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AVG

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Calculate the average value from a set of numbers.

NULL values are ignored. If no values can be averaged, this function returns NULL.

May be used as a window function and with the frame clause.

Syntax

Aggregate Function

AVG ( [DISTINCT] expression )

Window Function & Window Frame Clause

AVG( [ DISTINCT ] ( ) OVER (
     [ PARTITION BY (col | expr), ...] 
     [ORDER BY (col | expr), ...] [ <window_frame> ]
)

Arguments

  • DISTINCT: optional keyword. If present, will average the unique values.

  • expression: any numerical expression. This may be a column name, the result of another function, or a math operation

Return Type

A double if the input type is double, otherwise decimal.

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 AVG(yearly_total) FROM player_scores;
+-------------------+
| AVG(yearly_total) |
+-------------------+
|        314.914286 |
+-------------------+
SELECT AVG(yearly_total), (player_name) FROM player_scores GROUP BY player_name;
+-------------------+-------------+
| AVG(yearly_total) | player_name |
+-------------------+-------------+
|        327.300000 | June        |
|        348.500000 | Jack        |
|        369.100000 | Eve         |
|        202.500000 | Steve       |
|        378.300000 | Martin      |
|        271.600000 | Jim         |
|        307.100000 | Shelia      |
+-------------------+-------------+

Window Function

SELECT player_id, avg(1st_qtr_score), avg(2nd_qtr_score), avg(3rd_qtr_score), avg(4th_qtr_score)
OVER (PARTITION BY player_id)
FROM player_scores
GROUP BY player_id
ORDER BY player_id;
+-----------+--------------------+--------------------+--------------------+--------------------------+
| player_id | avg(1st_qtr_score) | avg(2nd_qtr_score) | avg(3rd_qtr_score) | avg(4th_qtr_score) OVER  |
|           |                    |                    |                    | (partition by player_id) |
+-----------+--------------------+--------------------+--------------------+--------------------------+
| 119       |          22.500000 |          72.000000 |          63.000000 |                45.000000 |
| 189       |          91.500000 |          88.100000 |          95.000000 |                94.500000 |
| 338       |          75.600000 |          72.000000 |          81.100000 |                78.400000 |
| 432       |          90.100000 |          78.000000 |          88.200000 |                92.200000 |
| 521       |          81.000000 |          87.300000 |          76.800000 |                82.200000 |
| 674       |          98.800000 |          95.100000 |          88.000000 |                96.400000 |
| 779       |          75.000000 |          68.900000 |          55.700000 |                72.000000 |
+-----------+--------------------+--------------------+--------------------+--------------------------+
CREATE TABLE avg_tick_table(TIMESTAMP DATETIME(6), symbol VARCHAR(5), comp_name VARCHAR (30), price NUMERIC(18,4));


INSERT INTO avg_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, AVG(price) OVER (PARTITION BY symbol) FROM avg_tick_table GROUP BY TIMESTAMP;
+----------------------------+--------+----------+---------------------------------------+
| TIMESTAMP                  | symbol | price    | AVG(price) OVER (PARTITION BY symbol) |
+----------------------------+--------+----------+---------------------------------------+
| 2022-11-18 10:55:50.000000 | AME    | 208.0000 |                          209.00000000 |
| 2022-11-18 10:55:52.000000 | AME    | 210.0000 |                          209.00000000 |
| 2022-11-18 10:55:57.000000 | OCO    |  21.0000 |                           22.50000000 |
| 2022-11-18 10:56:00.000000 | OCO    |  23.0000 |                           22.50000000 |
| 2022-11-18 10:56:03.000000 | OCO    |  24.0000 |                           22.50000000 |
| 2022-11-18 10:55:55.000000 | OCO    |  22.0000 |                           22.50000000 |
| 2022-11-18 10:55:36.000000 | STC    | 100.0000 |                          102.00000000 |
| 2022-11-18 10:55:48.000000 | STC    | 101.0000 |                          102.00000000 |
| 2022-11-18 10:55:42.000000 | STC    | 105.0000 |                          102.00000000 |
| 2022-11-18 10:55:37.000000 | STC    | 102.0000 |                          102.00000000 |
+----------------------------+--------+----------+---------------------------------------+

Window Frame Clause

CREATE TABLE avg_table(col_a INT, col_b DECIMAL(4,2),
   col_c DECIMAL(4,2), col_d VARCHAR(15), col_e INT);


INSERT INTO avg_table VALUES(1, 1.1, 11.17, 'one', 47),
(2, 2.2, 22.21, 'two', NULL),
(NULL, 3.3, 33.32, 'three', 892),
(4, 4.4, 44.43, 'four', NULL),
(5, 5.5, 55.54, 'five', 1102),
(6, NULL, 66.65, 'six', NULL);
SELECT col_a, col_b, col_c, col_d, col_e,
AVG(col_e) OVER
(PARTITION BY col_a ORDER BY col_b rows between UNBOUNDED PRECEDING
and CURRENT ROW) avg_col_e_rows_pre
FROM avg_table
ORDER BY col_a;
+-------+-------+-------+-------+-------+--------------------+
| col_a | col_b | col_c | col_d | col_e | avg_col_e_rows_pre |
+-------+-------+-------+-------+-------+--------------------+
|  NULL |  3.30 | 33.32 | three |   892 |           892.0000 |
|     1 |  1.10 | 11.17 | one   |    47 |            47.0000 |
|     2 |  2.20 | 22.21 | two   |  NULL |               NULL |
|     4 |  4.40 | 44.43 | four  |  NULL |               NULL |
|     5 |  5.50 | 55.54 | five  |  1102 |          1102.0000 |
|     6 |  NULL | 66.65 | six   |  NULL |               NULL |
+-------+-------+-------+-------+-------+--------------------+
SELECT TIMESTAMP, symbol, price,
AVG(price) OVER (PARTITION BY symbol
ROWS between 1 PRECEDING
and CURRENT ROW) AS AVG_2,
AVG(price) OVER (ORDER BY TIMESTAMP
ROWS between 2 PRECEDING
and CURRENT ROW) AS AVG_3
FROM avg_tick_table;
+----------------------------+--------+----------+--------------+--------------+
| TIMESTAMP                  | symbol | price    | AVG_2        | AVG_3        |
+----------------------------+--------+----------+--------------+--------------+
| 2022-11-18 10:55:36.000000 | STC    | 100.0000 | 100.50000000 | 100.00000000 |
| 2022-11-18 10:55:37.000000 | STC    | 102.0000 | 103.50000000 | 101.00000000 |
| 2022-11-18 10:55:42.000000 | STC    | 105.0000 | 105.00000000 | 102.33333333 |
| 2022-11-18 10:55:42.000000 | AME    | 198.0000 | 204.50000000 | 135.00000000 |
| 2022-11-18 10:55:48.000000 | STC    | 101.0000 | 101.50000000 | 134.66666667 |
| 2022-11-18 10:55:50.000000 | AME    | 208.0000 | 203.00000000 | 169.00000000 |
| 2022-11-18 10:55:52.000000 | OCO    |  21.0000 |  22.00000000 | 110.00000000 |
| 2022-11-18 10:55:52.000000 | AME    | 210.0000 | 210.00000000 | 146.33333333 |
| 2022-11-18 10:55:55.000000 | OCO    |  22.0000 |  23.00000000 |  84.33333333 |
| 2022-11-18 10:55:55.000000 | AME    | 211.0000 | 210.50000000 | 147.66666667 |
| 2022-11-18 10:55:57.000000 | OCO    |  21.0000 |  21.00000000 |  84.66666667 |
| 2022-11-18 10:56:00.000000 | OCO    |  23.0000 |  22.50000000 |  85.00000000 |
| 2022-11-18 10:56:03.000000 | STC    |  99.0000 |  99.50000000 |  47.66666667 |
| 2022-11-18 10:56:03.000000 | OCO    |  24.0000 |  24.00000000 |  48.66666667 |
+----------------------------+--------+----------+--------------+--------------+

Last modified: May 31, 2023

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Verification instructions

Note: You must install cosign to verify the authenticity of the SingleStore file.

Use the following steps to verify the authenticity of singlestoredb-server, singlestoredb-toolbox, singlestoredb-studio, and singlestore-client SingleStore files that have been downloaded.

You may perform the following steps on any computer that can run cosign, such as the main deployment host of the cluster.

  1. (Optional) Run the following command to view the associated signature files.

    curl undefined

  2. Download the signature file from the SingleStore release server.

    • Option 1: Click the Download Signature button next to the SingleStore file.

    • Option 2: Copy and paste the following URL into the address bar of your browser and save the signature file.

    • Option 3: Run the following command to download the signature file.

      curl -O undefined

  3. After the signature file has been downloaded, run the following command to verify the authenticity of the SingleStore file.

    echo -n undefined |
        cosign verify-blob --certificate-oidc-issuer https://oidc.eks.us-east-1.amazonaws.com/id/CCDCDBA1379A5596AB5B2E46DCA385BC \
          --certificate-identity https://kubernetes.io/namespaces/freya-production/serviceaccounts/job-worker \
          --bundle undefined \
          --new-bundle-format -
    Verified OK