MIN
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Returns the lowest value observed in all rows in an aggregation.
Lowest
is determined by the collation rules of the data passed in.
May be used as a window function and with the frame clause.
Note
This aggregate function is not to be confused with LEAST, which is a non-aggregate function returning the lowest value in its list of arguments.
Syntax
Aggregate Function
MIN ( expression )
Window Function & Window Frame Clause
MIN(expr) [ OVER ( [ PARTITION BY expr ] [ ORDER BY expr [<window_frame>] ] )]
Arguments
-
expression: any expression.
This may be a column name, the result of another function, or a math operation.
Return Type
The lowest value, in the type of the input.
Examples
CREATE TABLE player_scores(player_name VARCHAR(50), player_id VARCHAR(10),1st_qtr_score DECIMAL(5,2), 2nd_qtr_score DECIMAL(5,2),3rd_qtr_score DECIMAL(5,2), 4th_qtr_score DECIMAL(5,2),yearly_total AS 1st_qtr_score + 2nd_qtr_score + 3rd_qtr_score + 4th_qtr_score PERSISTED DECIMAL(5,2));INSERT INTO player_scores VALUES('Steve', '119','22.50','72.00', '63.00', '45.00'),('Jack', '432', '90.10', '78.00','88.20', '92.20'),('Jim', '779','75.00', '68.90','55.70', '72.00'),('Eve', '189','91.50', '88.10', '95.00', '94.50'),('Shelia','338', '75.60', '72.00', '81.10', '78.40'),('June', '521', '81.00', '87.30','76.80','82.20'),('Martin', '674','98.80', '95.10', '88.00', '96.40');
Aggregate Function
SELECT MIN(player_id) FROM player_scores;
+-----------------+
| MIN (player_id) |
+-----------------+
| 119 |
+-----------------+SELECT MIN(player_name) FROM player_scores;
+------------------+
| MIN(player_name) |
+------------------+
| Eve |
+------------------+Window Function
SELECT player_name, 1st_qtr_score, 2nd_qtr_score, MIN(2nd_qtr_score)OVER (partition by 1st_qtr_score) FROM player_scores ORDER BY 2nd_qtr_score, 1st_qtr_score;
+-------------+---------------+---------------+-----------------------------------+
| player_name | 1st_qtr_score | 2nd_qtr_score | MIN(2nd_qtr_score) |
| | | | OVER (partition by 1st_qtr_score) |
+-------------+---------------+---------------+-----------------------------------+
| Jim | 75.00 | 68.90 | 68.90 |
| Steve | 22.50 | 72.00 | 72.00 |
| Shelia | 75.60 | 72.00 | 72.00 |
| Jack | 90.10 | 78.00 | 78.00 |
| June | 81.00 | 87.30 | 87.30 |
| Eve | 91.50 | 88.10 | 88.10 |
| Martin | 98.80 | 95.10 | 95.10 |
+-------------+---------------+---------------+-----------------------------------+CREATE TABLE tick_table(TIMESTAMP DATETIME(6), symbol VARCHAR(5), comp_name VARCHAR (30), price NUMERIC(18,4));INSERT INTO tick_table VALUES('2022-11-18 10:55:36.000000','STC','SomeTechCo', 100.00),('2022-11-18 10:55:37.000000','STC','SomeTechCo', 102.00),('2022-11-18 10:55:42.000000', 'STC', 'SomeTechCo', 105.00),('2022-11-18 10:55:48.000000', 'STC', 'SomeTechCo', 101.00),('2022-11-18 10:56:03.000000', 'STC', 'SomeTechCo', 99.00),('2022-11-18 10:55:42.000000', 'AME', 'ACME', 198.00),('2022-11-18 10:55:50.000000', 'AME', 'ACME', 208.00),('2022-11-18 10:55:52.000000', 'AME', 'ACME', 210.00),('2022-11-18 10:55:55.000000', 'AME', 'ACME', 211.00),('2022-11-18 10:55:52.000000', 'OCO', 'OnCallCo', 21.00),('2022-11-18 10:55:55.000000', 'OCO', 'OnCallCo', 22.00),('2022-11-18 10:55:57.000000', 'OCO', 'OnCallCo', 21.00),('2022-11-18 10:56:00.000000', 'OCO', 'OnCallCo', 23.00),('2022-11-18 10:56:03.000000', 'OCO', 'OnCallCo', 24.00);
SELECT TIMESTAMP, symbol, price, MIN(price) OVER (PARTITION BY symbol)FROM tick_table GROUP BY TIMESTAMP;
+----------------------------+--------+----------+---------------------------------------+
| TIMESTAMP | symbol | price | MIN(price) OVER (PARTITION BY symbol) |
+----------------------------+--------+----------+---------------------------------------+
| 2022-11-18 10:55:50.000000 | AME | 208.0000 | 208.0000 |
| 2022-11-18 10:55:55.000000 | OCO | 22.0000 | 21.0000 |
| 2022-11-18 10:55:52.000000 | OCO | 21.0000 | 21.0000 |
| 2022-11-18 10:56:00.000000 | OCO | 23.0000 | 21.0000 |
| 2022-11-18 10:55:57.000000 | OCO | 21.0000 | 21.0000 |
| 2022-11-18 10:55:42.000000 | STC | 105.0000 | 99.0000 |
| 2022-11-18 10:55:37.000000 | STC | 102.0000 | 99.0000 |
| 2022-11-18 10:55:48.000000 | STC | 101.0000 | 99.0000 |
| 2022-11-18 10:55:36.000000 | STC | 100.0000 | 99.0000 |
| 2022-11-18 10:56:03.000000 | STC | 99.0000 | 99.0000 |
+----------------------------+--------+----------+---------------------------------------+Window Frame Clause
SELECT player_name, 1st_qtr_score, 2nd_qtr_score,min(1st_qtr_score) OVER (ORDER BY 1st_qtr_score, 2nd_qtr_score ROWS between 1 PRECEDING and CURRENT ROW)FROM player_scoresORDER BY player_name, 1st_qtr_score, 2nd_qtr_score;
+-------------+---------------+---------------+-------------------------------------------+
| player_name | 1st_qtr_score | 2nd_qtr_score | min(1st_qtr_score) OVER |
| | | | (ORDER BY 1st_qtr_score, 2nd_qtr_score |
| | | | ROWS between 1 PRECEDING and CURRENT ROW) |
+-------------+---------------+---------------+-------------------------------------------+
| Eve | 91.50 | 88.10 | 90.10 |
| Jack | 90.10 | 78.00 | 81.00 |
| Jim | 75.00 | 68.90 | 22.50 |
| June | 81.00 | 87.30 | 75.60 |
| Martin | 98.80 | 95.10 | 91.50 |
| Shelia | 75.60 | 72.00 | 75.00 |
| Steve | 22.50 | 72.00 | 22.50 |
+-------------+---------------+---------------+-------------------------------------------+Last modified: April 4, 2023