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angerszhu a98dc60408 [SPARK-33308][SQL] Refactor current grouping analytics 
### What changes were proposed in this pull request?
As discussed in
https://github.com/apache/spark/pull/30145#discussion_r514728642
https://github.com/apache/spark/pull/30145#discussion_r514734648

We need to rewrite current Grouping Analytics grammar to support  as flexible as Postgres SQL to support subsequent development.
In  postgres sql, it support
```
select a, b, c, count(1) from t group by cube (a, b, c);
select a, b, c, count(1) from t group by cube(a, b, c);
select a, b, c, count(1) from t group by cube (a, b, c, (a, b), (a, b, c));
select a, b, c, count(1) from t group by rollup(a, b, c);
select a, b, c, count(1) from t group by rollup (a, b, c);
select a, b, c, count(1) from t group by rollup (a, b, c, (a, b), (a, b, c));
```
In this pr,  we have done three things as below, and we will split it to different pr:

 - Refactor CUBE/ROLLUP (regarding them as ANTLR tokens in a parser)
 - Refactor GROUPING SETS (the logical node -> a new expr)
 - Support new syntax for CUBE/ROLLUP (e.g., GROUP BY CUBE ((a, b), (a, c)))

### Why are the changes needed?
Rewrite current Grouping Analytics grammar to support  as flexible as Postgres SQL to support subsequent development.

### Does this PR introduce _any_ user-facing change?
User can  write Grouping Analytics grammar as flexible as Postgres SQL to support subsequent development.

### How was this patch tested?
Added UT

Closes #30212 from AngersZhuuuu/refact-grouping-analytics.

Lead-authored-by: angerszhu <angers.zhu@gmail.com>
Co-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Co-authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-03-30 12:31:58 +00:00

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---
layout: global
title: GROUP BY Clause
displayTitle: GROUP BY Clause
license: |
Licensed to the Apache Software Foundation (ASF) under one or more
contributor license agreements. See the NOTICE file distributed with
this work for additional information regarding copyright ownership.
The ASF licenses this file to You under the Apache License, Version 2.0
(the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
---
### 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
```sql
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
```sql
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
```sql
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](sql-ref-syntax-qry-select.html)
* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
* [CASE Clause](sql-ref-syntax-qry-select-case.html)
* [PIVOT Clause](sql-ref-syntax-qry-select-pivot.html)
* [LATERAL VIEW Clause](sql-ref-syntax-qry-select-lateral-view.html)
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