The FROM clause specifies the source of the data on which the remainder of the query should operate. Logically, the FROM clause is where the query starts execution. The FROM clause can contain a single table, a combination of multiple tables that are joined together using JOIN clauses, or another SELECT query inside a subquery node. DuckDB also has an optional FROM-first syntax which enables you to also query without a SELECT statement.

Examples

Select all columns from the table called table_name:

SELECT *
FROM table_name;

Select all columns from the table using the FROM-first syntax:

FROM table_name
SELECT *;

Select all columns using the FROM-first syntax and omitting the SELECT clause:

FROM table_name;

Select all columns from the table called table_name through an alias tn:

SELECT tn.*
FROM table_name tn;

Select all columns from the table table_name in the schema schema_name:

SELECT *
FROM schema_name.table_name;

Select the column i from the table function range, where the first column of the range function is renamed to i:

SELECT t.i
FROM range(100) AS t(i);

Select all columns from the CSV file called test.csv:

SELECT *
FROM 'test.csv';

Select all columns from a subquery:

SELECT *
FROM (SELECT * FROM table_name);

Select the entire row of the table as a struct:

SELECT t
FROM t;

Select the entire row of the subquery as a struct (i.e., a single column):

SELECT t
FROM (SELECT unnest(generate_series(41, 43)) AS x, 'hello' AS y) t;

Join two tables together:

SELECT *
FROM table_name
JOIN other_table
  ON table_name.key = other_table.key;

Select a 10% sample from a table:

SELECT *
FROM table_name
TABLESAMPLE 10%;

Select a sample of 10 rows from a table:

SELECT *
FROM table_name
TABLESAMPLE 10 ROWS;

Use the FROM-first syntax with WHERE clause and aggregation:

FROM range(100) AS t(i)
SELECT sum(t.i)
WHERE i % 2 = 0;

Joins

Joins are a fundamental relational operation used to connect two tables or relations horizontally. The relations are referred to as the left and right sides of the join based on how they are written in the join clause. Each result row has the columns from both relations.

A join uses a rule to match pairs of rows from each relation. Often this is a predicate, but there are other implied rules that may be specified.

Outer Joins

Rows that do not have any matches can still be returned if an OUTER join is specified. Outer joins can be one of:

• LEFT (All rows from the left relation appear at least once)
• RIGHT (All rows from the right relation appear at least once)
• FULL (All rows from both relations appear at least once)

A join that is not OUTER is INNER (only rows that get paired are returned).

When an unpaired row is returned, the attributes from the other table are set to NULL.

Cross Product Joins (Cartesian Product)

The simplest type of join is a CROSS JOIN. There are no conditions for this type of join, and it just returns all the possible pairs.

Return all pairs of rows:

SELECT a.*, b.*
FROM a
CROSS JOIN b;

This is equivalent to omitting the JOIN clause:

SELECT a.*, b.*
FROM a, b;

Conditional Joins

Most joins are specified by a predicate that connects attributes from one side to attributes from the other side. The conditions can be explicitly specified using an ON clause with the join (clearer) or implied by the WHERE clause (old-fashioned).

We use the l_regions and the l_nations tables from the TPC-H schema:

CREATE TABLE l_regions (
    r_regionkey INTEGER NOT NULL PRIMARY KEY,
    r_name      CHAR(25) NOT NULL,
    r_comment   VARCHAR(152)
);

CREATE TABLE l_nations (
    n_nationkey INTEGER NOT NULL PRIMARY KEY,
    n_name      CHAR(25) NOT NULL,
    n_regionkey INTEGER NOT NULL,
    n_comment   VARCHAR(152),
    FOREIGN KEY (n_regionkey) REFERENCES l_regions(r_regionkey)
);

Return the regions for the nations:

SELECT n.*, r.*
FROM l_nations n
JOIN l_regions r ON (n_regionkey = r_regionkey);

If the column names are the same and are required to be equal, then the simpler USING syntax can be used:

CREATE TABLE l_regions (regionkey INTEGER NOT NULL PRIMARY KEY,
                        name      CHAR(25) NOT NULL,
                        comment   VARCHAR(152));

CREATE TABLE l_nations (nationkey INTEGER NOT NULL PRIMARY KEY,
                        name      CHAR(25) NOT NULL,
                        regionkey INTEGER NOT NULL,
                        comment   VARCHAR(152),
                        FOREIGN KEY (regionkey) REFERENCES l_regions(regionkey));

Return the regions for the nations:

SELECT n.*, r.*
FROM l_nations n
JOIN l_regions r USING (regionkey);

The expressions do not have to be equalities – any predicate can be used:

Return the pairs of jobs where one ran longer but cost less:

SELECT s1.t_id, s2.t_id
FROM west s1, west s2
WHERE s1.time > s2.time
  AND s1.cost < s2.cost;

Natural Joins

Natural joins join two tables based on attributes that share the same name.

For example, take the following example with cities, airport codes and airport names. Note that both tables are intentionally incomplete, i.e., they do not have a matching pair in the other table.

CREATE TABLE city_airport (city_name VARCHAR, iata VARCHAR);
CREATE TABLE airport_names (iata VARCHAR, airport_name VARCHAR);
INSERT INTO city_airport VALUES
    ('Amsterdam', 'AMS'),
    ('Rotterdam', 'RTM'),
    ('Eindhoven', 'EIN'),
    ('Groningen', 'GRQ');
INSERT INTO airport_names VALUES
    ('AMS', 'Amsterdam Airport Schiphol'),
    ('RTM', 'Rotterdam The Hague Airport'),
    ('MST', 'Maastricht Aachen Airport');

To join the tables on their shared IATA attributes, run:

SELECT *
FROM city_airport
NATURAL JOIN airport_names;

This produces the following result:

Note that only rows where the same iata attribute was present in both tables were included in the result.

We can also express query using the vanilla JOIN clause with the USING keyword:

SELECT *
FROM city_airport
JOIN airport_names
USING (iata);

Semi and Anti Joins

Semi joins return rows from the left table that have at least one match in the right table. Anti joins return rows from the left table that have no matches in the right table. When using a semi or anti join the result will never have more rows than the left hand side table. Semi joins provide the same logic as the IN operator statement. Anti joins provide the same logic as the NOT IN operator, except anti joins ignore NULL values from the right table.

Semi Join Example

Return a list of city–airport code pairs from the city_airport table where the airport name is available in the airport_names table:

SELECT *
FROM city_airport
SEMI JOIN airport_names
    USING (iata);

This query is equivalent with:

SELECT *
FROM city_airport
WHERE iata IN (SELECT iata FROM airport_names);

Anti Join Example

Return a list of city–airport code pairs from the city_airport table where the airport name is not available in the airport_names table:

SELECT *
FROM city_airport
ANTI JOIN airport_names
    USING (iata);

This query is equivalent with:

SELECT *
FROM city_airport
WHERE iata NOT IN (SELECT iata FROM airport_names WHERE iata IS NOT NULL);

Lateral Joins

The LATERAL keyword allows subqueries in the FROM clause to refer to previous subqueries. This feature is also known as a lateral join.

SELECT *
FROM range(3) t(i), LATERAL (SELECT i + 1) t2(j);

Lateral joins are a generalization of correlated subqueries, as they can return multiple values per input value rather than only a single value.

SELECT *
FROM
    generate_series(0, 1) t(i),
    LATERAL (SELECT i + 10 UNION ALL SELECT i + 100) t2(j);

It may be helpful to think about LATERAL as a loop where we iterate through the rows of the first subquery and use it as input to the second (LATERAL) subquery. In the examples above, we iterate through table t and refer to its column i from the definition of table t2. The rows of t2 form column j in the result.

It is possible to refer to multiple attributes from the LATERAL subquery. Using the table from the first example:

CREATE TABLE t1 AS
    SELECT *
    FROM range(3) t(i), LATERAL (SELECT i + 1) t2(j);

SELECT *
    FROM t1, LATERAL (SELECT i + j) t2(k)
    ORDER BY ALL;

DuckDB detects when LATERAL joins should be used, making the use of the LATERAL keyword optional.

Positional Joins

When working with data frames or other embedded tables of the same size, the rows may have a natural correspondence based on their physical order. In scripting languages, this is easily expressed using a loop:

for (i = 0; i < n; i++) {
    f(t1.a[i], t2.b[i]);
}

It is difficult to express this in standard SQL because relational tables are not ordered, but imported tables such as data frames or disk files (like CSVs or Parquet files) do have a natural ordering.

Connecting them using this ordering is called a positional join:

CREATE TABLE t1 (x INTEGER);
CREATE TABLE t2 (s VARCHAR);

INSERT INTO t1 VALUES (1), (2), (3);
INSERT INTO t2 VALUES ('a'), ('b');

SELECT *
FROM t1
POSITIONAL JOIN t2;

Positional joins are always FULL OUTER joins, i.e., missing values (the last values in the shorter column) are set to NULL.

As-Of Joins

A common operation when working with temporal or similarly-ordered data is to find the nearest (first) event in a reference table (such as prices). This is called an as-of join:

Attach prices to stock trades:

SELECT t.*, p.price
FROM trades t
ASOF JOIN prices p
       ON t.symbol = p.symbol AND t.when >= p.when;

The ASOF join requires at least one inequality condition on the ordering field. The inequality can be any inequality condition (>=, >, <=, <) on any data type, but the most common form is >= on a temporal type. Any other conditions must be equalities (or NOT DISTINCT). This means that the left/right order of the tables is significant.

ASOF joins each left side row with at most one right side row. It can be specified as an OUTER join to find unpaired rows (e.g., trades without prices or prices which have no trades.)

Attach prices or NULLs to stock trades:

SELECT *
FROM trades t
ASOF LEFT JOIN prices p
            ON t.symbol = p.symbol
           AND t.when >= p.when;

ASOF joins can also specify join conditions on matching column names with the USING syntax, but the last attribute in the list must be the inequality, which will be greater than or equal to (>=):

SELECT *
FROM trades t
ASOF JOIN prices p USING (symbol, "when");

Returns symbol, trades.when, price (but NOT prices.when):

If you combine USING with a SELECT * like this, the query will return the left side (probe) column values for the matches, not the right side (build) column values. To get the prices times in the example, you will need to list the columns explicitly:

SELECT t.symbol, t.when AS trade_when, p.when AS price_when, price
FROM trades t
ASOF LEFT JOIN prices p USING (symbol, "when");

Self-Joins

DuckDB allows self-joins for all types of joins. Note that tables need to be aliased, using the same table name without aliases will result in an error:

CREATE TABLE t(x int);
SELECT * FROM t JOIN t USING(x);

Binder Error: Duplicate alias "t" in query!

Adding the aliases allows the query to parse successfully:

SELECT * FROM t AS t t1 JOIN t t2 USING(x);

FROM-First Syntax

DuckDB's SQL supports the FROM-first syntax, i.e., it allows putting the FROM clause before the SELECT clause or completely omitting the SELECT clause. We use the following example to demonstrate it:

CREATE TABLE tbl AS
    SELECT *
    FROM (VALUES ('a'), ('b')) t1(s), range(1, 3) t2(i);

FROM-First Syntax with a SELECT Clause

The following statement demonstrates the use of the FROM-first syntax:

FROM tbl
SELECT i, s;

This is equivalent to:

SELECT i, s
FROM tbl;

FROM-First Syntax without a SELECT Clause

The following statement demonstrates the use of the optional SELECT clause:

FROM tbl;

This is equivalent to:

SELECT *
FROM tbl;

Syntax