Synopsis
Use the SELECT
statement to retrieve rows of specified columns that meet a given condition from a table. It specifies the columns to be retrieved, the name of the table, and the condition each selected row must satisfy.
The same syntax rules govern a subquery, wherever you might use one—like, for example, in an INSERT
statement. Certain syntax spots, for example a WHERE
clause predicate or the actual argument of a function like sqrt()
, allow only a scalar subquery.
Syntax
select ::= [ with_clause ] SELECT select_list
[ trailing_select_clauses ]
with_clause ::= WITH [ RECURSIVE ]
{ common_table_expression [ , ... ] }
select_list ::= [ ALL | DISTINCT [ ON { ( expression [ , ... ] ) } ] ]
[ * | { { expression
| fn_over_window
| ordinary_aggregate_fn_invocation
| within_group_aggregate_fn_invocation }
[ [ AS ] name ] } [ , ... ] ]
trailing_select_clauses ::= [ FROM { from_item [ , ... ] } ]
[ WHERE boolean_expression ]
[ GROUP BY { grouping_element [ , ... ] } ]
[ HAVING boolean_expression ]
[ WINDOW
{ { name AS window_definition }
[ , ... ] } ]
[ { UNION | INTERSECT | EXCEPT }
[ ALL | DISTINCT ] select ]
[ ORDER BY { order_expr [ , ... ] } ]
[ LIMIT { int_expression | ALL } ]
[ OFFSET int_expression [ ROW | ROWS ] ]
[ FETCH { FIRST | NEXT } int_expression
{ ROW | ROWS } ONLY ]
[ FOR { UPDATE
| NO KEY UPDATE
| SHARE
| KEY SHARE }
[ OF table_name [ , ... ] ]
[ NOWAIT | SKIP LOCKED ] [ ... ] ]
common_table_expression ::= cte_name [ ( column_name [ , ... ] ) ] AS
( { select
| values
| insert
| update
| delete } )
fn_over_window ::= name ( [ expression [ , ... ] | * ]
[ FILTER ( WHERE boolean_expression ) ] OVER
{ window_definition | name }
ordinary_aggregate_fn_invocation ::= name (
{ [ ALL | DISTINCT ] expression
[ , ... ]
| * }
[ ORDER BY order_expr [ , ... ] ]
) [ FILTER ( WHERE
boolean_expression ) ]
within_group_aggregate_fn_invocation ::= name (
{ expression [ , ... ] } )
WITHIN GROUP ( ORDER BY
order_expr [ , ... ] )
[ FILTER ( WHERE
boolean_expression ) ]
grouping_element ::= ( ) | ( expression [ , ... ] )
| ROLLUP ( expression [ , ... ] )
| CUBE ( expression [ , ... ] )
| GROUPING SETS ( grouping_element [ , ... ] )
order_expr ::= expression [ ASC | DESC | USING operator_name ]
[ NULLS { FIRST | LAST } ]
See the section The WITH clause and common table expressions for more information about the semantics of the common_table_expression
grammar rule.
Semantics
- An error is raised if the specified
table_name
does not exist. *
represents all columns.
While the where clause allows a wide range of operators, the exact conditions used in the where clause have significant performance considerations (especially for large datasets).
For details on from_item
see SELECT in the PostgreSQL documentation.
The fn_over_window
rule denotes the special kind of SELECT
list item that must be used to invoke a window function and that may be used to invoke an aggregate function. (Window functions are known as analytic functions in the terminology of some SQL database systems.) The dedicated diagram that follows the main diagram for the select
rule shows the FILTER
and the OVER
keywords. You can see that you cannot invoke a function in this way without specifying an OVER
clause—and that the OVER
clause requires the specification of the so-called window that gives this invocation style its name. The FILTER
clause is optional and may be used only when you invoke an aggregate function in this way. All of this is explained in the Window function invocation—SQL syntax and semantics section within the major section Window functions.
The ordinary_aggregate_fn_invocation
rule and the within_group_aggregate_fn_invocation
rule denote the special kinds of SELECT
list item that are used to invoke an aggregate function (when it isn't invoked as a window function). When an aggregate function is invoked in either of these two ways, it's very common to do so in conjunction with the GROUP BY
and HAVING
clauses. All of this is explained in the Aggregate function invocation—SQL syntax and semantics section within the major section Aggregate functions.
When you understand the story of the invocation of these two kinds of functions from the accounts in the Window functions section and the Aggregate functions section, you can use the \df
meta-command in ysqlsh
to discover the status of a particular function, thus:
\df row_number
... | Argument data types | Type
... +----------------------------------------+--------
... | | window
\df rank
... | Argument data types | Type
... +----------------------------------------+--------
... | | window
... | VARIADIC "any" ORDER BY VARIADIC "any" | agg
\df avg
... | Argument data types | Type
... +----------------------------------------+--------
... | bigint | agg
... | <other data types> | agg
-
A function whose type is listed as "window" can be invoked only as a window function. See this account of
row_number()
. -
A function whose type is listed both as "window" and as agg can be invoked:
-
either as a window function using the
fn_over_window
syntax—see this account ofrank()
-
or as a so-called within-group hypothetical-set aggregate function using the
within_group_aggregate_fn_invocation
syntax—see this account ofrank()
.
-
-
A function whose type is listed only as "agg" can, in fact, be invoked either as an aggregate function using the
ordinary_aggregate_fn_invocation
syntax or as a window function using thefn_over_window
syntax. Theavg()
function is described in the "Aggregate functions" major section in the subsectionavg()
,count()
,max()
,min()
,sum()
. See its subsectionsGROUP BY
syntax andOVER
syntax for, respectively, theordinary_aggregate_fn_invocation
and thefn_over_window
invocation alternatives. -
Notice that the three functions
mode()
,percentile_disc()
, andpercentile_cont()
are exceptions to this general rule (and they are the only exceptions). These functions are referred to as within-group ordered-set aggregate functions.\df
lists the type of these functions only as "agg". But these cannot be invoked as window functions. The attempt causes this error:42809: WITHIN GROUP is required for ordered-set aggregate mode
Note: The documentation in the Aggregate functions major section usually refers to the syntax that the ordinary_aggregate_fn_invocation
rule and the within_group_aggregate_fn_invocation
rule jointly govern as the GROUP BY
syntax because it's these two syntax variants (and only these two) can be used together with the GROUP BY
clause (and therefore the HAVING
clause). And it usually refers to the syntax that the fn_over_window
rule governs as the OVER
syntax because this syntax variant requires the use of the OVER
clause. Moreover, the use of the GROUP BY
clause (and therefore the HAVING
clause) is illegal with this syntax variant.
Examples
Create two sample tables.
yugabyte=# CREATE TABLE sample1(k1 bigint, k2 float, v text, PRIMARY KEY (k1, k2));
yugabyte=# CREATE TABLE sample2(k1 bigint, k2 float, v text, PRIMARY KEY (k1, k2));
Insert some rows.
yugabyte=# INSERT INTO sample1(k1, k2, v) VALUES (1, 2.5, 'abc'), (1, 3.5, 'def'), (1, 4.5, 'xyz');
yugabyte=# INSERT INTO sample2(k1, k2, v) VALUES (1, 2.5, 'foo'), (1, 4.5, 'bar');
Select from both tables using join.
yugabyte=# SELECT a.k1, a.k2, a.v as av, b.v as bv FROM sample1 a LEFT JOIN sample2 b ON (a.k1 = b.k1 and a.k2 = b.k2) WHERE a.k1 = 1 AND a.k2 IN (2.5, 3.5) ORDER BY a.k2 DESC;
k1 | k2 | av | bv
----+-----+-----+-----
1 | 3.5 | def |
1 | 2.5 | abc | foo
(2 rows)