SELECT, TABLE, WITH — retrieve rows from a table or view
[ WITH [ RECURSIVE ]with_query[, ...] ] SELECT [ ALL | DISTINCT [ ON (expression[, ...] ) ] ] [ * |expression[ [ AS ]output_name] [, ...] ] [ FROMfrom_item[, ...] ] [ WHEREcondition] [ GROUP BYgrouping_element[, ...] ] [ HAVINGcondition[, ...] ] [ WINDOWwindow_nameAS (window_definition) [, ...] ] [ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ]select] [ ORDER BYexpression[ ASC | DESC | USINGoperator] [ NULLS { FIRST | LAST } ] [, ...] ] [ LIMIT {count| ALL } ] [ OFFSETstart[ ROW | ROWS ] ] [ FETCH { FIRST | NEXT } [count] { ROW | ROWS } ONLY ] [ FOR { UPDATE | NO KEY UPDATE | SHARE | KEY SHARE } [ OFtable_name[, ...] ] [ NOWAIT | SKIP LOCKED ] [...] ] wherefrom_itemcan be one of: [ ONLY ]table_name[ * ] [ [ AS ]alias[ (column_alias[, ...] ) ] ] [ TABLESAMPLEsampling_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_typefrom_item[ ONjoin_condition| USING (join_column[, ...] ) ] andgrouping_elementcan be one of: ( )expression(expression[, ...] ) ROLLUP ( {expression| (expression[, ...] ) } [, ...] ) CUBE ( {expression| (expression[, ...] ) } [, ...] ) GROUPING SETS (grouping_element[, ...] ) andwith_queryis: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:
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.)
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.)
If the WHERE clause is specified, all rows
that do not satisfy the condition are eliminated from the
output. (See WHERE Clause below.)
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.)
The actual output rows are computed using the
SELECT output expressions for each selected
row or row group. (See
SELECT List
below.)
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.)
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.)
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.)
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.)
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).
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_termUNION [ 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.
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.
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 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.
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 ( . The column definition list must match the
actual number and types of columns returned by the function.
column_name data_type [, ...
])
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_typeOne of
[ INNER ] JOIN
LEFT [ OUTER ] JOIN
RIGHT [ OUTER ] JOIN
FULL [ OUTER ] JOIN
CROSS JOIN
For the INNER and OUTER join types, a
join condition must be specified, namely exactly one of
NATURAL, ON , or
join_conditionUSING (.
See below for the meaning. For join_column [, ...])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 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_conditionjoin_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 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.
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 YY 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 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.
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
WINDOWwindow_nameAS (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 BYexpression[, ...] ] [ ORDER BYexpression[ ASC | DESC | USINGoperator] [ 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 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
UNBOUNDED PRECEDINGvaluePRECEDING CURRENT ROWvalueFOLLOWING UNBOUNDED 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 is not allowed.
value
PRECEDING
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 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.
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;
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.
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 (
keeps only the first row of each set of rows where the given
expressions evaluate to equal. The expression [, ...] )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_statementUNION [ 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_statementINTERSECT [ 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_statementEXCEPT [ 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 BYexpression[ ASC | DESC | USINGoperator] [ 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 23.2.
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:
OFFSETstart{ ROW | ROWS } FETCH { FIRST | NEXT } [count] { ROW | ROWS } ONLY
In this syntax, to write anything except a simple integer constant for
start or count, you must write parentheses
around it.
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 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.
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
FORlock_strength[ OFtable_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.
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 CommandThe command
TABLE nameis 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.
To join the table films with the table
distributors:
SELECT f.title, f.did, d.name, f.date_prod, f.kind
FROM distributors d, films f
WHERE f.did = d.did
title | did | name | date_prod | kind
-------------------+-----+--------------+------------+----------
The Third Man | 101 | British Lion | 1949-12-23 | Drama
The African Queen | 101 | British Lion | 1951-08-11 | Romantic
...
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;
Of course, the SELECT statement is compatible
with the SQL standard. But there are some extensions and some
missing features.
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.
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 distributors.name = '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.
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.
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.
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
is approximately equivalent to
func(...) aliasFROM LATERAL (SELECT .
Note that func(...)) aliasLATERAL 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.
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.
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 above.
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.
WITH PostgreSQL allows INSERT,
UPDATE, and DELETE to be used as WITH
queries. This is not found in the SQL standard.
DISTINCT ON ( ... ) is an extension of the
SQL standard.
ROWS FROM( ... ) is an extension of the SQL standard.