SELECT(7) PostgreSQL 15.7 Documentation SELECT(7)
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 must be provided for it. 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.
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.
PostgreSQL 15.7 2024 SELECT(7)
Generated by dwww version 1.15 on Sat Jun 29 02:19:23 CEST 2024.