How can I efficiently insert or update rows in a database table based on two conditions using a single SQL statement?

INSERT INTO or UPDATE with Two Conditions

This query involves the challenge of efficiently managing data in a table where new rows are inserted and existing rows need to be updated based on specific conditions. The table has the following schema:

ID INTEGER PRIMARY KEY AUTOINCREMENT
name INTEGER
values1 INTEGER
values2 INTEGER
dates DATE

The objective is to insert a new row when there is new data for a given 'name' and 'dates' combination. However, if a row with the same 'name' and 'dates' already exists, it should be updated instead of inserting a duplicate row.

An initial solution could involve the use of a Stored Procedure (SPROC) to check the condition and execute the appropriate action. However, as the data is being pushed from another language, this approach is not feasible.

The optimal solution lies in utilizing the INSERT INTO ... ON DUPLICATE KEY UPDATE syntax. This allows for a single statement to both insert new rows and update existing rows based on the specified conditions.

In this scenario, you can define a unique composite key (name, dates) on the table:

unique key(name,dates)

This unique key ensures that the combination of 'name' and 'dates' cannot exist in the table more than once. When executing the INSERT query, you can use the ON DUPLICATE KEY UPDATE clause to specify the action to be taken if a unique key violation occurs:

INSERT INTO myThing (name, values1, values2, dates)
VALUES (777, 1, 1, '2015-07-11')
ON DUPLICATE KEY UPDATE values2 = values2 + 1;

With this approach, if a row with the 'name' and 'dates' provided already exists, its values2 column will be incremented instead of creating a new row. This behavior effectively updates the existing row with the new data.

To illustrate the functionality, consider the following example:

-- Create the table with the composite unique key
CREATE TABLE myThing (
    id INT AUTO_INCREMENT PRIMARY KEY,
    name INT NOT NULL,
    values1 INT NOT NULL,
    values2 INT NOT NULL,
    dates DATE NOT NULL,
    UNIQUE KEY (name, dates)
);

-- Insert a new row or update an existing row
INSERT INTO myThing (name, values1, values2, dates)
VALUES (777, 1, 1, '2015-07-11')
ON DUPLICATE KEY UPDATE values2 = values2 + 1;

-- Insert another new row or update the existing row for 'name' 777
INSERT INTO myThing (name, values1, values2, dates)
VALUES (777, 1, 1, '2015-07-11')
ON DUPLICATE KEY UPDATE values2 = values2 + 1;

-- Insert a new row for 'name' 778
INSERT INTO myThing (name, values1, values2, dates)
VALUES (778, 1, 1, '2015-07-11')
ON DUPLICATE KEY UPDATE values2 = values2 + 1;

-- Retrieve the results
SELECT * FROM myThing;

This will produce the following output:

+----+------+---------+---------+------------+
| id | name | values1 | values2 | dates      |
+----+------+---------+---------+------------+
| 1  | 777  | 1       | 2       | 2015-07-11 |
| 2  | 778  | 1       | 1       | 2015-07-11 |
+----+------+---------+---------+------------+

As evident, the row for 'name' 777 was updated with the new data, while a new row was created for 'name' 778.

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