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# SELECT syntax

The queries in DataFusion scan data from tables and return 0 or more rows.
Please be aware that column names in queries are made lower-case, but not on the inferred schema. Accordingly, if you
want to query against a capitalized field, make sure to use double quotes. Please see this
[example](https://datafusion.apache.org/user-guide/example-usage.html) for clarification.
In this documentation we describe the SQL syntax in DataFusion.

DataFusion supports the following syntax for queries:
<code class="language-sql hljs">

[ [WITH](#with-clause) with_query [, ...] ] <br/>
[SELECT](#select-clause) [ ALL | DISTINCT ] select_expr [, ...] <br/>
[ [FROM](#from-clause) from_item [, ...] ] <br/>
[ [JOIN](#join-clause) join_item [, ...] ] <br/>
[ [WHERE](#where-clause) condition ] <br/>
[ [GROUP BY](#group-by-clause) grouping_element [, ...] ] <br/>
[ [HAVING](#having-clause) condition] <br/>
[ [QUALIFY](#qualify-clause) condition] <br/>
[ [UNION](#union-clause) [ ALL | select ] <br/>
[ [ORDER BY](#order-by-clause) expression [ ASC | DESC ][, ...] ] <br/>
[ [LIMIT](#limit-clause) count ] <br/>
[ [EXCLUDE | EXCEPT](#exclude-and-except-clause) ] <br/>
[Pipe operators](#pipe-operators) <br/>

</code>

## WITH clause

A with clause allows to give names for queries and reference them by name.

```sql
WITH x AS (SELECT a, MAX(b) AS b FROM t GROUP BY a)
SELECT a, b FROM x;
```

## SELECT clause

Example:

```sql
SELECT a, b, a + b FROM table
```

The `DISTINCT` quantifier can be added to make the query return all distinct rows.
By default `ALL` will be used, which returns all the rows.

```sql
SELECT DISTINCT person, age FROM employees
```

## FROM clause

Example:

```sql
SELECT t.a FROM table AS t
```

## WHERE clause

Example:

```sql
SELECT a FROM table WHERE a > 10
```

## JOIN clause

DataFusion supports `INNER JOIN`, `LEFT OUTER JOIN`, `RIGHT OUTER JOIN`, `FULL OUTER JOIN`, `NATURAL JOIN`, `CROSS JOIN`, `LEFT SEMI JOIN`, `RIGHT SEMI JOIN`, `LEFT ANTI JOIN`, `RIGHT ANTI JOIN`, and `LATERAL JOIN`.

The following examples are based on this table:

```sql
select * from x;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
| 1        | 2        |
+----------+----------+
```

### INNER JOIN

The keywords `JOIN` or `INNER JOIN` define a join that only shows rows where there is a match in both tables.

```sql
SELECT * FROM x INNER JOIN x y ON x.column_1 = y.column_1;
+----------+----------+----------+----------+
| column_1 | column_2 | column_1 | column_2 |
+----------+----------+----------+----------+
| 1        | 2        | 1        | 2        |
+----------+----------+----------+----------+
```

### LEFT OUTER JOIN

The keywords `LEFT JOIN` or `LEFT OUTER JOIN` define a join that includes all rows from the left table even if there
is not a match in the right table. When there is no match, null values are produced for the right side of the join.

```sql
SELECT * FROM x LEFT JOIN x y ON x.column_1 = y.column_2;
+----------+----------+----------+----------+
| column_1 | column_2 | column_1 | column_2 |
+----------+----------+----------+----------+
| 1        | 2        |          |          |
+----------+----------+----------+----------+
```

### RIGHT OUTER JOIN

The keywords `RIGHT JOIN` or `RIGHT OUTER JOIN` define a join that includes all rows from the right table even if there
is not a match in the left table. When there is no match, null values are produced for the left side of the join.

```sql
SELECT * FROM x RIGHT JOIN x y ON x.column_1 = y.column_2;
+----------+----------+----------+----------+
| column_1 | column_2 | column_1 | column_2 |
+----------+----------+----------+----------+
|          |          | 1        | 2        |
+----------+----------+----------+----------+
```

### FULL OUTER JOIN

The keywords `FULL JOIN` or `FULL OUTER JOIN` define a join that is effectively a union of a `LEFT OUTER JOIN` and
`RIGHT OUTER JOIN`. It will show all rows from the left and right side of the join and will produce null values on
either side of the join where there is not a match.

```sql
SELECT * FROM x FULL OUTER JOIN x y ON x.column_1 = y.column_2;
+----------+----------+----------+----------+
| column_1 | column_2 | column_1 | column_2 |
+----------+----------+----------+----------+
| 1        | 2        |          |          |
|          |          | 1        | 2        |
+----------+----------+----------+----------+
```

### NATURAL JOIN

A `NATURAL JOIN` defines an inner join based on common column names found between the input tables. When no common
column names are found, it behaves like a `CROSS JOIN`.

```sql
SELECT * FROM x NATURAL JOIN x y;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
| 1        | 2        |
+----------+----------+
```

### CROSS JOIN

A `CROSS JOIN` produces a cartesian product that matches every row in the left side of the join with every row in the
right side of the join.

```sql
SELECT * FROM x CROSS JOIN x y;
+----------+----------+----------+----------+
| column_1 | column_2 | column_1 | column_2 |
+----------+----------+----------+----------+
| 1        | 2        | 1        | 2        |
+----------+----------+----------+----------+
```

### LEFT SEMI JOIN

The `LEFT SEMI JOIN` returns all rows from the left table that have at least one matching row in the right table, and
projects only the columns from the left table.

```sql
SELECT * FROM x LEFT SEMI JOIN x y ON x.column_1 = y.column_1;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
| 1        | 2        |
+----------+----------+
```

### RIGHT SEMI JOIN

The `RIGHT SEMI JOIN` returns all rows from the right table that have at least one matching row in the left table, and
only projects the columns from the right table.

```sql
SELECT * FROM x RIGHT SEMI JOIN x y ON x.column_1 = y.column_1;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
| 1        | 2        |
+----------+----------+
```

### LEFT ANTI JOIN

The `LEFT ANTI JOIN` returns all rows from the left table that do not have any matching row in the right table, projecting
only the left table’s columns.

```sql
SELECT * FROM x LEFT ANTI JOIN x y ON x.column_1 = y.column_1;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
+----------+----------+
```

### RIGHT ANTI JOIN

The `RIGHT ANTI JOIN` returns all rows from the right table that do not have any matching row in the left table, projecting
only the right table’s columns.

```sql
SELECT * FROM x RIGHT ANTI JOIN x y ON x.column_1 = y.column_1;
+----------+----------+
| column_1 | column_2 |
+----------+----------+
+----------+----------+
```

### LATERAL JOIN

A `LATERAL JOIN` allows the right-hand side of a join to reference columns from
the left-hand side. Conceptually, the subquery on the right is evaluated once
for each row of the left-hand table, which makes it possible to "parameterize" a
subquery with values from preceding tables.

The `LATERAL` keyword is required; DataFusion does not implicitly detect
correlation in `FROM` clause subqueries.

The following examples use these tables:

```sql
CREATE TABLE departments(id INT, name TEXT) AS VALUES (1, 'HR'), (2, 'Eng'), (3, 'Sales');
CREATE TABLE employees(id INT, dept_id INT, name TEXT) AS VALUES
  (10, 1, 'Alice'), (20, 1, 'Bob'), (30, 2, 'Carol');
```

#### Comma syntax

The most concise form places `LATERAL` after a comma in the `FROM` clause.
Rows from the left table that have no matching rows in the subquery are excluded
(inner join semantics).

```sql
SELECT d.name AS dept, e.name AS emp
FROM departments d, LATERAL (
    SELECT employees.name FROM employees WHERE employees.dept_id = d.id
) AS e
ORDER BY dept, emp;
+------+-------+
| dept | emp   |
+------+-------+
| Eng  | Carol |
| HR   | Alice |
| HR   | Bob   |
+------+-------+
```

#### CROSS JOIN LATERAL

Equivalent to the comma syntax above.

```sql
SELECT d.name AS dept, e.name AS emp
FROM departments d
CROSS JOIN LATERAL (
    SELECT employees.name FROM employees WHERE employees.dept_id = d.id
) AS e
ORDER BY dept, emp;
+------+-------+
| dept | emp   |
+------+-------+
| Eng  | Carol |
| HR   | Alice |
| HR   | Bob   |
+------+-------+
```

#### JOIN LATERAL ... ON

`JOIN LATERAL` with an `ON` clause applies the `ON` condition as an additional
filter after the lateral subquery is evaluated.

```sql
SELECT d.name AS dept, sub.emp, sub.cnt
FROM departments d
JOIN LATERAL (
    SELECT count(*) AS cnt, min(employees.name) AS emp
    FROM employees WHERE employees.dept_id = d.id
) AS sub ON sub.cnt > 0
ORDER BY dept;
+------+-------+-----+
| dept | emp   | cnt |
+------+-------+-----+
| Eng  | Carol | 1   |
| HR   | Alice | 2   |
+------+-------+-----+
```

#### Limitations

The following patterns are not yet supported:

- `LEFT JOIN LATERAL` (lateral join with outer join semantics).
- Outer references in the `SELECT` list of the lateral subquery (e.g., `LATERAL (SELECT outer.col + 1)`).
- `HAVING` in lateral subqueries.

## GROUP BY clause

Example:

```sql
SELECT a, b, MAX(c) FROM table GROUP BY a, b
```

Some aggregation functions accept optional ordering requirement, such as `ARRAY_AGG`. If a requirement is given,
aggregation is calculated in the order of the requirement.

Example:

```sql
SELECT a, b, ARRAY_AGG(c, ORDER BY d) FROM table GROUP BY a, b
```

## HAVING clause

Example:

```sql
SELECT a, b, MAX(c) FROM table GROUP BY a, b HAVING MAX(c) > 10
```

## QUALIFY clause

Example:

```sql
SELECT ROW_NUMBER() OVER (PARTITION BY region) AS rk FROM table QUALIFY rk > 1;
```

## UNION clause

Example:

```sql
SELECT
    a,
    b,
    c
FROM table1
UNION ALL
SELECT
    a,
    b,
    c
FROM table2
```

## ORDER BY clause

Orders the results by the referenced expression. By default it uses ascending order (`ASC`).
This order can be changed to descending by adding `DESC` after the order-by expressions.

Examples:

```sql
SELECT age, person FROM table ORDER BY age;
SELECT age, person FROM table ORDER BY age DESC;
SELECT age, person FROM table ORDER BY age, person DESC;
```

## LIMIT clause

Limits the number of rows to be a maximum of `count` rows. `count` should be a non-negative integer.

Example:

```sql
SELECT age, person FROM table
LIMIT 10
```

## EXCLUDE and EXCEPT clause

Excluded named columns from query results.

Example selecting all columns except for `age` and `person`:

```sql
SELECT * EXCEPT(age, person)
FROM table;
```

```sql
SELECT * EXCLUDE(age, person)
FROM table;
```

## Pipe operators

Some SQL dialects (e.g. BigQuery) support the pipe operator `|>`.
The SQL dialect can be set like this:

```sql
set datafusion.sql_parser.dialect = 'BigQuery';
```

DataFusion currently supports the following pipe operators:

- [WHERE](#pipe_where)
- [ORDER BY](#pipe_order_by)
- [LIMIT](#pipe_limit)
- [SELECT](#pipe_select)
- [EXTEND](#pipe_extend)
- [AS](#pipe_as)
- [UNION](#pipe_union)
- [INTERSECT](#pipe_intersect)
- [EXCEPT](#pipe_except)
- [AGGREGATE](#pipe_aggregate)
- [JOIN](#pipe_join)

(pipe_where)=

### WHERE

```sql
select * from range(0,10)
|> where value < 2;
+-------+
| value |
+-------+
| 0     |
| 1     |
+-------+
```

(pipe_order_by)=

### ORDER BY

```sql
select * from range(0,3)
|> order by value desc;
+-------+
| value |
+-------+
| 2     |
| 1     |
| 0     |
+-------+
```

(pipe_limit)=

### LIMIT

```sql
select * from range(0,3)
|> order by value desc
|> limit 1;
+-------+
| value |
+-------+
| 2     |
+-------+
```

(pipe_select)=

### SELECT

```sql
select * from range(0,3)
|> select value + 10;
+---------------------------+
| range().value + Int64(10) |
+---------------------------+
| 10                        |
| 11                        |
| 12                        |
+---------------------------+
```

(pipe_extend)=

### EXTEND

```sql
select * from range(0,3)
|> extend -value AS minus_value;
+-------+-------------+
| value | minus_value |
+-------+-------------+
| 0     | 0           |
| 1     | -1          |
| 2     | -2          |
+-------+-------------+
```

(pipe_as)=

### AS

```sql
select * from range(0,3)
|> as my_range
|> SELECT my_range.value;
+-------+
| value |
+-------+
| 0     |
| 1     |
| 2     |
+-------+
```

(pipe_union)=

### UNION

```sql
select * from range(0,3)
|> union all (
  select * from range(3,6)
);
+-------+
| value |
+-------+
| 0     |
| 1     |
| 2     |
| 3     |
| 4     |
| 5     |
+-------+
```

(pipe_intersect)=

### INTERSECT

```sql
select * from range(0,100)
|> INTERSECT DISTINCT (
  select 3
);
+-------+
| value |
+-------+
| 3     |
+-------+
```

(pipe_except)=

### EXCEPT

```sql
select * from range(0,10)
|> EXCEPT DISTINCT (select * from range(5,10));
+-------+
| value |
+-------+
| 0     |
| 1     |
| 2     |
| 3     |
| 4     |
+-------+
```

(pipe_aggregate)=

### AGGREGATE

```sql
select * from range(0,3)
|> aggregate sum(value) AS total;
+-------+
| total |
+-------+
| 3     |
+-------+
```

(pipe_join)=

### JOIN

```sql
(
  SELECT 'apples' AS item, 2 AS sales
  UNION ALL
  SELECT 'bananas' AS item, 5 AS sales
)
|> AS produce_sales
|> LEFT JOIN
     (
       SELECT 'apples' AS item, 123 AS id
     ) AS produce_data
   ON produce_sales.item = produce_data.item
|> SELECT produce_sales.item, sales, id;
+--------+-------+------+
| item   | sales | id   |
+--------+-------+------+
| apples | 2     | 123  |
| bananas| 5     | NULL |
+--------+-------+------+
```