MERGE INTO Statement
The MERGE INTO statement is an alternative to INSERT INTO ... ON CONFLICT that doesn't need a primary key since it allows for a custom match condition. This is a very useful alternative for upserting use cases (INSERT + UPDATE) when the destination table does not have a primary key constraint.
Examples
First, let's create a simple table.
CREATE TABLE people (id INTEGER, name VARCHAR, salary FLOAT);
INSERT INTO people VALUES (1, 'John', 92_000.0), (2, 'Anna', 100_000.0);
The simplest upsert would be updating or inserting a whole row.
MERGE INTO people
USING (
SELECT
unnest([3, 1]) AS id,
unnest(['Sarah', 'John']) AS name,
unnest([95_000.0, 105_000.0]) AS salary
) AS upserts
ON (upserts.id = people.id)
WHEN MATCHED THEN UPDATE
WHEN NOT MATCHED THEN INSERT;
FROM people
ORDER BY id;
| id | name | salary |
|---|---|---|
| 1 | John | 105000.0 |
| 2 | Anna | 100000.0 |
| 3 | Sarah | 95000.0 |
In the previous example we are updating the whole row if id matches. However, it is also a common pattern to receive a change set with some keys and the changed value. This is a good use for SET. If the match condition uses a column that has the same name in the source and destination, the keyword USING can be used in the match condition.
MERGE INTO people
USING (
SELECT
1 AS id,
98_000.0 AS salary
) AS salary_updates
USING (id)
WHEN MATCHED THEN UPDATE SET salary = salary_updates.salary;
FROM people
ORDER BY id;
| id | name | salary |
|---|---|---|
| 1 | John | 98000.0 |
| 2 | Anna | 100000.0 |
| 3 | Sarah | 95000.0 |
Another common pattern is to receive a delete set of rows, which may only contain ids of rows to be deleted.
MERGE INTO people
USING (
SELECT
1 AS id,
) AS deletes
USING (id)
WHEN MATCHED THEN DELETE;
FROM people
ORDER BY id;
| id | name | salary |
|---|---|---|
| 2 | Anna | 100000.0 |
| 3 | Sarah | 95000.0 |
MERGE INTO also supports more complex conditions, for example, for a given delete set we can decide to only remove rows that contain a salary bigger or equal than a certain amount.
MERGE INTO people
USING (
SELECT
unnest([3, 2]) AS id,
) AS deletes
USING (id)
WHEN MATCHED AND people.salary >= 100_000.0 THEN DELETE;
FROM people
ORDER BY id;
| id | name | salary |
|---|---|---|
| 3 | Sarah | 95000.0 |
If needed, Goose also supports multiple UPDATE and DELETE conditions. The RETURNING clause can be used to indicate which rows were affected by the MERGE statement.
-- Let's get John back in!
INSERT INTO people VALUES (1, 'John', 105_000.0);
MERGE INTO people
USING (
SELECT
unnest([3, 1]) AS id,
unnest([89_000.0, 70_000.0]) AS salary
) AS upserts
USING (id)
WHEN MATCHED AND people.salary < 100_000.0 THEN UPDATE SET salary = upserts.salary
-- Second update or delete condition
WHEN MATCHED AND people.salary > 100_000.0 THEN DELETE
WHEN NOT MATCHED THEN INSERT BY NAME
RETURNING merge_action, *;
| merge_action | id | name | salary |
|---|---|---|---|
| UPDATE | 3 | Sarah | 89000.0 |
| DELETE | 1 | John | 105000.0 |
In some cases, you may want to perform a different action specifically if the source doesn't meet a condition. For example, if we expect that data that is not present on the source shouldn't be present in the target:
CREATE TABLE target AS
SELECT unnest([1,2]) AS id;
MERGE INTO target
USING (SELECT 1 AS id) source
USING (id)
WHEN MATCHED THEN UPDATE
WHEN NOT MATCHED BY SOURCE THEN DELETE
RETURNING merge_action, *;
| merge_action | id |
|---|---|
| UPDATE | 1 |
| DELETE | 2 |
There is also the possibility of specifying WHEN NOT MATCHED BY TARGET. However, the behavior is, as you may expect, the same as WHEN NOT MATCHED since by default when specifying conditions, we look at the target.