Description
SELECT will return rows from one or more tables.
Candidates for selection are rows which satisfy the WHERE condition;
if WHERE is omitted, all rows are candidates.
(See WHERE Clause.)
Actually, the returned rows are not directly the rows produced by the
FROM/WHERE/GROUP BY/HAVING clauses; rather, the output rows are formed
by computing the SELECT output expressions for each selected row.
* can be written in the output list as a shorthand
for all the columns of the selected rows. Also, one can write
table_name.*
as a shorthand for the columns coming from just that table.
DISTINCT will eliminate duplicate rows from the
result.
ALL (the default) will return all candidate rows,
including duplicates.
DISTINCT ON eliminates rows that match on all the
specified expressions, keeping only the first row of each set of
duplicates. The DISTINCT ON expressions are interpreted using the
same rules as for ORDER BY items; see below.
Note that the "first row" of each set is unpredictable
unless ORDER BY is used to ensure that the desired
row appears first. For example,
SELECT DISTINCT ON (location) location, time, report
FROM weatherReports
ORDER BY location, time DESC;
retrieves the most recent weather report for each location. But if
we had not used ORDER BY to force descending order of time values
for each location, we'd have gotten a report of unpredictable age
for each location.
The GROUP BY clause allows a user to divide a table
into groups of rows that match on one or more values.
(See GROUP BY Clause.)
The HAVING clause allows selection of only those groups of rows
meeting the specified condition.
(See HAVING Clause.)
The ORDER BY clause causes the returned rows to be sorted in a specified
order. If ORDER BY is not given, the rows are returned in whatever order
the system finds cheapest to produce.
(See ORDER BY Clause.)
SELECT queries can be combined using UNION, INTERSECT, and EXCEPT
operators. Use parentheses if necessary to determine the ordering
of these operators.
The UNION operator computes the collection of rows
returned by the queries involved.
Duplicate rows are eliminated unless ALL is specified.
(See UNION Clause.)
The INTERSECT operator computes the rows that are common to both queries.
Duplicate rows are eliminated unless ALL is specified.
(See INTERSECT Clause.)
The EXCEPT operator computes the rows returned by the first query but
not the second query.
Duplicate rows are eliminated unless ALL is specified.
(See EXCEPT Clause.)
The LIMIT clause allows a subset of the rows produced by the query
to be returned to the user.
(See LIMIT Clause.)
The FOR UPDATE clause causes the SELECT statement to lock the selected
rows against concurrent updates.
You must have SELECT privilege to a table to read its values
(See the GRANT/REVOKE statements).
Use of FOR UPDATE requires UPDATE privilege as well.
FROM Clause
The FROM clause specifies one or more source tables for the SELECT.
If multiple sources are specified, the result is conceptually the
Cartesian product of all the rows in all the sources --- but usually
qualification conditions are added to restrict the returned rows to
a small subset of the Cartesian product.
When a FROM item is a simple table name, it implicitly includes rows
from sub-tables (inheritance children) of the table.
ONLY will
suppress rows from sub-tables of the table. Before
PostgreSQL 7.1,
this was the default result, and adding sub-tables was done
by appending * to the table name.
This old behavior is available via the command
SET SQL_Inheritance TO OFF.
A FROM item can also be a parenthesized sub-SELECT (note that an
alias clause is required for a sub-SELECT!). This is an extremely
handy feature since it's the only way to get multiple levels of
grouping, aggregation, or sorting in a single query.
A FROM item can be a table function (typically, a function that returns
multiple rows and/or columns, though actually any function can be used).
The function is invoked with the given argument value(s), and then its
output is scanned as though it were a table.
In some cases it is useful to define table functions that can return
different column sets depending on how they are invoked. To support this,
the table function can be declared as returning the pseudo-type
record. When such a function is used in FROM, it must be
followed by an alias, or the keyword AS alone,
and then by a parenthesized list of column names and types. This provides
a query-time composite type definition. The composite type definition
must match the actual composite type returned from the function, or an
error will be reported at run-time.
Finally, a FROM item can be a JOIN clause, which combines two simpler
FROM items. (Use parentheses if necessary to determine the order
of nesting.)
A CROSS JOIN or INNER JOIN is a simple Cartesian product,
the same as you get from listing the two items at the top level of FROM.
CROSS JOIN is equivalent to INNER JOIN ON (TRUE), that is, no rows are
removed by qualification. These join types are just a notational
convenience, since they do nothing you couldn't do with plain FROM and
WHERE.
LEFT OUTER JOIN returns all rows in the qualified Cartesian product
(i.e., all combined rows that pass its ON condition), plus one copy of each
row in the left-hand table for which there was no right-hand row that
passed the ON condition. This left-hand row is extended to the full
width of the joined table by inserting null values for the right-hand columns.
Note that only the JOIN's own ON or USING condition is considered while
deciding which rows have matches. Outer ON or WHERE conditions are
applied afterwards.
Conversely, RIGHT OUTER JOIN returns all the joined rows, plus one row
for each unmatched right-hand row (extended with nulls on the left).
This is just a notational
convenience, since you could convert it to a LEFT OUTER JOIN by switching
the left and right inputs.
FULL OUTER JOIN returns all the joined rows, plus one row for each
unmatched left-hand row (extended with nulls on the right), plus one row
for each unmatched right-hand row (extended with nulls on the left).
For all the JOIN types except CROSS JOIN, you must write exactly one of
ON join_condition,
USING ( join_column_list ),
or NATURAL. ON is the most general case: you can write any qualification
expression involving the two tables to be joined.
A USING column list ( a, b, ... ) is shorthand for the ON condition
left_table.a = right_table.a AND left_table.b = right_table.b ...
Also, USING implies that only one of each pair of equivalent columns will
be included in the JOIN output, not both. NATURAL is shorthand for
a USING list that mentions all similarly-named columns in the tables.
WHERE Clause
The optional WHERE condition has the general form:
WHERE boolean_expr
boolean_expr
can consist of any expression which evaluates to a Boolean value.
In many cases, this expression will be:
expr cond_op expr
or
log_op expr
where cond_op
can be one of: =, <, <=, >, >= or <>,
a conditional operator like ALL, ANY, IN, LIKE, or a
locally defined operator,
and log_op can be one
of: AND, OR, NOT.
SELECT will ignore all rows for which the WHERE condition does not return
TRUE.
GROUP BY Clause
GROUP BY specifies a grouped table derived by the application
of this clause:
GROUP BY expression [, ...]
GROUP BY will condense into a single row all selected rows that share the
same values for the grouped columns. Aggregate functions, if any,
are computed across all rows making up each group, producing a
separate value for each group (whereas without GROUP BY, an
aggregate produces a single value computed across all the selected
rows). When GROUP BY is present, it is not valid for the SELECT
output expression(s) to refer to
ungrouped columns except within aggregate functions, since there
would be more than one possible value to return for an ungrouped column.
A GROUP BY item can be an input column name, or the name or ordinal
number of an output column (SELECT expression), or it can be an arbitrary
expression formed from input-column values. In case of ambiguity, a GROUP
BY name will
be interpreted as an input-column name rather than an output column name.
HAVING Clause
The optional HAVING condition has the general form:
HAVING boolean_expr
where boolean_expr is the same
as specified for the WHERE clause.
HAVING specifies a grouped table derived by the elimination
of group rows that do not satisfy the
boolean_expr.
HAVING is different from WHERE:
WHERE filters individual rows before application of GROUP BY,
while HAVING filters group rows created by GROUP BY.
Each column referenced in
boolean_expr shall unambiguously
reference a grouping column, unless the reference appears within an
aggregate function.
ORDER BY Clause
ORDER BY expression [ ASC | DESC | USING operator ] [, ...]
An ORDER BY item can be the name or ordinal
number of an output column (SELECT expression), or it can be an arbitrary
expression formed from input-column values. In case of ambiguity, an
ORDER BY name will be interpreted as an output-column name.
The ordinal number refers to the ordinal (left-to-right) position
of the result column. This feature makes it possible to define an ordering
on the basis of a column that does not have a unique name.
This is never absolutely necessary because it is always possible
to assign a name to a result column using the AS clause, e.g.:
SELECT title, date_prod + 1 AS newlen FROM films ORDER BY newlen;
It is also possible to ORDER BY
arbitrary expressions (an extension to SQL92),
including fields that do not appear in the
SELECT result list.
Thus the following statement is legal:
SELECT name FROM distributors ORDER BY code;
A limitation of this feature is that an ORDER BY clause applying to the
result of a UNION, INTERSECT, or EXCEPT query may only specify an output
column name or number, not an expression.
Note that if an ORDER BY item is a simple name that matches both
a result column name and an input column name, ORDER BY will interpret
it as the result column name. This is the opposite of the choice that
GROUP BY will make in the same situation. This inconsistency is
mandated by the SQL92 standard.
Optionally one may add the key word DESC (descending)
or ASC (ascending) after each column name in the
ORDER BY clause. If not specified, ASC is
assumed by default. Alternatively, a specific ordering operator
name may be specified. ASC is equivalent to
USING < and DESC is equivalent to
USING >.
The null value sorts higher than any other value in a domain. In other
words, with ascending sort order nulls sort at the end and with
descending sort order nulls sort at the beginning.
Data of character types is sorted according to the locale-specific
collation order that was established when the database cluster
was initialized.
UNION Clause
table_query UNION [ ALL ] table_query
[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]
[ LIMIT { count | ALL } ]
[ OFFSET start ]
where
table_query
specifies any select expression without an ORDER BY, LIMIT, or FOR UPDATE
clause. (ORDER BY and LIMIT can be attached to a sub-expression
if it is enclosed in parentheses. Without parentheses, these clauses
will be taken to apply to the result of the UNION, not to its right-hand
input expression.)
The UNION operator computes the collection (set union) of the rows
returned by the queries involved.
The two SELECT statements that represent the direct operands of the UNION must
produce the same number of columns, and corresponding columns must be
of compatible data types.
The result of UNION does not contain any duplicate rows
unless the ALL option is specified. ALL prevents elimination of
duplicates.
Multiple UNION operators in the same SELECT statement are
evaluated left to right, unless otherwise indicated by parentheses.
Currently, FOR UPDATE may not be specified either for a UNION result
or for the inputs of a UNION.
INTERSECT Clause
table_query INTERSECT [ ALL ] table_query
[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]
[ LIMIT { count | ALL } ]
[ OFFSET start ]
where
table_query
specifies any select expression without an ORDER BY, LIMIT, or
FOR UPDATE clause.
INTERSECT is similar to UNION, except that it produces only rows that
appear in both query outputs, rather than rows that appear in either.
The result of INTERSECT does not contain any duplicate rows
unless the ALL option is specified. With ALL, a row that has
m duplicates in L and n duplicates in R will appear min(m,n) times.
Multiple INTERSECT operators in the same SELECT statement are
evaluated left to right, unless parentheses dictate otherwise.
INTERSECT binds more tightly than UNION --- that is,
A UNION B INTERSECT C will be read as
A UNION (B INTERSECT C) unless otherwise specified by parentheses.
EXCEPT Clause
table_query EXCEPT [ ALL ] table_query
[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]
[ LIMIT { count | ALL } ]
[ OFFSET start ]
where
table_query
specifies any select expression without an ORDER BY, LIMIT,
or FOR UPDATE clause.
EXCEPT is similar to UNION, except that it produces only rows that
appear in the left query's output but not in the right query's output.
The result of EXCEPT does not contain any duplicate rows
unless the ALL option is specified. With ALL, a row that has
m duplicates in L and n duplicates in R will appear max(m-n,0) times.
Multiple EXCEPT operators in the same SELECT statement are
evaluated left to right, unless parentheses dictate otherwise.
EXCEPT binds at the same level as UNION.
LIMIT Clause
LIMIT { count | ALL }
OFFSET start
where
count specifies the
maximum number of rows to return, and
start specifies the
number of rows to skip before starting to return rows.
LIMIT allows you to retrieve just a portion of the rows that are generated
by the rest of the query. If a limit count is given, no more than that
many rows will be returned. If an offset is given, that many rows will
be skipped before starting to return rows.
When using LIMIT, it is a good idea to use an ORDER BY clause that
constrains the result rows into a unique order. Otherwise you will get
an unpredictable subset of the query's rows---you may be asking for
the tenth through twentieth rows, but tenth through twentieth in what
ordering? You don't know what ordering unless you specify ORDER BY.
As of PostgreSQL 7.0, the
query optimizer takes LIMIT into account when generating a query plan,
so you are very likely to get different plans (yielding different row
orders) depending on what you use for LIMIT and OFFSET. Thus, using
different LIMIT/OFFSET values to select different subsets of a query
result will give inconsistent results unless
you enforce a predictable result ordering with ORDER BY. This is not
a bug; it is an inherent consequence of the fact that SQL does not
promise to deliver the results of a query in any particular order
unless ORDER BY is used to constrain the order.
FOR UPDATE Clause
FOR UPDATE [ OF tablename [, ...] ]
FOR UPDATE causes the rows retrieved by the query to be locked as though
for update. This prevents them from being modified or deleted by other
transactions until the current transaction ends; that is, other
transactions that attempt UPDATE, DELETE, or SELECT FOR UPDATE of these
rows will be blocked until the current transaction ends. Also, if an
UPDATE, DELETE, or SELECT FOR UPDATE from another transaction has already
locked a selected row or rows, SELECT FOR UPDATE will wait for the other
transaction to complete, and will then lock and return the updated row
(or no row, if the row was deleted). For further discussion see the
concurrency chapter of the User's Guide.
If specific tables are named in FOR UPDATE, then only rows coming from
those tables are locked; any other tables used in the SELECT are simply
read as usual.
FOR UPDATE cannot be used in contexts where returned rows can't be clearly
identified with individual table rows; for example it can't be used with
aggregation.
FOR UPDATE may appear before LIMIT for compatibility with
pre-7.3 applications. However, it effectively executes after LIMIT,
and so that is the recommended place to write it.
Usage
To join the table films with the table
distributors:
SELECT f.title, f.did, d.name, f.date_prod, f.kind
FROM distributors d, films f
WHERE f.did = d.did
title | did | name | date_prod | kind
---------------------------+-----+------------------+------------+----------
The Third Man | 101 | British Lion | 1949-12-23 | Drama
The African Queen | 101 | British Lion | 1951-08-11 | Romantic
Une Femme est une Femme | 102 | Jean Luc Godard | 1961-03-12 | Romantic
Vertigo | 103 | Paramount | 1958-11-14 | Action
Becket | 103 | Paramount | 1964-02-03 | Drama
48 Hrs | 103 | Paramount | 1982-10-22 | Action
War and Peace | 104 | Mosfilm | 1967-02-12 | Drama
West Side Story | 105 | United Artists | 1961-01-03 | Musical
Bananas | 105 | United Artists | 1971-07-13 | Comedy
Yojimbo | 106 | Toho | 1961-06-16 | Drama
There's a Girl in my Soup | 107 | Columbia | 1970-06-11 | Comedy
Taxi Driver | 107 | Columbia | 1975-05-15 | Action
Absence of Malice | 107 | Columbia | 1981-11-15 | Action
Storia di una donna | 108 | Westward | 1970-08-15 | Romantic
The King and I | 109 | 20th Century Fox | 1956-08-11 | Musical
Das Boot | 110 | Bavaria Atelier | 1981-11-11 | Drama
Bed Knobs and Broomsticks | 111 | Walt Disney | | Musical
(17 rows)
To sum the column len of all films and group
the results by kind:
SELECT kind, SUM(len) AS total FROM films GROUP BY kind;
kind | total
----------+-------
Action | 07:34
Comedy | 02:58
Drama | 14:28
Musical | 06:42
Romantic | 04:38
(5 rows)
To sum the column len of all films, group
the results by kind and show those group totals
that are less than 5 hours:
SELECT kind, SUM(len) AS total
FROM films
GROUP BY kind
HAVING SUM(len) < INTERVAL '5 hour';
kind | total
----------+-------
Comedy | 02:58
Romantic | 04:38
(2 rows)
The following two examples are identical ways of sorting the individual
results according to the contents of the second column
(name):
SELECT * FROM distributors ORDER BY name;
SELECT * FROM distributors ORDER BY 2;
did | name
-----+------------------
109 | 20th Century Fox
110 | Bavaria Atelier
101 | British Lion
107 | Columbia
102 | Jean Luc Godard
113 | Luso films
104 | Mosfilm
103 | Paramount
106 | Toho
105 | United Artists
111 | Walt Disney
112 | Warner Bros.
108 | Westward
(13 rows)
This example shows how to obtain the union of the tables
distributors and
actors, restricting the results to those that begin
with letter W in each table. Only distinct rows are wanted, so the
ALL keyword is omitted:
distributors: actors:
did | name id | name
-----+-------------- ----+----------------
108 | Westward 1 | Woody Allen
111 | Walt Disney 2 | Warren Beatty
112 | Warner Bros. 3 | Walter Matthau
... ...
SELECT distributors.name
FROM distributors
WHERE distributors.name LIKE 'W%'
UNION
SELECT actors.name
FROM actors
WHERE actors.name LIKE 'W%';
name
----------------
Walt Disney
Walter Matthau
Warner Bros.
Warren Beatty
Westward
Woody Allen
This example shows how to use a table function, both with and without
a column definition list.
distributors:
did | name
-----+--------------
108 | Westward
111 | Walt Disney
112 | Warner Bros.
...
CREATE FUNCTION distributors(int)
RETURNS SETOF distributors AS '
SELECT * FROM distributors WHERE did = $1;
' LANGUAGE SQL;
SELECT * FROM distributors(111);
did | name
-----+-------------
111 | Walt Disney
(1 row)
CREATE FUNCTION distributors_2(int)
RETURNS SETOF RECORD AS '
SELECT * FROM distributors WHERE did = $1;
' LANGUAGE SQL;
SELECT * FROM distributors_2(111) AS (f1 int, f2 text);
f1 | f2
-----+-------------
111 | Walt Disney
(1 row)