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NAME
SELECT, TABLE, WITH - retrieve rows from a table or view
SYNOPSIS
[ WITH [ RECURSIVE ] with_query [, ...] ]
SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
[ { * | expression [ [ AS ] output_name ] } [, ...] ]
[ FROM from_item [, ...] ]
[ WHERE condition ]
[ GROUP BY [ ALL | DISTINCT ] grouping_element [, ...] ]
[ HAVING condition ]
[ WINDOW window_name AS ( window_definition ) [, ...] ]
[ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] select ]
[ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [, ...] ]
[ LIMIT { count | ALL } ]
[ OFFSET start [ ROW | ROWS ] ]
[ FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } { ONLY | WITH TIES } ]
[ FOR { UPDATE | NO KEY UPDATE | SHARE | KEY SHARE } [ OF table_name [, ...] ] [ NOWAIT | SKIP LOCKED ] [...] ]
where from_item can be one of:
[ ONLY ] table_name [ * ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
[ TABLESAMPLE sampling_method ( argument [, ...] ) [ REPEATABLE ( seed ) ] ]
[ LATERAL ] ( select ) [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
with_query_name [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
[ LATERAL ] function_name ( [ argument [, ...] ] )
[ WITH ORDINALITY ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
[ LATERAL ] function_name ( [ argument [, ...] ] ) [ AS ] alias ( column_definition [, ...] )
[ LATERAL ] function_name ( [ argument [, ...] ] ) AS ( column_definition [, ...] )
[ LATERAL ] ROWS FROM( function_name ( [ argument [, ...] ] ) [ AS ( column_definition [, ...] ) ] [, ...] )
[ WITH ORDINALITY ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
from_item join_type from_item { ON join_condition | USING ( join_column [, ...] ) [ AS join_using_alias ] }
from_item NATURAL join_type from_item
from_item CROSS JOIN from_item
and grouping_element can be one of:
( )
expression
( expression [, ...] )
ROLLUP ( { expression | ( expression [, ...] ) } [, ...] )
CUBE ( { expression | ( expression [, ...] ) } [, ...] )
GROUPING SETS ( grouping_element [, ...] )
and with_query is:
with_query_name [ ( column_name [, ...] ) ] AS [ [ NOT ] MATERIALIZED ] ( select | values | insert | update | delete )
[ SEARCH { BREADTH | DEPTH } FIRST BY column_name [, ...] SET search_seq_col_name ]
[ CYCLE column_name [, ...] SET cycle_mark_col_name [ TO cycle_mark_value DEFAULT cycle_mark_default ] USING cycle_path_col_name ]
TABLE [ ONLY ] table_name [ * ]
DESCRIPTION
SELECT retrieves rows from zero or more tables. The general processing of SELECT is as
follows:
1. All queries in the WITH list are computed. These effectively serve as temporary tables
that can be referenced in the FROM list. A WITH query that is referenced more than
once in FROM is computed only once, unless specified otherwise with NOT MATERIALIZED.
(See WITH Clause below.)
2. All elements in the FROM list are computed. (Each element in the FROM list is a real
or virtual table.) If more than one element is specified in the FROM list, they are
cross-joined together. (See FROM Clause below.)
3. If the WHERE clause is specified, all rows that do not satisfy the condition are
eliminated from the output. (See WHERE Clause below.)
4. If the GROUP BY clause is specified, or if there are aggregate function calls, the
output is combined into groups of rows that match on one or more values, and the
results of aggregate functions are computed. If the HAVING clause is present, it
eliminates groups that do not satisfy the given condition. (See GROUP BY Clause and
HAVING Clause below.) Although query output columns are nominally computed in the next
step, they can also be referenced (by name or ordinal number) in the GROUP BY clause.
5. The actual output rows are computed using the SELECT output expressions for each
selected row or row group. (See SELECT List below.)
6. SELECT DISTINCT eliminates duplicate rows from the result. SELECT DISTINCT ON
eliminates rows that match on all the specified expressions. SELECT ALL (the default)
will return all candidate rows, including duplicates. (See DISTINCT Clause below.)
7. Using the operators UNION, INTERSECT, and EXCEPT, the output of more than one SELECT
statement can be combined to form a single result set. The UNION operator returns all
rows that are in one or both of the result sets. The INTERSECT operator returns all
rows that are strictly in both result sets. The EXCEPT operator returns the rows that
are in the first result set but not in the second. In all three cases, duplicate rows
are eliminated unless ALL is specified. The noise word DISTINCT can be added to
explicitly specify eliminating duplicate rows. Notice that DISTINCT is the default
behavior here, even though ALL is the default for SELECT itself. (See UNION Clause,
INTERSECT Clause, and EXCEPT Clause below.)
8. If the ORDER BY clause is specified, the returned rows are sorted in the specified
order. If ORDER BY is not given, the rows are returned in whatever order the system
finds fastest to produce. (See ORDER BY Clause below.)
9. If the LIMIT (or FETCH FIRST) or OFFSET clause is specified, the SELECT statement only
returns a subset of the result rows. (See LIMIT Clause below.)
10. If FOR UPDATE, FOR NO KEY UPDATE, FOR SHARE or FOR KEY SHARE is specified, the SELECT
statement locks the selected rows against concurrent updates. (See The Locking Clause
below.)
You must have SELECT privilege on each column used in a SELECT command. The use of FOR NO
KEY UPDATE, FOR UPDATE, FOR SHARE or FOR KEY SHARE requires UPDATE privilege as well (for
at least one column of each table so selected).
PARAMETERS
WITH Clause
The WITH clause allows you to specify one or more subqueries that can be referenced by
name in the primary query. The subqueries effectively act as temporary tables or views for
the duration of the primary query. Each subquery can be a SELECT, TABLE, VALUES, INSERT,
UPDATE or DELETE statement. When writing a data-modifying statement (INSERT, UPDATE or
DELETE) in WITH, it is usual to include a RETURNING clause. It is the output of RETURNING,
not the underlying table that the statement modifies, that forms the temporary table that
is read by the primary query. If RETURNING is omitted, the statement is still executed,
but it produces no output so it cannot be referenced as a table by the primary query.
A name (without schema qualification) must be specified for each WITH query. Optionally, a
list of column names can be specified; if this is omitted, the column names are inferred
from the subquery.
If RECURSIVE is specified, it allows a SELECT subquery to reference itself by name. Such a
subquery must have the form
non_recursive_term UNION [ ALL | DISTINCT ] recursive_term
where the recursive self-reference must appear on the right-hand side of the UNION. Only
one recursive self-reference is permitted per query. Recursive data-modifying statements
are not supported, but you can use the results of a recursive SELECT query in a
data-modifying statement. See Section 7.8 for an example.
Another effect of RECURSIVE is that WITH queries need not be ordered: a query can
reference another one that is later in the list. (However, circular references, or mutual
recursion, are not implemented.) Without RECURSIVE, WITH queries can only reference
sibling WITH queries that are earlier in the WITH list.
When there are multiple queries in the WITH clause, RECURSIVE should be written only once,
immediately after WITH. It applies to all queries in the WITH clause, though it has no
effect on queries that do not use recursion or forward references.
The optional SEARCH clause computes a search sequence column that can be used for ordering
the results of a recursive query in either breadth-first or depth-first order. The
supplied column name list specifies the row key that is to be used for keeping track of
visited rows. A column named search_seq_col_name will be added to the result column list
of the WITH query. This column can be ordered by in the outer query to achieve the
respective ordering. See Section 7.8.2.1 for examples.
The optional CYCLE clause is used to detect cycles in recursive queries. The supplied
column name list specifies the row key that is to be used for keeping track of visited
rows. A column named cycle_mark_col_name will be added to the result column list of the
WITH query. This column will be set to cycle_mark_value when a cycle has been detected,
else to cycle_mark_default. Furthermore, processing of the recursive union will stop when
a cycle has been detected. cycle_mark_value and cycle_mark_default must be constants and
they must be coercible to a common data type, and the data type must have an inequality
operator. (The SQL standard requires that they be Boolean constants or character strings,
but PostgreSQL does not require that.) By default, TRUE and FALSE (of type boolean) are
used. Furthermore, a column named cycle_path_col_name will be added to the result column
list of the WITH query. This column is used internally for tracking visited rows. See
Section 7.8.2.2 for examples.
Both the SEARCH and the CYCLE clause are only valid for recursive WITH queries. The
with_query must be a UNION (or UNION ALL) of two SELECT (or equivalent) commands (no
nested UNIONs). If both clauses are used, the column added by the SEARCH clause appears
before the columns added by the CYCLE clause.
The primary query and the WITH queries are all (notionally) executed at the same time.
This implies that the effects of a data-modifying statement in WITH cannot be seen from
other parts of the query, other than by reading its RETURNING output. If two such
data-modifying statements attempt to modify the same row, the results are unspecified.
A key property of WITH queries is that they are normally evaluated only once per execution
of the primary query, even if the primary query refers to them more than once. In
particular, data-modifying statements are guaranteed to be executed once and only once,
regardless of whether the primary query reads all or any of their output.
However, a WITH query can be marked NOT MATERIALIZED to remove this guarantee. In that
case, the WITH query can be folded into the primary query much as though it were a simple
sub-SELECT in the primary query's FROM clause. This results in duplicate computations if
the primary query refers to that WITH query more than once; but if each such use requires
only a few rows of the WITH query's total output, NOT MATERIALIZED can provide a net
savings by allowing the queries to be optimized jointly. NOT MATERIALIZED is ignored if
it is attached to a WITH query that is recursive or is not side-effect-free (i.e., is not
a plain SELECT containing no volatile functions).
By default, a side-effect-free WITH query is folded into the primary query if it is used
exactly once in the primary query's FROM clause. This allows joint optimization of the two
query levels in situations where that should be semantically invisible. However, such
folding can be prevented by marking the WITH query as MATERIALIZED. That might be useful,
for example, if the WITH query is being used as an optimization fence to prevent the
planner from choosing a bad plan. PostgreSQL versions before v12 never did such folding,
so queries written for older versions might rely on WITH to act as an optimization fence.
See Section 7.8 for additional information.
FROM Clause
The FROM clause specifies one or more source tables for the SELECT. If multiple sources
are specified, the result is the Cartesian product (cross join) of all the sources. But
usually qualification conditions are added (via WHERE) to restrict the returned rows to a
small subset of the Cartesian product.
The FROM clause can contain the following elements:
table_name
The name (optionally schema-qualified) of an existing table or view. If ONLY is
specified before the table name, only that table is scanned. If ONLY is not specified,
the table and all its descendant tables (if any) are scanned. Optionally, * can be
specified after the table name to explicitly indicate that descendant tables are
included.
alias
A substitute name for the FROM item containing the alias. An alias is used for brevity
or to eliminate ambiguity for self-joins (where the same table is scanned multiple
times). When an alias is provided, it completely hides the actual name of the table or
function; for example given FROM foo AS f, the remainder of the SELECT must refer to
this FROM item as f not foo. If an alias is written, a column alias list can also be
written to provide substitute names for one or more columns of the table.
TABLESAMPLE sampling_method ( argument [, ...] ) [ REPEATABLE ( seed ) ]
A TABLESAMPLE clause after a table_name indicates that the specified sampling_method
should be used to retrieve a subset of the rows in that table. This sampling precedes
the application of any other filters such as WHERE clauses. The standard PostgreSQL
distribution includes two sampling methods, BERNOULLI and SYSTEM, and other sampling
methods can be installed in the database via extensions.
The BERNOULLI and SYSTEM sampling methods each accept a single argument which is the
fraction of the table to sample, expressed as a percentage between 0 and 100. This
argument can be any real-valued expression. (Other sampling methods might accept more
or different arguments.) These two methods each return a randomly-chosen sample of the
table that will contain approximately the specified percentage of the table's rows.
The BERNOULLI method scans the whole table and selects or ignores individual rows
independently with the specified probability. The SYSTEM method does block-level
sampling with each block having the specified chance of being selected; all rows in
each selected block are returned. The SYSTEM method is significantly faster than the
BERNOULLI method when small sampling percentages are specified, but it may return a
less-random sample of the table as a result of clustering effects.
The optional REPEATABLE clause specifies a seed number or expression to use for
generating random numbers within the sampling method. The seed value can be any
non-null floating-point value. Two queries that specify the same seed and argument
values will select the same sample of the table, if the table has not been changed
meanwhile. But different seed values will usually produce different samples. If
REPEATABLE is not given then a new random sample is selected for each query, based
upon a system-generated seed. Note that some add-on sampling methods do not accept
REPEATABLE, and will always produce new samples on each use.
select
A sub-SELECT can appear in the FROM clause. This acts as though its output were
created as a temporary table for the duration of this single SELECT command. Note that
the sub-SELECT must be surrounded by parentheses, and an alias can be provided in the
same way as for a table. A VALUES command can also be used here.
with_query_name
A WITH query is referenced by writing its name, just as though the query's name were a
table name. (In fact, the WITH query hides any real table of the same name for the
purposes of the primary query. If necessary, you can refer to a real table of the same
name by schema-qualifying the table's name.) An alias can be provided in the same way
as for a table.
function_name
Function calls can appear in the FROM clause. (This is especially useful for functions
that return result sets, but any function can be used.) This acts as though the
function's output were created as a temporary table for the duration of this single
SELECT command. If the function's result type is composite (including the case of a
function with multiple OUT parameters), each attribute becomes a separate column in
the implicit table.
When the optional WITH ORDINALITY clause is added to the function call, an additional
column of type bigint will be appended to the function's result column(s). This column
numbers the rows of the function's result set, starting from 1. By default, this
column is named ordinality.
An alias can be provided in the same way as for a table. If an alias is written, a
column alias list can also be written to provide substitute names for one or more
attributes of the function's composite return type, including the ordinality column if
present.
Multiple function calls can be combined into a single FROM-clause item by surrounding
them with ROWS FROM( ... ). The output of such an item is the concatenation of the
first row from each function, then the second row from each function, etc. If some of
the functions produce fewer rows than others, null values are substituted for the
missing data, so that the total number of rows returned is always the same as for the
function that produced the most rows.
If the function has been defined as returning the record data type, then an alias or
the key word AS must be present, followed by a column definition list in the form (
column_name data_type [, ... ]). The column definition list must match the actual
number and types of columns returned by the function.
When using the ROWS FROM( ... ) syntax, if one of the functions requires a column
definition list, it's preferred to put the column definition list after the function
call inside ROWS FROM( ... ). A column definition list can be placed after the ROWS
FROM( ... ) construct only if there's just a single function and no WITH ORDINALITY
clause.
To use ORDINALITY together with a column definition list, you must use the ROWS FROM(
... ) syntax and put the column definition list inside ROWS FROM( ... ).
join_type
One of
• [ INNER ] JOIN
• LEFT [ OUTER ] JOIN
• RIGHT [ OUTER ] JOIN
• FULL [ OUTER ] JOIN
For the INNER and OUTER join types, a join condition must be specified, namely exactly
one of ON join_condition, USING (join_column [, ...]), or NATURAL. See below for the
meaning.
A JOIN clause combines two FROM items, which for convenience we will refer to as
“tables”, though in reality they can be any type of FROM item. Use parentheses if
necessary to determine the order of nesting. In the absence of parentheses, JOINs nest
left-to-right. In any case JOIN binds more tightly than the commas separating
FROM-list items. All the JOIN options 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 join condition), plus one copy of each row in the
left-hand table for which there was no right-hand row that passed the join 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 clause's own condition is
considered while deciding which rows have matches. Outer 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 tables.
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).
ON join_condition
join_condition is an expression resulting in a value of type boolean (similar to a
WHERE clause) that specifies which rows in a join are considered to match.
USING ( join_column [, ...] ) [ AS join_using_alias ]
A clause of the form USING ( a, b, ... ) is shorthand for ON 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.
If a join_using_alias name is specified, it provides a table alias for the join
columns. Only the join columns listed in the USING clause are addressable by this
name. Unlike a regular alias, this does not hide the names of the joined tables from
the rest of the query. Also unlike a regular alias, you cannot write a column alias
list — the output names of the join columns are the same as they appear in the USING
list.
NATURAL
NATURAL is shorthand for a USING list that mentions all columns in the two tables that
have matching names. If there are no common column names, NATURAL is equivalent to ON
TRUE.
CROSS JOIN
CROSS JOIN is equivalent to INNER JOIN ON (TRUE), that is, no rows are removed by
qualification. They produce a simple Cartesian product, the same result as you get
from listing the two tables at the top level of FROM, but restricted by the join
condition (if any).
LATERAL
The LATERAL key word can precede a sub-SELECT FROM item. This allows the sub-SELECT to
refer to columns of FROM items that appear before it in the FROM list. (Without
LATERAL, each sub-SELECT is evaluated independently and so cannot cross-reference any
other FROM item.)
LATERAL can also precede a function-call FROM item, but in this case it is a noise
word, because the function expression can refer to earlier FROM items in any case.
A LATERAL item can appear at top level in the FROM list, or within a JOIN tree. In the
latter case it can also refer to any items that are on the left-hand side of a JOIN
that it is on the right-hand side of.
When a FROM item contains LATERAL cross-references, evaluation proceeds as follows:
for each row of the FROM item providing the cross-referenced column(s), or set of rows
of multiple FROM items providing the columns, the LATERAL item is evaluated using that
row or row set's values of the columns. The resulting row(s) are joined as usual with
the rows they were computed from. This is repeated for each row or set of rows from
the column source table(s).
The column source table(s) must be INNER or LEFT joined to the LATERAL item, else
there would not be a well-defined set of rows from which to compute each set of rows
for the LATERAL item. Thus, although a construct such as X RIGHT JOIN LATERAL Y is
syntactically valid, it is not actually allowed for Y to reference X.
WHERE Clause
The optional WHERE clause has the general form
WHERE condition
where condition is any expression that evaluates to a result of type boolean. Any row that
does not satisfy this condition will be eliminated from the output. A row satisfies the
condition if it returns true when the actual row values are substituted for any variable
references.
GROUP BY Clause
The optional GROUP BY clause has the general form
GROUP BY [ ALL | DISTINCT ] grouping_element [, ...]
GROUP BY will condense into a single row all selected rows that share the same values for
the grouped expressions. An expression used inside a grouping_element can be an input
column name, or the name or ordinal number of an output column (SELECT list item), or 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.
If any of GROUPING SETS, ROLLUP or CUBE are present as grouping elements, then the GROUP
BY clause as a whole defines some number of independent grouping sets. The effect of this
is equivalent to constructing a UNION ALL between subqueries with the individual grouping
sets as their GROUP BY clauses. The optional DISTINCT clause removes duplicate sets before
processing; it does not transform the UNION ALL into a UNION DISTINCT. For further details
on the handling of grouping sets see Section 7.2.4.
Aggregate functions, if any are used, are computed across all rows making up each group,
producing a separate value for each group. (If there are aggregate functions but no GROUP
BY clause, the query is treated as having a single group comprising all the selected
rows.) The set of rows fed to each aggregate function can be further filtered by attaching
a FILTER clause to the aggregate function call; see Section 4.2.7 for more information.
When a FILTER clause is present, only those rows matching it are included in the input to
that aggregate function.
When GROUP BY is present, or any aggregate functions are present, it is not valid for the
SELECT list expressions to refer to ungrouped columns except within aggregate functions or
when the ungrouped column is functionally dependent on the grouped columns, since there
would otherwise be more than one possible value to return for an ungrouped column. A
functional dependency exists if the grouped columns (or a subset thereof) are the primary
key of the table containing the ungrouped column.
Keep in mind that all aggregate functions are evaluated before evaluating any “scalar”
expressions in the HAVING clause or SELECT list. This means that, for example, a CASE
expression cannot be used to skip evaluation of an aggregate function; see Section 4.2.14.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
with GROUP BY.
HAVING Clause
The optional HAVING clause has the general form
HAVING condition
where condition is the same as specified for the WHERE clause.
HAVING eliminates group rows that do not satisfy the condition. HAVING is different from
WHERE: WHERE filters individual rows before the application of GROUP BY, while HAVING
filters group rows created by GROUP BY. Each column referenced in condition must
unambiguously reference a grouping column, unless the reference appears within an
aggregate function or the ungrouped column is functionally dependent on the grouping
columns.
The presence of HAVING turns a query into a grouped query even if there is no GROUP BY
clause. This is the same as what happens when the query contains aggregate functions but
no GROUP BY clause. All the selected rows are considered to form a single group, and the
SELECT list and HAVING clause can only reference table columns from within aggregate
functions. Such a query will emit a single row if the HAVING condition is true, zero rows
if it is not true.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
with HAVING.
WINDOW Clause
The optional WINDOW clause has the general form
WINDOW window_name AS ( window_definition ) [, ...]
where window_name is a name that can be referenced from OVER clauses or subsequent window
definitions, and window_definition is
[ existing_window_name ]
[ PARTITION BY expression [, ...] ]
[ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [, ...] ]
[ frame_clause ]
If an existing_window_name is specified it must refer to an earlier entry in the WINDOW
list; the new window copies its partitioning clause from that entry, as well as its
ordering clause if any. In this case the new window cannot specify its own PARTITION BY
clause, and it can specify ORDER BY only if the copied window does not have one. The new
window always uses its own frame clause; the copied window must not specify a frame
clause.
The elements of the PARTITION BY list are interpreted in much the same fashion as elements
of a GROUP BY clause, except that they are always simple expressions and never the name or
number of an output column. Another difference is that these expressions can contain
aggregate function calls, which are not allowed in a regular GROUP BY clause. They are
allowed here because windowing occurs after grouping and aggregation.
Similarly, the elements of the ORDER BY list are interpreted in much the same fashion as
elements of a statement-level ORDER BY clause, except that the expressions are always
taken as simple expressions and never the name or number of an output column.
The optional frame_clause defines the window frame for window functions that depend on the
frame (not all do). The window frame is a set of related rows for each row of the query
(called the current row). The frame_clause can be one of
{ RANGE | ROWS | GROUPS } frame_start [ frame_exclusion ]
{ RANGE | ROWS | GROUPS } BETWEEN frame_start AND frame_end [ frame_exclusion ]
where frame_start and frame_end can be one of
UNBOUNDED PRECEDING
offset PRECEDING
CURRENT ROW
offset FOLLOWING
UNBOUNDED FOLLOWING
and frame_exclusion can be one of
EXCLUDE CURRENT ROW
EXCLUDE GROUP
EXCLUDE TIES
EXCLUDE NO OTHERS
If frame_end is omitted it defaults to CURRENT ROW. Restrictions are that frame_start
cannot be UNBOUNDED FOLLOWING, frame_end cannot be UNBOUNDED PRECEDING, and the frame_end
choice cannot appear earlier in the above list of frame_start and frame_end options than
the frame_start choice does — for example RANGE BETWEEN CURRENT ROW AND offset PRECEDING
is not allowed.
The default framing option is RANGE UNBOUNDED PRECEDING, which is the same as RANGE
BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW; it sets the frame to be all rows from the
partition start up through the current row's last peer (a row that the window's ORDER BY
clause considers equivalent to the current row; all rows are peers if there is no ORDER
BY). In general, UNBOUNDED PRECEDING means that the frame starts with the first row of the
partition, and similarly UNBOUNDED FOLLOWING means that the frame ends with the last row
of the partition, regardless of RANGE, ROWS or GROUPS mode. In ROWS mode, CURRENT ROW
means that the frame starts or ends with the current row; but in RANGE or GROUPS mode it
means that the frame starts or ends with the current row's first or last peer in the ORDER
BY ordering. The offset PRECEDING and offset FOLLOWING options vary in meaning depending
on the frame mode. In ROWS mode, the offset is an integer indicating that the frame starts
or ends that many rows before or after the current row. In GROUPS mode, the offset is an
integer indicating that the frame starts or ends that many peer groups before or after the
current row's peer group, where a peer group is a group of rows that are equivalent
according to the window's ORDER BY clause. In RANGE mode, use of an offset option requires
that there be exactly one ORDER BY column in the window definition. Then the frame
contains those rows whose ordering column value is no more than offset less than (for
PRECEDING) or more than (for FOLLOWING) the current row's ordering column value. In these
cases the data type of the offset expression depends on the data type of the ordering
column. For numeric ordering columns it is typically of the same type as the ordering
column, but for datetime ordering columns it is an interval. In all these cases, the value
of the offset must be non-null and non-negative. Also, while the offset does not have to
be a simple constant, it cannot contain variables, aggregate functions, or window
functions.
The frame_exclusion option allows rows around the current row to be excluded from the
frame, even if they would be included according to the frame start and frame end options.
EXCLUDE CURRENT ROW excludes the current row from the frame. EXCLUDE GROUP excludes the
current row and its ordering peers from the frame. EXCLUDE TIES excludes any peers of the
current row from the frame, but not the current row itself. EXCLUDE NO OTHERS simply
specifies explicitly the default behavior of not excluding the current row or its peers.
Beware that the ROWS mode can produce unpredictable results if the ORDER BY ordering does
not order the rows uniquely. The RANGE and GROUPS modes are designed to ensure that rows
that are peers in the ORDER BY ordering are treated alike: all rows of a given peer group
will be in the frame or excluded from it.
The purpose of a WINDOW clause is to specify the behavior of window functions appearing in
the query's SELECT list or ORDER BY clause. These functions can reference the WINDOW
clause entries by name in their OVER clauses. A WINDOW clause entry does not have to be
referenced anywhere, however; if it is not used in the query it is simply ignored. It is
possible to use window functions without any WINDOW clause at all, since a window function
call can specify its window definition directly in its OVER clause. However, the WINDOW
clause saves typing when the same window definition is needed for more than one window
function.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
with WINDOW.
Window functions are described in detail in Section 3.5, Section 4.2.8, and Section 7.2.5.
SELECT List
The SELECT list (between the key words SELECT and FROM) specifies expressions that form
the output rows of the SELECT statement. The expressions can (and usually do) refer to
columns computed in the FROM clause.
Just as in a table, every output column of a SELECT has a name. In a simple SELECT this
name is just used to label the column for display, but when the SELECT is a sub-query of a
larger query, the name is seen by the larger query as the column name of the virtual table
produced by the sub-query. To specify the name to use for an output column, write AS
output_name after the column's expression. (You can omit AS, but only if the desired
output name does not match any PostgreSQL keyword (see Appendix C). For protection against
possible future keyword additions, it is recommended that you always either write AS or
double-quote the output name.) If you do not specify a column name, a name is chosen
automatically by PostgreSQL. If the column's expression is a simple column reference then
the chosen name is the same as that column's name. In more complex cases a function or
type name may be used, or the system may fall back on a generated name such as ?column?.
An output column's name can be used to refer to the column's value in ORDER BY and GROUP
BY clauses, but not in the WHERE or HAVING clauses; there you must write out the
expression instead.
Instead of an expression, * can be written in the output list as a shorthand for all the
columns of the selected rows. Also, you can write table_name.* as a shorthand for the
columns coming from just that table. In these cases it is not possible to specify new
names with AS; the output column names will be the same as the table columns' names.
According to the SQL standard, the expressions in the output list should be computed
before applying DISTINCT, ORDER BY, or LIMIT. This is obviously necessary when using
DISTINCT, since otherwise it's not clear what values are being made distinct. However, in
many cases it is convenient if output expressions are computed after ORDER BY and LIMIT;
particularly if the output list contains any volatile or expensive functions. With that
behavior, the order of function evaluations is more intuitive and there will not be
evaluations corresponding to rows that never appear in the output. PostgreSQL will
effectively evaluate output expressions after sorting and limiting, so long as those
expressions are not referenced in DISTINCT, ORDER BY or GROUP BY. (As a counterexample,
SELECT f(x) FROM tab ORDER BY 1 clearly must evaluate f(x) before sorting.) Output
expressions that contain set-returning functions are effectively evaluated after sorting
and before limiting, so that LIMIT will act to cut off the output from a set-returning
function.
Note
PostgreSQL versions before 9.6 did not provide any guarantees about the timing of
evaluation of output expressions versus sorting and limiting; it depended on the form
of the chosen query plan.
DISTINCT Clause
If SELECT DISTINCT is specified, all duplicate rows are removed from the result set (one
row is kept from each group of duplicates). SELECT ALL specifies the opposite: all rows
are kept; that is the default.
SELECT DISTINCT ON ( expression [, ...] ) keeps only the first row of each set of rows
where the given expressions evaluate to equal. The DISTINCT ON expressions are interpreted
using the same rules as for ORDER BY (see above). 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 weather_reports
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
from an unpredictable time for each location.
The DISTINCT ON expression(s) must match the leftmost ORDER BY expression(s). The ORDER BY
clause will normally contain additional expression(s) that determine the desired
precedence of rows within each DISTINCT ON group.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
with DISTINCT.
UNION Clause
The UNION clause has this general form:
select_statement UNION [ ALL | DISTINCT ] select_statement
select_statement is any SELECT statement without an ORDER BY, LIMIT, FOR NO KEY UPDATE,
FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause. (ORDER BY and LIMIT can be attached to a
subexpression 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 set union of the rows returned by the involved SELECT
statements. A row is in the set union of two result sets if it appears in at least one of
the result sets. 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. (Therefore, UNION ALL is usually
significantly quicker than UNION; use ALL when you can.) DISTINCT can be written to
explicitly specify the default behavior of eliminating duplicate rows.
Multiple UNION operators in the same SELECT statement are evaluated left to right, unless
otherwise indicated by parentheses.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
either for a UNION result or for any input of a UNION.
INTERSECT Clause
The INTERSECT clause has this general form:
select_statement INTERSECT [ ALL | DISTINCT ] select_statement
select_statement is any SELECT statement without an ORDER BY, LIMIT, FOR NO KEY UPDATE,
FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause.
The INTERSECT operator computes the set intersection of the rows returned by the involved
SELECT statements. A row is in the intersection of two result sets if it appears in both
result sets.
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 the left table and n duplicates in the
right table will appear min(m,n) times in the result set. DISTINCT can be written to
explicitly specify the default behavior of eliminating duplicate rows.
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).
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
either for an INTERSECT result or for any input of an INTERSECT.
EXCEPT Clause
The EXCEPT clause has this general form:
select_statement EXCEPT [ ALL | DISTINCT ] select_statement
select_statement is any SELECT statement without an ORDER BY, LIMIT, FOR NO KEY UPDATE,
FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause.
The EXCEPT operator computes the set of rows that are in the result of the left SELECT
statement but not in the result of the right one.
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 the left table and n duplicates in the
right table will appear max(m-n,0) times in the result set. DISTINCT can be written to
explicitly specify the default behavior of eliminating duplicate rows.
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.
Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE cannot be specified
either for an EXCEPT result or for any input of an EXCEPT.
ORDER BY Clause
The optional ORDER BY clause has this general form:
ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [, ...]
The ORDER BY clause causes the result rows to be sorted according to the specified
expression(s). If two rows are equal according to the leftmost expression, they are
compared according to the next expression and so on. If they are equal according to all
specified expressions, they are returned in an implementation-dependent order.
Each expression can be the name or ordinal number of an output column (SELECT list item),
or it can be an arbitrary expression formed from input-column values.
The ordinal number refers to the ordinal (left-to-right) position of the output 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 an output column using the AS clause.
It is also possible to use arbitrary expressions in the ORDER BY clause, including columns
that do not appear in the SELECT output list. Thus the following statement is valid:
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 clause can only specify an output column name or number, not an
expression.
If an ORDER BY expression is a simple name that matches both an output column name and an
input column name, ORDER BY will interpret it as the output column name. This is the
opposite of the choice that GROUP BY will make in the same situation. This inconsistency
is made to be compatible with the SQL standard.
Optionally one can add the key word ASC (ascending) or DESC (descending) after any
expression in the ORDER BY clause. If not specified, ASC is assumed by default.
Alternatively, a specific ordering operator name can be specified in the USING clause. An
ordering operator must be a less-than or greater-than member of some B-tree operator
family. ASC is usually equivalent to USING < and DESC is usually equivalent to USING >.
(But the creator of a user-defined data type can define exactly what the default sort
ordering is, and it might correspond to operators with other names.)
If NULLS LAST is specified, null values sort after all non-null values; if NULLS FIRST is
specified, null values sort before all non-null values. If neither is specified, the
default behavior is NULLS LAST when ASC is specified or implied, and NULLS FIRST when DESC
is specified (thus, the default is to act as though nulls are larger than non-nulls). When
USING is specified, the default nulls ordering depends on whether the operator is a
less-than or greater-than operator.
Note that ordering options apply only to the expression they follow; for example ORDER BY
x, y DESC does not mean the same thing as ORDER BY x DESC, y DESC.
Character-string data is sorted according to the collation that applies to the column
being sorted. That can be overridden at need by including a COLLATE clause in the
expression, for example ORDER BY mycolumn COLLATE "en_US". For more information see
Section 4.2.10 and Section 24.2.
LIMIT Clause
The LIMIT clause consists of two independent sub-clauses:
LIMIT { count | ALL }
OFFSET start
The parameter count specifies the maximum number of rows to return, while start specifies
the number of rows to skip before starting to return rows. When both are specified, start
rows are skipped before starting to count the count rows to be returned.
If the count expression evaluates to NULL, it is treated as LIMIT ALL, i.e., no limit. If
start evaluates to NULL, it is treated the same as OFFSET 0.
SQL:2008 introduced a different syntax to achieve the same result, which PostgreSQL also
supports. It is:
OFFSET start { ROW | ROWS }
FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } { ONLY | WITH TIES }
In this syntax, the start or count value is required by the standard to be a literal
constant, a parameter, or a variable name; as a PostgreSQL extension, other expressions
are allowed, but will generally need to be enclosed in parentheses to avoid ambiguity. If
count is omitted in a FETCH clause, it defaults to 1. The WITH TIES option is used to
return any additional rows that tie for the last place in the result set according to the
ORDER BY clause; ORDER BY is mandatory in this case, and SKIP LOCKED is not allowed. ROW
and ROWS as well as FIRST and NEXT are noise words that don't influence the effects of
these clauses. According to the standard, the OFFSET clause must come before the FETCH
clause if both are present; but PostgreSQL is laxer and allows either order.
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 might 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.
The query planner 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.
It is even possible for repeated executions of the same LIMIT query to return different
subsets of the rows of a table, if there is not an ORDER BY to enforce selection of a
deterministic subset. Again, this is not a bug; determinism of the results is simply not
guaranteed in such a case.
The Locking Clause
FOR UPDATE, FOR NO KEY UPDATE, FOR SHARE and FOR KEY SHARE are locking clauses; they
affect how SELECT locks rows as they are obtained from the table.
The locking clause has the general form
FOR lock_strength [ OF table_name [, ...] ] [ NOWAIT | SKIP LOCKED ]
where lock_strength can be one of
UPDATE
NO KEY UPDATE
SHARE
KEY SHARE
For more information on each row-level lock mode, refer to Section 13.3.2.
To prevent the operation from waiting for other transactions to commit, use either the
NOWAIT or SKIP LOCKED option. With NOWAIT, the statement reports an error, rather than
waiting, if a selected row cannot be locked immediately. With SKIP LOCKED, any selected
rows that cannot be immediately locked are skipped. Skipping locked rows provides an
inconsistent view of the data, so this is not suitable for general purpose work, but can
be used to avoid lock contention with multiple consumers accessing a queue-like table.
Note that NOWAIT and SKIP LOCKED apply only to the row-level lock(s) — the required ROW
SHARE table-level lock is still taken in the ordinary way (see Chapter 13). You can use
LOCK with the NOWAIT option first, if you need to acquire the table-level lock without
waiting.
If specific tables are named in a locking clause, then only rows coming from those tables
are locked; any other tables used in the SELECT are simply read as usual. A locking clause
without a table list affects all tables used in the statement. If a locking clause is
applied to a view or sub-query, it affects all tables used in the view or sub-query.
However, these clauses do not apply to WITH queries referenced by the primary query. If
you want row locking to occur within a WITH query, specify a locking clause within the
WITH query.
Multiple locking clauses can be written if it is necessary to specify different locking
behavior for different tables. If the same table is mentioned (or implicitly affected) by
more than one locking clause, then it is processed as if it was only specified by the
strongest one. Similarly, a table is processed as NOWAIT if that is specified in any of
the clauses affecting it. Otherwise, it is processed as SKIP LOCKED if that is specified
in any of the clauses affecting it.
The locking clauses cannot be used in contexts where returned rows cannot be clearly
identified with individual table rows; for example they cannot be used with aggregation.
When a locking clause appears at the top level of a SELECT query, the rows that are locked
are exactly those that are returned by the query; in the case of a join query, the rows
locked are those that contribute to returned join rows. In addition, rows that satisfied
the query conditions as of the query snapshot will be locked, although they will not be
returned if they were updated after the snapshot and no longer satisfy the query
conditions. If a LIMIT is used, locking stops once enough rows have been returned to
satisfy the limit (but note that rows skipped over by OFFSET will get locked). Similarly,
if a locking clause is used in a cursor's query, only rows actually fetched or stepped
past by the cursor will be locked.
When a locking clause appears in a sub-SELECT, the rows locked are those returned to the
outer query by the sub-query. This might involve fewer rows than inspection of the
sub-query alone would suggest, since conditions from the outer query might be used to
optimize execution of the sub-query. For example,
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss WHERE col1 = 5;
will lock only rows having col1 = 5, even though that condition is not textually within
the sub-query.
Previous releases failed to preserve a lock which is upgraded by a later savepoint. For
example, this code:
BEGIN;
SELECT * FROM mytable WHERE key = 1 FOR UPDATE;
SAVEPOINT s;
UPDATE mytable SET ... WHERE key = 1;
ROLLBACK TO s;
would fail to preserve the FOR UPDATE lock after the ROLLBACK TO. This has been fixed in
release 9.3.
Caution
It is possible for a SELECT command running at the READ COMMITTED transaction
isolation level and using ORDER BY and a locking clause to return rows out of order.
This is because ORDER BY is applied first. The command sorts the result, but might
then block trying to obtain a lock on one or more of the rows. Once the SELECT
unblocks, some of the ordering column values might have been modified, leading to
those rows appearing to be out of order (though they are in order in terms of the
original column values). This can be worked around at need by placing the FOR
UPDATE/SHARE clause in a sub-query, for example
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss ORDER BY column1;
Note that this will result in locking all rows of mytable, whereas FOR UPDATE at the
top level would lock only the actually returned rows. This can make for a significant
performance difference, particularly if the ORDER BY is combined with LIMIT or other
restrictions. So this technique is recommended only if concurrent updates of the
ordering columns are expected and a strictly sorted result is required.
At the REPEATABLE READ or SERIALIZABLE transaction isolation level this would cause a
serialization failure (with an SQLSTATE of '40001'), so there is no possibility of
receiving rows out of order under these isolation levels.
TABLE Command
The command
TABLE name
is equivalent to
SELECT * FROM name
It can be used as a top-level command or as a space-saving syntax variant in parts of
complex queries. Only the WITH, UNION, INTERSECT, EXCEPT, ORDER BY, LIMIT, OFFSET, FETCH
and FOR locking clauses can be used with TABLE; the WHERE clause and any form of
aggregation cannot be used.
EXAMPLES
To join the table films with the table distributors:
SELECT f.title, f.did, d.name, f.date_prod, f.kind
FROM distributors d JOIN films f USING (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
...
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
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 hours';
kind | total
----------+-------
Comedy | 02:58
Romantic | 04:38
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
The next example shows how to obtain the union of the tables distributors and actors,
restricting the results to those that begin with the letter W in each table. Only distinct
rows are wanted, so the key word ALL 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 function in the FROM clause, both with and without a
column definition list:
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
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
Here is an example of a function with an ordinality column added:
SELECT * FROM unnest(ARRAY['a','b','c','d','e','f']) WITH ORDINALITY;
unnest | ordinality
--------+----------
a | 1
b | 2
c | 3
d | 4
e | 5
f | 6
(6 rows)
This example shows how to use a simple WITH clause:
WITH t AS (
SELECT random() as x FROM generate_series(1, 3)
)
SELECT * FROM t
UNION ALL
SELECT * FROM t;
x
--------------------
0.534150459803641
0.520092216785997
0.0735620250925422
0.534150459803641
0.520092216785997
0.0735620250925422
Notice that the WITH query was evaluated only once, so that we got two sets of the same
three random values.
This example uses WITH RECURSIVE to find all subordinates (direct or indirect) of the
employee Mary, and their level of indirectness, from a table that shows only direct
subordinates:
WITH RECURSIVE employee_recursive(distance, employee_name, manager_name) AS (
SELECT 1, employee_name, manager_name
FROM employee
WHERE manager_name = 'Mary'
UNION ALL
SELECT er.distance + 1, e.employee_name, e.manager_name
FROM employee_recursive er, employee e
WHERE er.employee_name = e.manager_name
)
SELECT distance, employee_name FROM employee_recursive;
Notice the typical form of recursive queries: an initial condition, followed by UNION,
followed by the recursive part of the query. Be sure that the recursive part of the query
will eventually return no tuples, or else the query will loop indefinitely. (See
Section 7.8 for more examples.)
This example uses LATERAL to apply a set-returning function get_product_names() for each
row of the manufacturers table:
SELECT m.name AS mname, pname
FROM manufacturers m, LATERAL get_product_names(m.id) pname;
Manufacturers not currently having any products would not appear in the result, since it
is an inner join. If we wished to include the names of such manufacturers in the result,
we could do:
SELECT m.name AS mname, pname
FROM manufacturers m LEFT JOIN LATERAL get_product_names(m.id) pname ON true;
COMPATIBILITY
Of course, the SELECT statement is compatible with the SQL standard. But there are some
extensions and some missing features.
Omitted FROM Clauses
PostgreSQL allows one to omit the FROM clause. It has a straightforward use to compute the
results of simple expressions:
SELECT 2+2;
?column?
----------
4
Some other SQL databases cannot do this except by introducing a dummy one-row table from
which to do the SELECT.
Empty SELECT Lists
The list of output expressions after SELECT can be empty, producing a zero-column result
table. This is not valid syntax according to the SQL standard. PostgreSQL allows it to be
consistent with allowing zero-column tables. However, an empty list is not allowed when
DISTINCT is used.
Omitting the AS Key Word
In the SQL standard, the optional key word AS can be omitted before an output column name
whenever the new column name is a valid column name (that is, not the same as any reserved
keyword). PostgreSQL is slightly more restrictive: AS is required if the new column name
matches any keyword at all, reserved or not. Recommended practice is to use AS or
double-quote output column names, to prevent any possible conflict against future keyword
additions.
In FROM items, both the standard and PostgreSQL allow AS to be omitted before an alias
that is an unreserved keyword. But this is impractical for output column names, because of
syntactic ambiguities.
Omitting Sub-SELECT Aliases in FROM
According to the SQL standard, a sub-SELECT in the FROM list must have an alias. In
PostgreSQL, this alias may be omitted.
ONLY and Inheritance
The SQL standard requires parentheses around the table name when writing ONLY, for example
SELECT * FROM ONLY (tab1), ONLY (tab2) WHERE .... PostgreSQL considers these parentheses
to be optional.
PostgreSQL allows a trailing * to be written to explicitly specify the non-ONLY behavior
of including child tables. The standard does not allow this.
(These points apply equally to all SQL commands supporting the ONLY option.)
TABLESAMPLE Clause Restrictions
The TABLESAMPLE clause is currently accepted only on regular tables and materialized
views. According to the SQL standard it should be possible to apply it to any FROM item.
Function Calls in FROM
PostgreSQL allows a function call to be written directly as a member of the FROM list. In
the SQL standard it would be necessary to wrap such a function call in a sub-SELECT; that
is, the syntax FROM func(...) alias is approximately equivalent to FROM LATERAL (SELECT
func(...)) alias. Note that LATERAL is considered to be implicit; this is because the
standard requires LATERAL semantics for an UNNEST() item in FROM. PostgreSQL treats
UNNEST() the same as other set-returning functions.
Namespace Available to GROUP BY and ORDER BY
In the SQL-92 standard, an ORDER BY clause can only use output column names or numbers,
while a GROUP BY clause can only use expressions based on input column names. PostgreSQL
extends each of these clauses to allow the other choice as well (but it uses the
standard's interpretation if there is ambiguity). PostgreSQL also allows both clauses to
specify arbitrary expressions. Note that names appearing in an expression will always be
taken as input-column names, not as output-column names.
SQL:1999 and later use a slightly different definition which is not entirely upward
compatible with SQL-92. In most cases, however, PostgreSQL will interpret an ORDER BY or
GROUP BY expression the same way SQL:1999 does.
Functional Dependencies
PostgreSQL recognizes functional dependency (allowing columns to be omitted from GROUP BY)
only when a table's primary key is included in the GROUP BY list. The SQL standard
specifies additional conditions that should be recognized.
LIMIT and OFFSET
The clauses LIMIT and OFFSET are PostgreSQL-specific syntax, also used by MySQL. The
SQL:2008 standard has introduced the clauses OFFSET ... FETCH {FIRST|NEXT} ... for the
same functionality, as shown above in LIMIT Clause. This syntax is also used by IBM DB2.
(Applications written for Oracle frequently use a workaround involving the automatically
generated rownum column, which is not available in PostgreSQL, to implement the effects of
these clauses.)
FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE, FOR KEY SHARE
Although FOR UPDATE appears in the SQL standard, the standard allows it only as an option
of DECLARE CURSOR. PostgreSQL allows it in any SELECT query as well as in sub-SELECTs,
but this is an extension. The FOR NO KEY UPDATE, FOR SHARE and FOR KEY SHARE variants, as
well as the NOWAIT and SKIP LOCKED options, do not appear in the standard.
Data-Modifying Statements in WITH
PostgreSQL allows INSERT, UPDATE, and DELETE to be used as WITH queries. This is not found
in the SQL standard.
Nonstandard Clauses
DISTINCT ON ( ... ) is an extension of the SQL standard.
ROWS FROM( ... ) is an extension of the SQL standard.
The MATERIALIZED and NOT MATERIALIZED options of WITH are extensions of the SQL standard.