sales (
  product_ID INTEGER,
  retail_price REAL,
  quantity INTEGER,
  city VARCHAR,
  state VARCHAR);

INSERT INTO sales (product_id, retail_price, quantity, city, state) VALUES
  (1, 2.00,  1, 'SF', 'CA'),
  (1, 2.00,  2, 'SJ', 'CA'),
  (2, 5.00,  4, 'SF', 'CA'),
  (2, 5.00,  8, 'SJ', 'CA'),
  (2, 5.00, 16, 'Miami', 'FL'),
  (2, 5.00, 32, 'Orlando', 'FL'),
  (2, 5.00, 64, 'SJ', 'PR');

CREATE TABLE products (
  product_ID INTEGER,
  wholesale_price REAL);
INSERT INTO products (product_ID, wholesale_price) VALUES (1, 1.00);
INSERT INTO products (product_ID, wholesale_price) VALUES (2, 2.00);
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Group By One Column

This example shows the gross revenue per product, grouped by product_id (i.e. the total amount of money received for each product):

SELECT product_ID, SUM(retail_price * quantity) AS gross_revenue
  FROM sales
  GROUP BY product_ID;
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+------------+---------------+
| PRODUCT_ID | GROSS_REVENUE |
+============+===============+
|          1 |          6    |
+------------+---------------+
|          2 |        620    |
+------------+---------------+

The following example builds on the previous example, showing the net profit per product, grouped by product_id:

SELECT p.product_ID, SUM((s.retail_price - p.wholesale_price) * s.quantity) AS profit
  FROM products AS p, sales AS s
  WHERE s.product_ID = p.product_ID
  GROUP BY p.product_ID;
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+------------+--------+
| PRODUCT_ID | PROFIT |
+============+========+
|          1 |      3 |
+------------+--------+
|          2 |    372 |
+------------+--------+

Group By Multiple Columns

The following example demonstrates how to group by multiple columns:

SELECT state, city, SUM(retail_price * quantity) AS gross_revenue
  FROM sales
  GROUP BY state, city;
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+-------+---------+---------------+
| STATE |   CITY  | GROSS REVENUE |
+=======+=========+===============+
|   CA  | SF      |            22 |
+-------+---------+---------------+
|   CA  | SJ      |            44 |
+-------+---------+---------------+
|   FL  | Miami   |            80 |
+-------+---------+---------------+
|   FL  | Orlando |           160 |
+-------+---------+---------------+
|   PR  | SJ      |           320 |
+-------+---------+---------------+

Group By All Columns

The following example is equivalent to the example used in Group By Multiple Columns.

SELECT state, city, SUM(retail_price * quantity) AS gross_revenue
  FROM sales
  GROUP BY ALL;
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+-------+---------+---------------+
| STATE |   CITY  | GROSS REVENUE |
+=======+=========+===============+
|   CA  | SF      |            22 |
+-------+---------+---------------+
|   CA  | SJ      |            44 |
+-------+---------+---------------+
|   FL  | Miami   |            80 |
+-------+---------+---------------+
|   FL  | Orlando |           160 |
+-------+---------+---------------+
|   PR  | SJ      |           320 |
+-------+---------+---------------+

Demonstrate Precedence When a Column Name and an Alias Match

It is possible (but usually a bad idea) to create a query that contains an alias that matches a column name:

SELECT x, some_expression AS x
  FROM ...
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If a GROUP BY clause contains a name that matches both a column name and an alias, then the GROUP BY clause uses the column name. This is demonstrated in the example below.

Create a table and insert rows:

Create table employees (salary float, state varchar, employment_state varchar);
insert into employees (salary, state, employment_state) values
    (60000, 'California', 'Active'),
    (70000, 'California', 'On leave'),
    (80000, 'Oregon', 'Active');
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The query below returns the sum of the salaries of the employees who are active and the sum of the salaries of the employees who are on leave.

select sum(salary), ANY_VALUE(employment_state)
    from employees
    group by employment_state;
+-------------+-----------------------------+
| SUM(SALARY) | ANY_VALUE(EMPLOYMENT_STATE) |
|-------------+-----------------------------|
|      140000 | Active                      |
|       70000 | On leave                    |
+-------------+-----------------------------+
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The query below uses the alias state, which matches the name of a column of a table in the query. When state is used in the GROUP BY, Snowflake interprets it as a reference to the column name, not the alias. This query therefore returns the sum of the salaries of the employees in the state of California and the sum of the salaries of the employees in the state of Oregon, yet displays employment_state information (e.g. “Active”) rather than the names of states or provinces.

select sum(salary), ANY_VALUE(employment_state) as state
    from employees
    group by state;
+-------------+--------+
| SUM(SALARY) | STATE  |
|-------------+--------|
|      130000 | Active |
|       80000 | Active |
+-------------+--------+
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