spark-instrumented-optimizer/docs/sql-ref-syntax-qry-select-groupby.md

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Description

The GROUP BY clause is used to group the rows based on a set of specified grouping expressions and compute aggregations on the group of rows based on one or more specified aggregate functions. Spark also supports advanced aggregations to do multiple aggregations for the same input record set via GROUPING SETS, CUBE, ROLLUP clauses. When a FILTER clause is attached to an aggregate function, only the matching rows are passed to that function.

Syntax

GROUP BY group_expression [ , group_expression [ , ... ] ]
    [ { WITH ROLLUP | WITH CUBE | GROUPING SETS (grouping_set [ , ...]) } ]

GROUP BY { group_expression | { ROLLUP | CUBE | GROUPING SETS } (grouping_set [ , ...]) } [ , ... ]

While aggregate functions are defined as

aggregate_name ( [ DISTINCT ] expression [ , ... ] ) [ FILTER ( WHERE boolean_expression ) ]

Parameters

• grouping_expression

  Specifies the criteria based on which the rows are grouped together. The grouping of rows is performed based on result values of the grouping expressions. A grouping expression may be a column name like GROUP BY a, a column position like GROUP BY 0, or an expression like GROUP BY a + b.

• grouping_set

  A grouping set is specified by zero or more comma-separated expressions in parentheses. When the grouping set has only one element, parentheses can be omitted. For example, GROUPING SETS ((a), (b)) is the same as GROUPING SETS (a, b).

  Syntax: { ( [ expression [ , ... ] ] ) | expression }

• GROUPING SETS

  Groups the rows for each grouping set specified after GROUPING SETS. For example, GROUP BY GROUPING SETS ((warehouse), (product)) is semantically equivalent to union of results of GROUP BY warehouse and GROUP BY product. This clause is a shorthand for a UNION ALL where each leg of the UNION ALL operator performs aggregation of each grouping set specified in the GROUPING SETS clause. Similarly, GROUP BY GROUPING SETS ((warehouse, product), (product), ()) is semantically equivalent to the union of results of GROUP BY warehouse, product, GROUP BY product and global aggregate.

• ROLLUP

  Specifies multiple levels of aggregations in a single statement. This clause is used to compute aggregations based on multiple grouping sets. ROLLUP is a shorthand for GROUPING SETS. For example, GROUP BY warehouse, product WITH ROLLUP or GROUP BY ROLLUP(warehouse, product) is equivalent to GROUP BY GROUPING SETS((warehouse, product), (warehouse), ()). GROUP BY ROLLUP(warehouse, product, (warehouse, location)) is equivalent to GROUP BY GROUPING SETS((warehouse, product, location), (warehouse, product), (warehouse), ()). The N elements of a ROLLUP specification results in N+1 GROUPING SETS.

• CUBE

  CUBE clause is used to perform aggregations based on combination of grouping columns specified in the GROUP BY clause. CUBE is a shorthand for GROUPING SETS. For example, GROUP BY warehouse, product WITH CUBE or GROUP BY CUBE(warehouse, product) is equivalent to GROUP BY GROUPING SETS((warehouse, product), (warehouse), (product), ()). GROUP BY CUBE(warehouse, product, (warehouse, location)) is equivalent to GROUP BY GROUPING SETS((warehouse, product, location), (warehouse, product), (warehouse, location), (product, warehouse, location), (warehouse), (product), (warehouse, product), ()). The N elements of a CUBE specification results in 2^N GROUPING SETS.

• aggregate_name

  Specifies an aggregate function name (MIN, MAX, COUNT, SUM, AVG, etc.).

• DISTINCT

  Removes duplicates in input rows before they are passed to aggregate functions.

• FILTER

  Filters the input rows for which the boolean_expression in the WHERE clause evaluates to true are passed to the aggregate function; other rows are discarded.

Examples

CREATE TABLE dealer (id INT, city STRING, car_model STRING, quantity INT);
INSERT INTO dealer VALUES
    (100, 'Fremont', 'Honda Civic', 10),
    (100, 'Fremont', 'Honda Accord', 15),
    (100, 'Fremont', 'Honda CRV', 7),
    (200, 'Dublin', 'Honda Civic', 20),
    (200, 'Dublin', 'Honda Accord', 10),
    (200, 'Dublin', 'Honda CRV', 3),
    (300, 'San Jose', 'Honda Civic', 5),
    (300, 'San Jose', 'Honda Accord', 8);

-- Sum of quantity per dealership. Group by `id`.
SELECT id, sum(quantity) FROM dealer GROUP BY id ORDER BY id;
+---+-------------+
| id|sum(quantity)|
+---+-------------+
|100|           32|
|200|           33|
|300|           13|
+---+-------------+

-- Use column position in GROUP by clause.
SELECT id, sum(quantity) FROM dealer GROUP BY 1 ORDER BY 1;
+---+-------------+
| id|sum(quantity)|
+---+-------------+
|100|           32|
|200|           33|
|300|           13|
+---+-------------+

-- Multiple aggregations.
-- 1. Sum of quantity per dealership.
-- 2. Max quantity per dealership.
SELECT id, sum(quantity) AS sum, max(quantity) AS max FROM dealer GROUP BY id ORDER BY id;
+---+---+---+
| id|sum|max|
+---+---+---+
|100| 32| 15|
|200| 33| 20|
|300| 13|  8|
+---+---+---+

-- Count the number of distinct dealer cities per car_model.
SELECT car_model, count(DISTINCT city) AS count FROM dealer GROUP BY car_model;
+------------+-----+
|   car_model|count|
+------------+-----+
| Honda Civic|    3|
|   Honda CRV|    2|
|Honda Accord|    3|
+------------+-----+

-- Sum of only 'Honda Civic' and 'Honda CRV' quantities per dealership.
SELECT id, sum(quantity) FILTER (
            WHERE car_model IN ('Honda Civic', 'Honda CRV')
        ) AS `sum(quantity)` FROM dealer
    GROUP BY id ORDER BY id;
+---+-------------+
| id|sum(quantity)|
+---+-------------+
|100|           17|
|200|           23|
|300|            5|
+---+-------------+

-- Aggregations using multiple sets of grouping columns in a single statement.
-- Following performs aggregations based on four sets of grouping columns.
-- 1. city, car_model
-- 2. city
-- 3. car_model
-- 4. Empty grouping set. Returns quantities for all city and car models.
SELECT city, car_model, sum(quantity) AS sum FROM dealer
    GROUP BY GROUPING SETS ((city, car_model), (city), (car_model), ())
    ORDER BY city;
+---------+------------+---+
|     city|   car_model|sum|
+---------+------------+---+
|     null|        null| 78|
|     null| HondaAccord| 33|
|     null|    HondaCRV| 10|
|     null|  HondaCivic| 35|
|   Dublin|        null| 33|
|   Dublin| HondaAccord| 10|
|   Dublin|    HondaCRV|  3|
|   Dublin|  HondaCivic| 20|
|  Fremont|        null| 32|
|  Fremont| HondaAccord| 15|
|  Fremont|    HondaCRV|  7|
|  Fremont|  HondaCivic| 10|
| San Jose|        null| 13|
| San Jose| HondaAccord|  8|
| San Jose|  HondaCivic|  5|
+---------+------------+---+

-- Alternate syntax for `GROUPING SETS` in which both `GROUP BY` and `GROUPING SETS`
-- specifications are present.
SELECT city, car_model, sum(quantity) AS sum FROM dealer
    GROUP BY city, car_model GROUPING SETS ((city, car_model), (city), (car_model), ())
    ORDER BY city, car_model;
+---------+------------+---+
|     city|   car_model|sum|
+---------+------------+---+
|     null|        null| 78|
|     null| HondaAccord| 33|
|     null|    HondaCRV| 10|
|     null|  HondaCivic| 35|
|   Dublin|        null| 33|
|   Dublin| HondaAccord| 10|
|   Dublin|    HondaCRV|  3|
|   Dublin|  HondaCivic| 20|
|  Fremont|        null| 32|
|  Fremont| HondaAccord| 15|
|  Fremont|    HondaCRV|  7|
|  Fremont|  HondaCivic| 10|
| San Jose|        null| 13|
| San Jose| HondaAccord|  8|
| San Jose|  HondaCivic|  5|
+---------+------------+---+

-- Group by processing with `ROLLUP` clause.
-- Equivalent GROUP BY GROUPING SETS ((city, car_model), (city), ())
SELECT city, car_model, sum(quantity) AS sum FROM dealer
    GROUP BY city, car_model WITH ROLLUP
    ORDER BY city, car_model;
+---------+------------+---+
|     city|   car_model|sum|
+---------+------------+---+
|     null|        null| 78|
|   Dublin|        null| 33|
|   Dublin| HondaAccord| 10|
|   Dublin|    HondaCRV|  3|
|   Dublin|  HondaCivic| 20|
|  Fremont|        null| 32|
|  Fremont| HondaAccord| 15|
|  Fremont|    HondaCRV|  7|
|  Fremont|  HondaCivic| 10|
| San Jose|        null| 13|
| San Jose| HondaAccord|  8|
| San Jose|  HondaCivic|  5|
+---------+------------+---+

-- Group by processing with `CUBE` clause.
-- Equivalent GROUP BY GROUPING SETS ((city, car_model), (city), (car_model), ())
SELECT city, car_model, sum(quantity) AS sum FROM dealer
    GROUP BY city, car_model WITH CUBE
    ORDER BY city, car_model;
+---------+------------+---+
|     city|   car_model|sum|
+---------+------------+---+
|     null|        null| 78|
|     null| HondaAccord| 33|
|     null|    HondaCRV| 10|
|     null|  HondaCivic| 35|
|   Dublin|        null| 33|
|   Dublin| HondaAccord| 10|
|   Dublin|    HondaCRV|  3|
|   Dublin|  HondaCivic| 20|
|  Fremont|        null| 32|
|  Fremont| HondaAccord| 15|
|  Fremont|    HondaCRV|  7|
|  Fremont|  HondaCivic| 10|
| San Jose|        null| 13|
| San Jose| HondaAccord|  8|
| San Jose|  HondaCivic|  5|
+---------+------------+---+

--Prepare data for ignore nulls example
CREATE TABLE person (id INT, name STRING, age INT);
INSERT INTO person VALUES
    (100, 'Mary', NULL),
    (200, 'John', 30),
    (300, 'Mike', 80),
    (400, 'Dan', 50);

--Select the first row in column age
SELECT FIRST(age) FROM person;
+--------------------+
| first(age, false)  |
+--------------------+
| NULL               |
+--------------------+

--Get the first row in column `age` ignore nulls,last row in column `id` and sum of column `id`.
SELECT FIRST(age IGNORE NULLS), LAST(id), SUM(id) FROM person;
+-------------------+------------------+----------+
| first(age, true)  | last(id, false)  | sum(id)  |
+-------------------+------------------+----------+
| 30                | 400              | 1000     |
+-------------------+------------------+----------+

Related Statements

• SELECT Main
• WHERE Clause
• HAVING Clause
• ORDER BY Clause
• SORT BY Clause
• CLUSTER BY Clause
• DISTRIBUTE BY Clause
• LIMIT Clause
• CASE Clause
• PIVOT Clause
• LATERAL VIEW Clause