Subqueries
Version 0.9.2

Scalar Subquery

Scalar subqueries are subqueries that return a single value. They can be used anywhere where a regular expression can be used. If a scalar subquery returns more than a single value, the first value returned will be used.

Consider the following table:

7 Math
9 Math
8 CS
``````CREATE TABLE grades(grade INTEGER, course VARCHAR);
INSERT INTO grades VALUES (7, 'Math'), (9, 'Math'), (8, 'CS');
``````

We can run the following query to obtain the minimum grade:

``````SELECT MIN(grade) FROM grades;
-- {7}
``````

By using a scalar subquery in the `WHERE` clause, we can figure out for which course this grade was obtained:

``````SELECT course FROM grades WHERE grade = (SELECT MIN(grade) FROM grades);
-- {Math}
``````

Exists

The `EXISTS` operator tests for the existence of any row inside the subquery. It returns either true when the subquery returns one or more records, and false otherwise. The `EXISTS` operator is generally the most useful as a correlated subquery to express semijoin operations. However, it can be used as an uncorrelated subquery as well.

For example, we can use it to figure out if there are any grades present for a given course:

``````SELECT EXISTS (SELECT * FROM grades WHERE course='Math');
-- true

SELECT EXISTS (SELECT * FROM grades WHERE course='History');
-- false
``````

Not exists

The `NOT EXISTS` operator tests for the absence of any row inside the subquery. It returns either true when the subquery returns an empty result, and false otherwise. The `NOT EXISTS` operator is generally the most useful as a correlated subquery to express antijoin operations. For example, to find Person nodes without an interest:

``````CREATE TABLE Person(id BIGINT, name VARCHAR);
CREATE TABLE interest(PersonId BIGINT, topic VARCHAR);

INSERT INTO Person VALUES (1, 'Jane'), (2, 'Joe');
INSERT INTO interest VALUES (2, 'Music');

SELECT *
FROM Person
WHERE NOT EXISTS (SELECT * FROM interest WHERE interest.PersonId = Person.id);
``````
``````┌───────┬─────────┐
│  id   │  name   │
│ int64 │ varchar │
├───────┼─────────┤
│     1 │ Jane    │
└───────┴─────────┘
``````

DuckDB automatically detects when a `NOT EXISTS` query expresses an antijoin operation. There is no need to manually rewrite such queries to use `LEFT OUTER JOIN ... WHERE ... IS NULL`.

In Operator

The `IN` operator checks containment of the left expression inside the result defined by the subquery or the set of expressions on the right hand side (RHS). The `IN` operator returns true if the expression is present in the RHS, false if the expression is not in the RHS and the RHS has no `NULL` values, or `NULL` if the expression is not in the RHS and the RHS has `NULL` values.

We can use the `IN` operator in a similar manner as we used the `EXISTS` operator:

``````SELECT 'Math' IN (SELECT course FROM grades);
-- true

``````

Correlated Subqueries

All the subqueries presented here so far have been uncorrelated subqueries, where the subqueries themselves are entirely self-contained and can be run without the parent query. There exists a second type of subqueries called correlated subqueries. For correlated subqueries, the subquery uses values from the parent subquery.

Conceptually, the subqueries are run once for every single row in the parent query. Perhaps a simple way of envisioning this is that the correlated subquery is a function that is applied to every row in the source data set.

For example, suppose that we want to find the minimum grade for every course. We could do that as follows:

``````SELECT *
-- {7, Math}, {8, CS}
``````

The subquery uses a column from the parent query (`grades_parent.course`). Conceptually, we can see the subquery as a function where the correlated column is a parameter to that function:

``````SELECT MIN(grade) FROM grades WHERE course=?;
``````

Now when we execute this function for each of the rows, we can see that for `Math` this will return `7`, and for `CS` it will return `8`. We then compare it against the grade for that actual row. As a result, the row `(Math, 9)` will be filtered out, as `9 <> 7`.

Returning Each Row of the Subquery as a Struct

Using the name of a subquery in the `SELECT` clause (without referring to a specific column) turns each row of the subquery into a struct whose fields correspond to the columns of the subquery. For example:

``````SELECT t FROM (SELECT unnest(generate_series(41, 43)) AS x, 'hello' AS y) t;
``````
``````┌─────────────────────────────┐
│              t              │
│ struct(x bigint, y varchar) │
├─────────────────────────────┤
│ {'x': 41, 'y': hello}       │
│ {'x': 42, 'y': hello}       │
│ {'x': 43, 'y': hello}       │
└─────────────────────────────┘
``````
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