Skip site navigation (1)Skip section navigation (2)

FreeBSD Manual Pages


home | help
SELECT(7)		PostgreSQL 9.6.19 Documentation		     SELECT(7)

       SELECT, TABLE, WITH - retrieve rows from	a table	or view

       [ WITH [	RECURSIVE ] with_query [, ...] ]
       SELECT [	ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
	   [ * | expression [ [	AS ] output_name ] [, ...] ]
	   [ FROM from_item [, ...] ]
	   [ WHERE condition ]
	   [ GROUP BY 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 ]
	   [ 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 [ NATURAL ] join_type from_item [ ON join_condition | USING ( join_column [, ...] ) ]

       and grouping_element can	be one of:

	   ( )
	   ( expression	[, ...]	)
	   ROLLUP ( { expression | ( expression	[, ...]	) } [, ...] )
	   CUBE	( { expression | ( expression [, ...] )	} [, ...] )
	   GROUPING SETS ( grouping_element [, ...] )

       and with_query is:

	   with_query_name [ ( column_name [, ...] ) ] AS ( select | values | insert | update |	delete )

       TABLE [ ONLY ] table_name [ * ]

       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. (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.)

	5. The actual output rows are computed using the SELECT	output
	   expressions for each	selected row or	row group. (See	SELECT List

	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

	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.)

	   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.
       requires	UPDATE privilege as well (for at least one column of each
       table so	selected).

   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

       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,	"WITH Queries (Common Table Expressions)", in the
       documentation 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.

       A key property of WITH queries is that they are 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.

       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 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.

       See Section 7.8,	"WITH Queries (Common Table Expressions)", in the
       documentation 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:

	   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.

	   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

	   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.

	   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(7)
	   command can also be used here.

	   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 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.
	   When	the optional WITH ORDINALITY clause is added to	the function
	   call, a new column is appended after	all the	function's output
	   columns with	numbering for each row.

	   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 column added	by
	   ORDINALITY 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( ... ).

	   One of

	   o   [ INNER ] JOIN

	   o   LEFT [ OUTER ] JOIN

	   o   RIGHT [ OUTER ] JOIN

	   o   FULL [ OUTER ] JOIN

	   o   CROSS JOIN

	   For the INNER and OUTER join	types, a join condition	must be
	   specified, namely exactly one of NATURAL, ON	join_condition,	or
	   USING (join_column [, ...]).	See below for the meaning. For CROSS
	   JOIN, none of these clauses can appear.

	   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.

	   CROSS JOIN and INNER	JOIN 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).  CROSS JOIN
	   is equivalent to INNER JOIN ON (TRUE), that is, no rows are removed
	   by qualification. These join	types are just a notational
	   convenience,	since they do nothing you couldn't do with plain FROM
	   and WHERE.

	   LEFT	OUTER JOIN returns all rows in the qualified Cartesian product
	   (i.e., all combined rows that pass its 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

	   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 [, ...] )
	   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.

	   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.

	   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

   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

   GROUP BY Clause
       The optional GROUP BY clause has	the general form

	   GROUP BY 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.	For further details on the
       handling	of grouping sets see Section 7.2.4, "GROUPING SETS, CUBE, and
       ROLLUP",	in the documentation.

       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, "Aggregate Expressions", in the documentation 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,
       "Expression Evaluation Rules", in the documentation.

       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.

       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

       Similarly, the elements of the ORDER BY list are	interpreted in much
       the same	fashion	as elements of an 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 } frame_start
	   { RANGE | ROWS } BETWEEN frame_start	AND frame_end

       where frame_start and frame_end can be one of

	   value PRECEDING
	   value FOLLOWING

       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 than the frame_start choice -- for example RANGE BETWEEN
       CURRENT ROW AND value PRECEDING is not allowed.

       The default framing option is RANGE UNBOUNDED PRECEDING,	which is the
       frame to	be all rows from the partition start up	through	the current
       row's last peer (a row that ORDER BY considers equivalent to the
       current row, or all rows	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 or ROWS
       mode). In ROWS mode, CURRENT ROW	means that the frame starts or ends
       with the	current	row; but in RANGE mode it means	that the frame starts
       or ends with the	current	row's first or last peer in the	ORDER BY
       ordering. The value PRECEDING and value FOLLOWING cases are currently
       only allowed in ROWS mode. They indicate	that the frame starts or ends
       with the	row that many rows before or after the current row.  value
       must be an integer expression not containing any	variables, aggregate
       functions, or window functions. The value must not be null or negative;
       but it can be zero, which selects the current row itself.

       Beware that the ROWS options can	produce	unpredictable results if the
       ORDER BY	ordering does not order	the rows uniquely. The RANGE options
       are designed to ensure that rows	that are peers in the ORDER BY
       ordering	are treated alike; all peer rows will be in the	same frame.

       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.

       cannot be specified with	WINDOW.

       Window functions	are described in detail	in Section 3.5,	"Window
       Functions", in the documentation, Section 4.2.8,	"Window	Function
       Calls", in the documentation, and Section 7.2.5,	"Window	Function
       Processing", in the documentation.

   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

       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,	SQL Key	Words).	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

	   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

       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.

       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,
       (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

       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.

       cannot be specified either for a	UNION result or	for any	input of a

       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,

       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

       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,

       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.

       cannot be specified either for an EXCEPT	result or for any input	of an

   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, "Collation
       Expressions", in	the documentation and Section 23.2, "Collation
       Support", in the	documentation.

   LIMIT Clause
       The LIMIT clause	consists of two	independent sub-clauses:

	   LIMIT { count | ALL }
	   OFFSET start

       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

       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.	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

       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
       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


       For more	information on each row-level lock mode, refer to Section
       13.3.2, "Row-level Locks", in the documentation.

       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,
       Concurrency Control, in the documentation). You can use LOCK(7) 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:

	   SELECT * FROM mytable WHERE key = 1 FOR UPDATE;
	   UPDATE mytable SET ... WHERE	key = 1;

       would fail to preserve the FOR UPDATE lock after	the ROLLBACK TO. This
       has been	fixed in release 9.3.

	   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 a 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

       To join the table films with the	table distributors:

	   SELECT f.title, f.did,, f.date_prod, f.kind
	       FROM distributors d, films f
	       WHERE f.did = d.did

		  title	      |	did |	  name	   | date_prod	|   kind
	    The	Third Man     |	101 | British Lion | 1949-12-23	| Drama
	    The	African	Queen |	101 | British Lion | 1951-08-11	| Romantic

       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
	    ...				...

	       FROM distributors
	       WHERE LIKE 'W%'
	       FROM actors
	       WHERE LIKE 'W%';

	    Walt Disney
	    Walter Matthau
	    Warner Bros.
	    Warren Beatty
	    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;

	   SELECT * FROM distributors(111);
	    did	|    name
	    111	| Walt Disney

	   CREATE FUNCTION distributors_2(int) RETURNS SETOF record AS $$
	       SELECT *	FROM distributors WHERE	did = $1;

	   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)


       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'
	       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, "WITH
       Queries (Common Table Expressions)", in the documentation for more

       This example uses LATERAL to apply a set-returning function
       get_product_names() for each row	of the manufacturers table:

	   SELECT AS mname, pname
	   FROM	manufacturers m, LATERAL get_product_names( 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 AS mname, pname
	   FROM	manufacturers m	LEFT JOIN LATERAL get_product_names( pname	ON true;

       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;


       Some other SQL databases	cannot do this except by introducing a dummy
       one-row table from which	to do the SELECT.

       Note that if a FROM clause is not specified, the	query cannot reference
       any database tables. For	example, the following query is	invalid:

	   SELECT distributors.* WHERE = 'Westward';

       PostgreSQL releases prior to 8.1	would accept queries of	this form, and
       add an implicit entry to	the query's FROM clause	for each table
       referenced by the query.	This is	no longer allowed.

   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

   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.

   WINDOW Clause Restrictions
       The SQL standard	provides additional options for	the window
       frame_clause.  PostgreSQL currently supports only the options listed

       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.)

       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.

PostgreSQL 9.6.19		     2020			     SELECT(7)


Want to link to this manual page? Use this URL:

home | help