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Query Syntax

JOIN

A JOIN operation combines rows from two tables (or other table-like sources, such as views or table functions) to create a new combined row that can be used in the query. For a conceptual explanation of joins, see Working with Joins.

This topic describes how to use the JOIN construct in the FROM clause. The JOIN subclause specifies (explicitly or implicitly) how to relate rows in one table to the corresponding rows in the other table. See also ASOF JOIN, which is used to join time-series data on timestamp columns when their values closely follow each other, precede each other, or match exactly.

Although the recommended way to join tables is to use JOIN with the ON subclause of the FROM clause, an alternative way to join tables is to use the WHERE clause. For details, see the documentation for the WHERE clause.

Syntax

Use one of the following:

SELECT ...
FROM <object_ref1> [
                     {
                       INNER
                       | { LEFT | RIGHT | FULL } [ OUTER ]
                     }
                   ]
                   JOIN <object_ref2>
  [ ON <condition> ]
[ ... ]
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SELECT *
FROM <object_ref1> [
                     {
                       INNER
                       | { LEFT | RIGHT | FULL } [ OUTER ]
                     }
                   ]
                   JOIN <object_ref2>
  [ USING( <column_list> ) ]
[ ... ]
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SELECT ...
FROM <object_ref1> [
                     {
                       | NATURAL [ { LEFT | RIGHT | FULL } [ OUTER ] ]
                       | CROSS
                     }
                   ]
                   JOIN <object_ref2>
[ ... ]
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object_ref1 and object_ref2

Each object reference is a table or table-like data source.

JOIN

Use the JOIN keyword to specify that the tables should be joined. Combine JOIN with other join-related keywords (e.g. INNER or OUTER) to specify the type of join.

The semantics of joins are as follows (for brevity, this topic uses o1 and o2 for object_ref1 and object_ref2, respectively).

Join Type

Semantics

o1 INNER JOIN o2

For each row of o1, a row is produced for each row of o2 that matches according to the ON condition subclause. (Note that you can also use a comma to specify an inner join. For an example, see the examples section below.) If you use INNER JOIN without the ON clause (or if you use comma without a WHERE clause), the result is the same as using CROSS JOIN: a Cartesian product (every row of o1 paired with every row of o2).

o1 LEFT OUTER JOIN o2

The result of the inner join is augmented with a row for each row of o1 that has no matches in o2. The result columns referencing o2 contain null.

o1 RIGHT OUTER JOIN o2

The result of the inner join is augmented with a row for each row of o2 that has no matches in o1. The result columns referencing o1 contain null.

o1 FULL OUTER JOIN o2

Returns all joined rows, plus one row for each unmatched left side row (extended with nulls on the right), plus one row for each unmatched right side row (extended with nulls on the left).

o1 CROSS JOIN o2

For every possible combination of rows from o1 and o2 (i.e. Cartesian product), the joined table contains a row consisting of all columns in o1 followed by all columns in o2. A CROSS JOIN cannot be combined with an ON condition clause. However, you can use a WHERE clause to filter the results.

o1 NATURAL JOIN o2

A NATURAL JOIN is identical to an explicit JOIN on the common columns of the two tables, except that the common columns are included only once in the output. (A natural join assumes that columns with the same name, but in different tables, contain corresponding data.) See the Examples section below for some examples. A NATURAL JOIN can be combined with an OUTER JOIN. A NATURAL JOIN cannot be combined with an ON condition clause because the JOIN condition is already implied. However, you can use a WHERE clause to filter the results.

See also:

Default: INNER JOIN

If the word JOIN is used without specifying INNER or OUTER, then the JOIN is an inner join.

ON condition

A boolean expression that defines the rows from the two sides of the JOIN that are considered to match, for example:

ON object_ref2.id_number = object_ref1.id_number
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Conditions are discussed in more detail in the WHERE clause documentation.

The ON clause is prohibited for CROSS JOIN.

The ON clause is unnecessary (and prohibited) for NATURAL JOIN; the join columns are implied.

For other joins, the ON clause is optional. However, omitting the ON clause results in a Cartesian product (every row of object_ref1 paired with every row of object_ref2). A Cartesian product can produce a very large volume of output, almost all of which consists of pairs of rows that aren’t actually related; this consumes a lot of resources and is often a user error.

USING( <column_list> )

A list of columns in common between the two tables being joined; these columns are used as the join columns. The columns must have the same name and meaning in each of the tables being joined.

For example, suppose that the SQL statement contains:

... o1 JOIN o2
    USING (key_column)
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In the simple case, this would be equivalent to:

... o1 JOIN o2
    ON o2.key_column = o1.key_column
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In the standard JOIN syntax, the projection list (the list of columns and other expressions after the SELECT keyword) is “*”. This causes the query to return the key_column exactly once. The columns are returned in the following order:

  • The columns in the USING clause in the order specified.

  • The left table columns not specified in the USING clause.

  • The right table columns not specified in the USING clause.

For examples of standard and non-standard usage, see the examples below.

Usage notes

  • The following restrictions apply to table functions other than SQL UDTFs:

    • You cannot specify the ON, USING, or NATURAL JOIN clause in a lateral table function (other than a SQL UDTF).

      For example, the following syntax is not allowed:

      SELECT ... FROM my_table
  JOIN TABLE(FLATTEN(input=>[col_a]))
  ON ... ;
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      SELECT ... FROM my_table
  INNER JOIN TABLE(FLATTEN(input=>[col_a]))
  ON ... ;
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      SELECT ... FROM my_table
  JOIN TABLE(my_js_udtf(col_a))
  ON ... ;
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      SELECT ... FROM my_table
  INNER JOIN TABLE(my_js_udtf(col_a))
  ON ... ;
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    • You cannot specify the ON, USING, or NATURAL JOIN clause in an outer lateral join to a table function (other than a SQL UDTF).

      For example, the following syntax is not allowed:

      SELECT ... FROM my_table
  LEFT JOIN TABLE(FLATTEN(input=>[a]))
  ON ... ;
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      SELECT ... FROM my_table
  FULL JOIN TABLE(FLATTEN(input=>[a]))
  ON ... ;
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      SELECT ... FROM my_table
  LEFT JOIN TABLE(my_js_udtf(a))
  ON ... ;
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      SELECT ... FROM my_table
  FULL JOIN TABLE(my_js_udtf(a))
  ON ... ;
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    • Using this syntax above results in the following error:

      000002 (0A000): Unsupported feature
  'lateral table function called with OUTER JOIN syntax
   or a join predicate (ON clause)'

    • These restrictions do not apply if you are using a comma, rather than a JOIN keyword:

      SELECT ... FROM my_table,
  TABLE(FLATTEN(input=>[col_a]))
  ON ... ;
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Examples

Many of the JOIN examples use two tables, t1 and t2. The tables and their data are created as shown below:

CREATE TABLE t1 (col1 INTEGER);
CREATE TABLE t2 (col1 INTEGER);
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INSERT INTO t1 (col1) VALUES 
   (2),
   (3),
   (4);
INSERT INTO t2 (col1) VALUES 
   (1),
   (2),
   (2),
   (3);
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Inner join:

SELECT t1.col1, t2.col1
    FROM t1 INNER JOIN t2
        ON t2.col1 = t1.col1
    ORDER BY 1,2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    2 |
|    2 |    2 |
|    3 |    3 |
+------+------+
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This shows a left outer join. Note the NULL value for the row in table t1 that doesn’t have a matching row in table t2.

SELECT t1.col1, t2.col1
    FROM t1 LEFT OUTER JOIN t2
        ON t2.col1 = t1.col1
    ORDER BY 1,2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    2 |
|    2 |    2 |
|    3 |    3 |
|    4 | NULL |
+------+------+
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This shows a right outer join. Note the NULL value for the row in table t1 that doesn’t have a matching row in table t2.

SELECT t1.col1, t2.col1
    FROM t1 RIGHT OUTER JOIN t2
        ON t2.col1 = t1.col1
    ORDER BY 1,2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    2 |
|    2 |    2 |
|    3 |    3 |
| NULL |    1 |
+------+------+
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This shows a full outer join. Note that because each table has a row that doesn’t have a matching row in the other table, the output contains two rows with NULL values:

SELECT t1.col1, t2.col1
    FROM t1 FULL OUTER JOIN t2
        ON t2.col1 = t1.col1
    ORDER BY 1,2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    2 |
|    2 |    2 |
|    3 |    3 |
|    4 | NULL |
| NULL |    1 |
+------+------+
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Here is an example of a cross join, which produces a Cartesian product. Note that the cross join does not have an ON clause.

SELECT t1.col1, t2.col1
    FROM t1 CROSS JOIN t2
    ORDER BY 1, 2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    1 |
|    2 |    2 |
|    2 |    2 |
|    2 |    3 |
|    3 |    1 |
|    3 |    2 |
|    3 |    2 |
|    3 |    3 |
|    4 |    1 |
|    4 |    2 |
|    4 |    2 |
|    4 |    3 |
+------+------+
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A cross join can be filtered by a WHERE clause, as shown in the example below:

SELECT t1.col1, t2.col1
    FROM t1 CROSS JOIN t2
    WHERE t2.col1 = t1.col1
    ORDER BY 1, 2;
+------+------+
| COL1 | COL1 |
|------+------|
|    2 |    2 |
|    2 |    2 |
|    3 |    3 |
+------+------+
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This is an example of a natural join. This produces the same output as the corresponding inner join, except that the output doesn’t include a second copy of the join column:

CREATE OR REPLACE TABLE d1 (
  id number,
  name string
  );
+--------------------------------+
| status                         |
|--------------------------------|
| Table D1 successfully created. |
+--------------------------------+
INSERT INTO d1 (id, name) VALUES
  (1,'a'),
  (2,'b'),
  (4,'c');
+-------------------------+
| number of rows inserted |
|-------------------------|
|                       3 |
+-------------------------+
CREATE OR REPLACE TABLE d2 (
  id number,
  value string
  );
+--------------------------------+
| status                         |
|--------------------------------|
| Table D2 successfully created. |
+--------------------------------+
INSERT INTO d2 (id, value) VALUES
  (1,'xx'),
  (2,'yy'),
  (5,'zz');
+-------------------------+
| number of rows inserted |
|-------------------------|
|                       3 |
+-------------------------+
SELECT *
    FROM d1 NATURAL INNER JOIN d2
    ORDER BY id;
+----+------+-------+
| ID | NAME | VALUE |
|----+------+-------|
|  1 | a    | xx    |
|  2 | b    | yy    |
+----+------+-------+
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Natural joins can be combined with outer joins, for example:

SELECT *
  FROM d1 NATURAL FULL OUTER JOIN d2
  ORDER BY ID;
+----+------+-------+
| ID | NAME | VALUE |
|----+------+-------|
|  1 | a    | xx    |
|  2 | b    | yy    |
|  4 | c    | NULL  |
|  5 | NULL | zz    |
+----+------+-------+
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Joins can be combined in the FROM clause. The following code creates a third table, then chains together two JOINs in the FROM clause:

CREATE TABLE t3 (col1 INTEGER);
INSERT INTO t3 (col1) VALUES 
   (2),
   (6);
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SELECT t1.*, t2.*, t3.*
  FROM t1
     LEFT OUTER JOIN t2 ON (t1.col1 = t2.col1)
     RIGHT OUTER JOIN t3 ON (t3.col1 = t2.col1)
  ORDER BY t1.col1;
+------+------+------+
| COL1 | COL1 | COL1 |
|------+------+------|
|    2 |    2 |    2 |
|    2 |    2 |    2 |
| NULL | NULL |    6 |
+------+------+------+
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In such a query, the results are determined based on the joins taking place from left to right (though the optimizer might reorder the joins if a different join order will produce the same result). If the right outer join is meant to take place before the left outer join, then the query can be written as follows:

SELECT t1.*, t2.*, t3.*
  FROM t1
     LEFT OUTER JOIN
     (t2 RIGHT OUTER JOIN t3 ON (t3.col1 = t2.col1))
     ON (t1.col1 = t2.col1)
  ORDER BY t1.col1;
+------+------+------+
| COL1 | COL1 | COL1 |
|------+------+------|
|    2 |    2 |    2 |
|    2 |    2 |    2 |
|    3 | NULL | NULL |
|    4 | NULL | NULL |
+------+------+------+
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The two examples below show standard (ISO 9075) and non-standard usage of the USING clause. Both are supported by Snowflake.

This first example shows standard usage. Specifically, the projection list contains exactly “*”. Even though the example query joins two tables, and each table has one column, and the query asks for all columns, the output contains one column, not two.

WITH
    l AS (
         SELECT 'a' AS userid
         ),
    r AS (
         SELECT 'b' AS userid
         )
  SELECT *
    FROM l LEFT JOIN r USING(userid)
;
+--------+
| USERID |
|--------|
| a      |
+--------+
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The following example shows non-standard usage. The projection list contains something other than “*”. The output contains two columns, and the second column contains either a value from the second table or NULL.

WITH
    l AS (
         SELECT 'a' AS userid
       ),
    r AS (
         SELECT 'b' AS userid
         )
  SELECT l.userid as UI_L,
         r.userid as UI_R
    FROM l LEFT JOIN r USING(userid)
;
+------+------+
| UI_L | UI_R |
|------+------|
| a    | NULL |
+------+------+
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