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SELECT

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

Synopsis

[ WITH [ RECURSIVE ] with_query [, ...] ]
SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]
    [ { * | expression [ [ AS ] output_name ] } [, ...] ]
    [ FROM from_item [, ...] ]
    [ WHERE condition ]
    [ GROUP BY [ ALL | DISTINCT ] grouping_element [, ...] ]
    [ HAVING condition ]
    [ WINDOW window_name AS ( window_definition ) [, ...] ]
    [ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] select ]
    [ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST
 } ] [, ...] ]
    [ LIMIT { count | ALL } ]
    [ OFFSET start [ ROW | ROWS ] ]
    [ FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } { ONLY | WITH TIES } ]
    [ FOR { UPDATE | NO KEY UPDATE | SHARE | KEY SHARE } [ OF from_reference [,
...] ] [ 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_def
inition [, ...] )
    [ LATERAL ] function_name ( [ argument [, ...] ] ) AS ( column_definition [,
 ...] )
    [ LATERAL ] ROWS FROM( function_name ( [ argument [, ...] ] ) [ AS ( column_
definition [, ...] ) ] [, ...] )
                [ WITH ORDINALITY ] [ [ AS ] alias [ ( column_alias [, ...] ) ]
]
    from_item join_type from_item { ON join_condition | USING ( join_column [, .
..] ) [ AS join_using_alias ] }
    from_item NATURAL join_type from_item
    from_item CROSS JOIN from_item

and grouping_element can be one of:

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

and with_query is:

    with_query_name [ ( column_name [, ...] ) ] AS [ [ NOT ] MATERIALIZED ] ( se
lect | values | insert | update | delete | merge )
        [ SEARCH { BREADTH | DEPTH } FIRST BY column_name [, ...] SET search_seq
_col_name ]
        [ CYCLE column_name [, ...] SET cycle_mark_col_name [ TO cycle_mark_valu
e DEFAULT cycle_mark_default ] USING cycle_path_col_name ]

TABLE [ ONLY ] table_name [ * ]

Description

   SELECT retrieves rows from zero or more tables. The general processing
   of SELECT is as follows:
    1. All queries in the WITH list are computed. These effectively serve
       as temporary tables that can be referenced in the FROM list. A WITH
       query that is referenced more than once in FROM is computed only
       once, unless specified otherwise with NOT MATERIALIZED. (See WITH
       Clause below.)
    2. All elements in the FROM list are computed. (Each element in the
       FROM list is a real or virtual table.) If more than one element is
       specified in the FROM list, they are cross-joined together. (See
       FROM Clause below.)
    3. If the WHERE clause is specified, all rows that do not satisfy the
       condition are eliminated from the output. (See WHERE Clause below.)
    4. If the GROUP BY clause is specified, or if there are aggregate
       function calls, the output is combined into groups of rows that
       match on one or more values, and the results of aggregate functions
       are computed. If the HAVING clause is present, it eliminates groups
       that do not satisfy the given condition. (See GROUP BY Clause and
       HAVING Clause below.) Although query output columns are nominally
       computed in the next step, they can also be referenced (by name or
       ordinal number) in the GROUP BY clause.
    5. The actual output rows are computed using the SELECT output
       expressions for each selected row or row group. (See SELECT List
       below.)
    6. SELECT DISTINCT eliminates duplicate rows from the result. SELECT
       DISTINCT ON eliminates rows that match on all the specified
       expressions. SELECT ALL (the default) will return all candidate
       rows, including duplicates. (See DISTINCT Clause below.)
    7. Using the operators UNION, INTERSECT, and EXCEPT, the output of
       more than one SELECT statement can be combined to form a single
       result set. The UNION operator returns all rows that are in one or
       both of the result sets. The INTERSECT operator returns all rows
       that are strictly in both result sets. The EXCEPT operator returns
       the rows that are in the first result set but not in the second. In
       all three cases, duplicate rows are eliminated unless ALL is
       specified. The noise word DISTINCT can be added to explicitly
       specify eliminating duplicate rows. Notice that DISTINCT is the
       default behavior here, even though ALL is the default for SELECT
       itself. (See UNION Clause, INTERSECT Clause, and EXCEPT Clause
       below.)
    8. If the ORDER BY clause is specified, the returned rows are sorted
       in the specified order. If ORDER BY is not given, the rows are
       returned in whatever order the system finds fastest to produce.
       (See ORDER BY Clause below.)
    9. If the LIMIT (or FETCH FIRST) or OFFSET clause is specified, the
       SELECT statement only returns a subset of the result rows. (See
       LIMIT Clause below.)
   10. If FOR UPDATE, FOR NO KEY UPDATE, FOR SHARE or FOR KEY SHARE is
       specified, the SELECT statement locks the selected rows against
       concurrent updates. (See The Locking Clause below.)

   You must have SELECT privilege on each column used in a SELECT command.
   The use of FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE or FOR KEY SHARE
   requires UPDATE privilege as well (for at least one column of each
   table so selected).

Parameters

WITH Clause

   The WITH clause allows you to specify one or more subqueries that can
   be referenced by name in the primary query. The subqueries effectively
   act as temporary tables or views for the duration of the primary query.
   Each subquery can be a SELECT, TABLE, VALUES, INSERT, UPDATE, DELETE,
   or MERGE statement. When writing a data-modifying statement (INSERT,
   UPDATE, DELETE, or MERGE) in WITH, it is usual to include a RETURNING
   clause. It is the output of RETURNING, not the underlying table that
   the statement modifies, that forms the temporary table that is read by
   the primary query. If RETURNING is omitted, the statement is still
   executed, but it produces no output so it cannot be referenced as a
   table by the primary query.

   A name (without schema qualification) must be specified for each WITH
   query. Optionally, a list of column names can be specified; if this is
   omitted, the column names are inferred from the subquery.

   If RECURSIVE is specified, it allows a SELECT subquery to reference
   itself by name. Such a subquery must have the form
non_recursive_term UNION [ ALL | DISTINCT ] recursive_term

   where the recursive self-reference must appear on the right-hand side
   of the UNION. Only one recursive self-reference is permitted per query.
   Recursive data-modifying statements are not supported, but you can use
   the results of a recursive SELECT query in a data-modifying statement.
   See Section 7.8 for an example.

   Another effect of RECURSIVE is that WITH queries need not be ordered: a
   query can reference another one that is later in the list. (However,
   circular references, or mutual recursion, are not implemented.) Without
   RECURSIVE, WITH queries can only reference sibling WITH queries that
   are earlier in the WITH list.

   When there are multiple queries in the WITH clause, RECURSIVE should be
   written only once, immediately after WITH. It applies to all queries in
   the WITH clause, though it has no effect on queries that do not use
   recursion or forward references.

   The optional SEARCH clause computes a search sequence column that can
   be used for ordering the results of a recursive query in either
   breadth-first or depth-first order. The supplied column name list
   specifies the row key that is to be used for keeping track of visited
   rows. A column named search_seq_col_name will be added to the result
   column list of the WITH query. This column can be ordered by in the
   outer query to achieve the respective ordering. See Section 7.8.2.1 for
   examples.

   The optional CYCLE clause is used to detect cycles in recursive
   queries. The supplied column name list specifies the row key that is to
   be used for keeping track of visited rows. A column named
   cycle_mark_col_name will be added to the result column list of the WITH
   query. This column will be set to cycle_mark_value when a cycle has
   been detected, else to cycle_mark_default. Furthermore, processing of
   the recursive union will stop when a cycle has been detected.
   cycle_mark_value and cycle_mark_default must be constants and they must
   be coercible to a common data type, and the data type must have an
   inequality operator. (The SQL standard requires that they be Boolean
   constants or character strings, but PostgreSQL does not require that.)
   By default, TRUE and FALSE (of type boolean) are used. Furthermore, a
   column named cycle_path_col_name will be added to the result column
   list of the WITH query. This column is used internally for tracking
   visited rows. See Section 7.8.2.2 for examples.

   Both the SEARCH and the CYCLE clause are only valid for recursive WITH
   queries. The with_query must be a UNION (or UNION ALL) of two SELECT
   (or equivalent) commands (no nested UNIONs). If both clauses are used,
   the column added by the SEARCH clause appears before the columns added
   by the CYCLE clause.

   The primary query and the WITH queries are all (notionally) executed at
   the same time. This implies that the effects of a data-modifying
   statement in WITH cannot be seen from other parts of the query, other
   than by reading its RETURNING output. If two such data-modifying
   statements attempt to modify the same row, the results are unspecified.

   A key property of WITH queries is that they are normally evaluated only
   once per execution of the primary query, even if the primary query
   refers to them more than once. In particular, data-modifying statements
   are guaranteed to be executed once and only once, regardless of whether
   the primary query reads all or any of their output.

   However, a WITH query can be marked NOT MATERIALIZED to remove this
   guarantee. In that case, the WITH query can be folded into the primary
   query much as though it were a simple sub-SELECT in the primary query's
   FROM clause. This results in duplicate computations if the primary
   query refers to that WITH query more than once; but if each such use
   requires only a few rows of the WITH query's total output, NOT
   MATERIALIZED can provide a net savings by allowing the queries to be
   optimized jointly. NOT MATERIALIZED is ignored if it is attached to a
   WITH query that is recursive or is not side-effect-free (i.e., is not a
   plain SELECT containing no volatile functions).

   By default, a side-effect-free WITH query is folded into the primary
   query if it is used exactly once in the primary query's FROM clause.
   This allows joint optimization of the two query levels in situations
   where that should be semantically invisible. However, such folding can
   be prevented by marking the WITH query as MATERIALIZED. That might be
   useful, for example, if the WITH query is being used as an optimization
   fence to prevent the planner from choosing a bad plan. PostgreSQL
   versions before v12 never did such folding, so queries written for
   older versions might rely on WITH to act as an optimization fence.

   See Section 7.8 for additional information.

FROM Clause

   The FROM clause specifies one or more source tables for the SELECT. If
   multiple sources are specified, the result is the Cartesian product
   (cross join) of all the sources. But usually qualification conditions
   are added (via WHERE) to restrict the returned rows to a small subset
   of the Cartesian product.

   The FROM clause can contain the following elements:

   table_name
          The name (optionally schema-qualified) of an existing table or
          view. If ONLY is specified before the table name, only that
          table is scanned. If ONLY is not specified, the table and all
          its descendant tables (if any) are scanned. Optionally, * can be
          specified after the table name to explicitly indicate that
          descendant tables are included.

   alias
          A substitute name for the FROM item containing the alias. An
          alias is used for brevity or to eliminate ambiguity for
          self-joins (where the same table is scanned multiple times).
          When an alias is provided, it completely hides the actual name
          of the table or function; for example given FROM foo AS f, the
          remainder of the SELECT must refer to this FROM item as f not
          foo. If an alias is written, a column alias list can also be
          written to provide substitute names for one or more columns of
          the table.

   TABLESAMPLE sampling_method ( argument [, ...] ) [ REPEATABLE ( seed )
          ]
          A TABLESAMPLE clause after a table_name indicates that the
          specified sampling_method should be used to retrieve a subset of
          the rows in that table. This sampling precedes the application
          of any other filters such as WHERE clauses. The standard
          PostgreSQL distribution includes two sampling methods, BERNOULLI
          and SYSTEM, and other sampling methods can be installed in the
          database via extensions.

          The BERNOULLI and SYSTEM sampling methods each accept a single
          argument which is the fraction of the table to sample, expressed
          as a percentage between 0 and 100. This argument can be any
          real-valued expression. (Other sampling methods might accept
          more or different arguments.) These two methods each return a
          randomly-chosen sample of the table that will contain
          approximately the specified percentage of the table's rows. The
          BERNOULLI method scans the whole table and selects or ignores
          individual rows independently with the specified probability.
          The SYSTEM method does block-level sampling with each block
          having the specified chance of being selected; all rows in each
          selected block are returned. The SYSTEM method is significantly
          faster than the BERNOULLI method when small sampling percentages
          are specified, but it may return a less-random sample of the
          table as a result of clustering effects.

          The optional REPEATABLE clause specifies a seed number or
          expression to use for generating random numbers within the
          sampling method. The seed value can be any non-null
          floating-point value. Two queries that specify the same seed and
          argument values will select the same sample of the table, if the
          table has not been changed meanwhile. But different seed values
          will usually produce different samples. If REPEATABLE is not
          given then a new random sample is selected for each query, based
          upon a system-generated seed. Note that some add-on sampling
          methods do not accept REPEATABLE, and will always produce new
          samples on each use.

   select
          A sub-SELECT can appear in the FROM clause. This acts as though
          its output were created as a temporary table for the duration of
          this single SELECT command. Note that the sub-SELECT must be
          surrounded by parentheses, and an alias can be provided in the
          same way as for a table. A VALUES command can also be used here.

   with_query_name
          A WITH query is referenced by writing its name, just as though
          the query's name were a table name. (In fact, the WITH query
          hides any real table of the same name for the purposes of the
          primary query. If necessary, you can refer to a real table of
          the same name by schema-qualifying the table's name.) An alias
          can be provided in the same way as for a table.

   function_name
          Function calls can appear in the FROM clause. (This is
          especially useful for functions that return result sets, but any
          function can be used.) This acts as though the function's output
          were created as a temporary table for the duration of this
          single SELECT command. If the function's result type is
          composite (including the case of a function with multiple OUT
          parameters), each attribute becomes a separate column in the
          implicit table.

          When the optional WITH ORDINALITY clause is added to the
          function call, an additional column of type bigint will be
          appended to the function's result column(s). This column numbers
          the rows of the function's result set, starting from 1. By
          default, this column is named ordinality.

          An alias can be provided in the same way as for a table. If an
          alias is written, a column alias list can also be written to
          provide substitute names for one or more attributes of the
          function's composite return type, including the ordinality
          column if present.

          Multiple function calls can be combined into a single
          FROM-clause item by surrounding them with ROWS FROM( ... ). The
          output of such an item is the concatenation of the first row
          from each function, then the second row from each function, etc.
          If some of the functions produce fewer rows than others, null
          values are substituted for the missing data, so that the total
          number of rows returned is always the same as for the function
          that produced the most rows.

          If the function has been defined as returning the record data
          type, then an alias or the key word AS must be present, followed
          by a column definition list in the form ( column_name data_type
          [, ... ]). The column definition list must match the actual
          number and types of columns returned by the function.

          When using the ROWS FROM( ... ) syntax, if one of the functions
          requires a column definition list, it's preferred to put the
          column definition list after the function call inside ROWS FROM(
          ... ). A column definition list can be placed after the ROWS
          FROM( ... ) construct only if there's just a single function and
          no WITH ORDINALITY clause.

          To use ORDINALITY together with a column definition list, you
          must use the ROWS FROM( ... ) syntax and put the column
          definition list inside ROWS FROM( ... ).

   join_type
          One of

          + [ INNER ] JOIN
          + LEFT [ OUTER ] JOIN
          + RIGHT [ OUTER ] JOIN
          + FULL [ OUTER ] JOIN

          For the INNER and OUTER join types, a join condition must be
          specified, namely exactly one of ON join_condition, USING
          (join_column [, ...]), or NATURAL. See below for the meaning.

          A JOIN clause combines two FROM items, which for convenience we
          will refer to as “tables”, though in reality they can be any
          type of FROM item. Use parentheses if necessary to determine the
          order of nesting. In the absence of parentheses, JOINs nest
          left-to-right. In any case JOIN binds more tightly than the
          commas separating FROM-list items. All the JOIN options are just
          a notational convenience, since they do nothing you couldn't do
          with plain FROM and WHERE.

          LEFT OUTER JOIN returns all rows in the qualified Cartesian
          product (i.e., all combined rows that pass its join condition),
          plus one copy of each row in the left-hand table for which there
          was no right-hand row that passed the join condition. This
          left-hand row is extended to the full width of the joined table
          by inserting null values for the right-hand columns. Note that
          only the JOIN clause's own condition is considered while
          deciding which rows have matches. Outer conditions are applied
          afterwards.

          Conversely, RIGHT OUTER JOIN returns all the joined rows, plus
          one row for each unmatched right-hand row (extended with nulls
          on the left). This is just a notational convenience, since you
          could convert it to a LEFT OUTER JOIN by switching the left and
          right tables.

          FULL OUTER JOIN returns all the joined rows, plus one row for
          each unmatched left-hand row (extended with nulls on the right),
          plus one row for each unmatched right-hand row (extended with
          nulls on the left).

   ON join_condition
          join_condition is an expression resulting in a value of type
          boolean (similar to a WHERE clause) that specifies which rows in
          a join are considered to match.

   USING ( join_column [, ...] ) [ AS join_using_alias ]
          A clause of the form USING ( a, b, ... ) is shorthand for ON
          left_table.a = right_table.a AND left_table.b = right_table.b
          .... Also, USING implies that only one of each pair of
          equivalent columns will be included in the join output, not
          both.

          If a join_using_alias name is specified, it provides a table
          alias for the join columns. Only the join columns listed in the
          USING clause are addressable by this name. Unlike a regular
          alias, this does not hide the names of the joined tables from
          the rest of the query. Also unlike a regular alias, you cannot
          write a column alias list — the output names of the join columns
          are the same as they appear in the USING list.

   NATURAL
          NATURAL is shorthand for a USING list that mentions all columns
          in the two tables that have matching names. If there are no
          common column names, NATURAL is equivalent to ON TRUE.

   CROSS JOIN
          CROSS JOIN is equivalent to INNER JOIN ON (TRUE), that is, no
          rows are removed by qualification. They produce a simple
          Cartesian product, the same result as you get from listing the
          two tables at the top level of FROM, but restricted by the join
          condition (if any).

   LATERAL
          The LATERAL key word can precede a sub-SELECT FROM item. This
          allows the sub-SELECT to refer to columns of FROM items that
          appear before it in the FROM list. (Without LATERAL, each
          sub-SELECT is evaluated independently and so cannot
          cross-reference any other FROM item.)

          LATERAL can also precede a function-call FROM item, but in this
          case it is a noise word, because the function expression can
          refer to earlier FROM items in any case.

          A LATERAL item can appear at top level in the FROM list, or
          within a JOIN tree. In the latter case it can also refer to any
          items that are on the left-hand side of a JOIN that it is on the
          right-hand side of.

          When a FROM item contains LATERAL cross-references, evaluation
          proceeds as follows: for each row of the FROM item providing the
          cross-referenced column(s), or set of rows of multiple FROM
          items providing the columns, the LATERAL item is evaluated using
          that row or row set's values of the columns. The resulting
          row(s) are joined as usual with the rows they were computed
          from. This is repeated for each row or set of rows from the
          column source table(s).

          The column source table(s) must be INNER or LEFT joined to the
          LATERAL item, else there would not be a well-defined set of rows
          from which to compute each set of rows for the LATERAL item.
          Thus, although a construct such as X RIGHT JOIN LATERAL Y is
          syntactically valid, it is not actually allowed for Y to
          reference X.

WHERE Clause

   The optional WHERE clause has the general form
WHERE condition

   where condition is any expression that evaluates to a result of type
   boolean. Any row that does not satisfy this condition will be
   eliminated from the output. A row satisfies the condition if it returns
   true when the actual row values are substituted for any variable
   references.

GROUP BY Clause

   The optional GROUP BY clause has the general form
GROUP BY [ ALL | DISTINCT ] grouping_element [, ...]

   GROUP BY will condense into a single row all selected rows that share
   the same values for the grouped expressions. An expression used inside
   a grouping_element can be an input column name, or the name or ordinal
   number of an output column (SELECT list item), or an arbitrary
   expression formed from input-column values. In case of ambiguity, a
   GROUP BY name will be interpreted as an input-column name rather than
   an output column name.

   If any of GROUPING SETS, ROLLUP or CUBE are present as grouping
   elements, then the GROUP BY clause as a whole defines some number of
   independent grouping sets. The effect of this is equivalent to
   constructing a UNION ALL between subqueries with the individual
   grouping sets as their GROUP BY clauses. The optional DISTINCT clause
   removes duplicate sets before processing; it does not transform the
   UNION ALL into a UNION DISTINCT. For further details on the handling of
   grouping sets see Section 7.2.4.

   Aggregate functions, if any are used, are computed across all rows
   making up each group, producing a separate value for each group. (If
   there are aggregate functions but no GROUP BY clause, the query is
   treated as having a single group comprising all the selected rows.) The
   set of rows fed to each aggregate function can be further filtered by
   attaching a FILTER clause to the aggregate function call; see
   Section 4.2.7 for more information. When a FILTER clause is present,
   only those rows matching it are included in the input to that aggregate
   function.

   When GROUP BY is present, or any aggregate functions are present, it is
   not valid for the SELECT list expressions to refer to ungrouped columns
   except within aggregate functions or when the ungrouped column is
   functionally dependent on the grouped columns, since there would
   otherwise be more than one possible value to return for an ungrouped
   column. A functional dependency exists if the grouped columns (or a
   subset thereof) are the primary key of the table containing the
   ungrouped column.

   Keep in mind that all aggregate functions are evaluated before
   evaluating any “scalar” expressions in the HAVING clause or SELECT
   list. This means that, for example, a CASE expression cannot be used to
   skip evaluation of an aggregate function; see Section 4.2.14.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified with GROUP BY.

HAVING Clause

   The optional HAVING clause has the general form
HAVING condition

   where condition is the same as specified for the WHERE clause.

   HAVING eliminates group rows that do not satisfy the condition. HAVING
   is different from WHERE: WHERE filters individual rows before the
   application of GROUP BY, while HAVING filters group rows created by
   GROUP BY. Each column referenced in condition must unambiguously
   reference a grouping column, unless the reference appears within an
   aggregate function or the ungrouped column is functionally dependent on
   the grouping columns.

   The presence of HAVING turns a query into a grouped query even if there
   is no GROUP BY clause. This is the same as what happens when the query
   contains aggregate functions but no GROUP BY clause. All the selected
   rows are considered to form a single group, and the SELECT list and
   HAVING clause can only reference table columns from within aggregate
   functions. Such a query will emit a single row if the HAVING condition
   is true, zero rows if it is not true.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified with HAVING.

WINDOW Clause

   The optional WINDOW clause has the general form
WINDOW window_name AS ( window_definition ) [, ...]

   where window_name is a name that can be referenced from OVER clauses or
   subsequent window definitions, and window_definition is
[ existing_window_name ]
[ PARTITION BY expression [, ...] ]
[ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ]
 [, ...] ]
[ frame_clause ]

   If an existing_window_name is specified it must refer to an earlier
   entry in the WINDOW list; the new window copies its partitioning clause
   from that entry, as well as its ordering clause if any. In this case
   the new window cannot specify its own PARTITION BY clause, and it can
   specify ORDER BY only if the copied window does not have one. The new
   window always uses its own frame clause; the copied window must not
   specify a frame clause.

   The elements of the PARTITION BY list are interpreted in much the same
   fashion as elements of a GROUP BY clause, except that they are always
   simple expressions and never the name or number of an output column.
   Another difference is that these expressions can contain aggregate
   function calls, which are not allowed in a regular GROUP BY clause.
   They are allowed here because windowing occurs after grouping and
   aggregation.

   Similarly, the elements of the ORDER BY list are interpreted in much
   the same fashion as elements of a statement-level ORDER BY clause,
   except that the expressions are always taken as simple expressions and
   never the name or number of an output column.

   The optional frame_clause defines the window frame for window functions
   that depend on the frame (not all do). The window frame is a set of
   related rows for each row of the query (called the current row). The
   frame_clause can be one of
{ RANGE | ROWS | GROUPS } frame_start [ frame_exclusion ]
{ RANGE | ROWS | GROUPS } BETWEEN frame_start AND frame_end [ frame_exclusion ]

   where frame_start and frame_end can be one of
UNBOUNDED PRECEDING
offset PRECEDING
CURRENT ROW
offset FOLLOWING
UNBOUNDED FOLLOWING

   and frame_exclusion can be one of
EXCLUDE CURRENT ROW
EXCLUDE GROUP
EXCLUDE TIES
EXCLUDE NO OTHERS

   If frame_end is omitted it defaults to CURRENT ROW. Restrictions are
   that frame_start cannot be UNBOUNDED FOLLOWING, frame_end cannot be
   UNBOUNDED PRECEDING, and the frame_end choice cannot appear earlier in
   the above list of frame_start and frame_end options than the
   frame_start choice does — for example RANGE BETWEEN CURRENT ROW AND
   offset PRECEDING is not allowed.

   The default framing option is RANGE UNBOUNDED PRECEDING, which is the
   same as RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW; it sets the
   frame to be all rows from the partition start up through the current
   row's last peer (a row that the window's ORDER BY clause considers
   equivalent to the current row; all rows are peers if there is no ORDER
   BY). In general, UNBOUNDED PRECEDING means that the frame starts with
   the first row of the partition, and similarly UNBOUNDED FOLLOWING means
   that the frame ends with the last row of the partition, regardless of
   RANGE, ROWS or GROUPS mode. In ROWS mode, CURRENT ROW means that the
   frame starts or ends with the current row; but in RANGE or GROUPS mode
   it means that the frame starts or ends with the current row's first or
   last peer in the ORDER BY ordering. The offset PRECEDING and offset
   FOLLOWING options vary in meaning depending on the frame mode. In ROWS
   mode, the offset is an integer indicating that the frame starts or ends
   that many rows before or after the current row. In GROUPS mode, the
   offset is an integer indicating that the frame starts or ends that many
   peer groups before or after the current row's peer group, where a peer
   group is a group of rows that are equivalent according to the window's
   ORDER BY clause. In RANGE mode, use of an offset option requires that
   there be exactly one ORDER BY column in the window definition. Then the
   frame contains those rows whose ordering column value is no more than
   offset less than (for PRECEDING) or more than (for FOLLOWING) the
   current row's ordering column value. In these cases the data type of
   the offset expression depends on the data type of the ordering column.
   For numeric ordering columns it is typically of the same type as the
   ordering column, but for datetime ordering columns it is an interval.
   In all these cases, the value of the offset must be non-null and
   non-negative. Also, while the offset does not have to be a simple
   constant, it cannot contain variables, aggregate functions, or window
   functions.

   The frame_exclusion option allows rows around the current row to be
   excluded from the frame, even if they would be included according to
   the frame start and frame end options. EXCLUDE CURRENT ROW excludes the
   current row from the frame. EXCLUDE GROUP excludes the current row and
   its ordering peers from the frame. EXCLUDE TIES excludes any peers of
   the current row from the frame, but not the current row itself. EXCLUDE
   NO OTHERS simply specifies explicitly the default behavior of not
   excluding the current row or its peers.

   Beware that the ROWS mode can produce unpredictable results if the
   ORDER BY ordering does not order the rows uniquely. The RANGE and
   GROUPS modes are designed to ensure that rows that are peers in the
   ORDER BY ordering are treated alike: all rows of a given peer group
   will be in the frame or excluded from it.

   The purpose of a WINDOW clause is to specify the behavior of window
   functions appearing in the query's SELECT list or ORDER BY clause.
   These functions can reference the WINDOW clause entries by name in
   their OVER clauses. A WINDOW clause entry does not have to be
   referenced anywhere, however; if it is not used in the query it is
   simply ignored. It is possible to use window functions without any
   WINDOW clause at all, since a window function call can specify its
   window definition directly in its OVER clause. However, the WINDOW
   clause saves typing when the same window definition is needed for more
   than one window function.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified with WINDOW.

   Window functions are described in detail in Section 3.5, Section 4.2.8,
   and Section 7.2.5.

SELECT List

   The SELECT list (between the key words SELECT and FROM) specifies
   expressions that form the output rows of the SELECT statement. The
   expressions can (and usually do) refer to columns computed in the FROM
   clause.

   Just as in a table, every output column of a SELECT has a name. In a
   simple SELECT this name is just used to label the column for display,
   but when the SELECT is a sub-query of a larger query, the name is seen
   by the larger query as the column name of the virtual table produced by
   the sub-query. To specify the name to use for an output column, write
   AS output_name after the column's expression. (You can omit AS, but
   only if the desired output name does not match any PostgreSQL keyword
   (see Appendix C). For protection against possible future keyword
   additions, it is recommended that you always either write AS or
   double-quote the output name.) If you do not specify a column name, a
   name is chosen automatically by PostgreSQL. If the column's expression
   is a simple column reference then the chosen name is the same as that
   column's name. In more complex cases a function or type name may be
   used, or the system may fall back on a generated name such as ?column?.

   An output column's name can be used to refer to the column's value in
   ORDER BY and GROUP BY clauses, but not in the WHERE or HAVING clauses;
   there you must write out the expression instead.

   Instead of an expression, * can be written in the output list as a
   shorthand for all the columns of the selected rows. Also, you can write
   table_name.* as a shorthand for the columns coming from just that
   table. In these cases it is not possible to specify new names with AS;
   the output column names will be the same as the table columns' names.

   According to the SQL standard, the expressions in the output list
   should be computed before applying DISTINCT, ORDER BY, or LIMIT. This
   is obviously necessary when using DISTINCT, since otherwise it's not
   clear what values are being made distinct. However, in many cases it is
   convenient if output expressions are computed after ORDER BY and LIMIT;
   particularly if the output list contains any volatile or expensive
   functions. With that behavior, the order of function evaluations is
   more intuitive and there will not be evaluations corresponding to rows
   that never appear in the output. PostgreSQL will effectively evaluate
   output expressions after sorting and limiting, so long as those
   expressions are not referenced in DISTINCT, ORDER BY or GROUP BY. (As a
   counterexample, SELECT f(x) FROM tab ORDER BY 1 clearly must evaluate
   f(x) before sorting.) Output expressions that contain set-returning
   functions are effectively evaluated after sorting and before limiting,
   so that LIMIT will act to cut off the output from a set-returning
   function.

Note

   PostgreSQL versions before 9.6 did not provide any guarantees about the
   timing of evaluation of output expressions versus sorting and limiting;
   it depended on the form of the chosen query plan.

DISTINCT Clause

   If SELECT DISTINCT is specified, all duplicate rows are removed from
   the result set (one row is kept from each group of duplicates). SELECT
   ALL specifies the opposite: all rows are kept; that is the default.

   SELECT DISTINCT ON ( expression [, ...] ) keeps only the first row of
   each set of rows where the given expressions evaluate to equal. The
   DISTINCT ON expressions are interpreted using the same rules as for
   ORDER BY (see above). Note that the “first row” of each set is
   unpredictable unless ORDER BY is used to ensure that the desired row
   appears first. For example:
SELECT DISTINCT ON (location) location, time, report
    FROM weather_reports
    ORDER BY location, time DESC;

   retrieves the most recent weather report for each location. But if we
   had not used ORDER BY to force descending order of time values for each
   location, we'd have gotten a report from an unpredictable time for each
   location.

   The DISTINCT ON expression(s) must match the leftmost ORDER BY
   expression(s). The ORDER BY clause will normally contain additional
   expression(s) that determine the desired precedence of rows within each
   DISTINCT ON group.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified with DISTINCT.

UNION Clause

   The UNION clause has this general form:
select_statement UNION [ ALL | DISTINCT ] select_statement

   select_statement is any SELECT statement without an ORDER BY, LIMIT,
   FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause.
   (ORDER BY and LIMIT can be attached to a subexpression if it is
   enclosed in parentheses. Without parentheses, these clauses will be
   taken to apply to the result of the UNION, not to its right-hand input
   expression.)

   The UNION operator computes the set union of the rows returned by the
   involved SELECT statements. A row is in the set union of two result
   sets if it appears in at least one of the result sets. The two SELECT
   statements that represent the direct operands of the UNION must produce
   the same number of columns, and corresponding columns must be of
   compatible data types.

   The result of UNION does not contain any duplicate rows unless the ALL
   option is specified. ALL prevents elimination of duplicates.
   (Therefore, UNION ALL is usually significantly quicker than UNION; use
   ALL when you can.) DISTINCT can be written to explicitly specify the
   default behavior of eliminating duplicate rows.

   Multiple UNION operators in the same SELECT statement are evaluated
   left to right, unless otherwise indicated by parentheses.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified either for a UNION result or for any input of a
   UNION.

INTERSECT Clause

   The INTERSECT clause has this general form:
select_statement INTERSECT [ ALL | DISTINCT ] select_statement

   select_statement is any SELECT statement without an ORDER BY, LIMIT,
   FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause.

   The INTERSECT operator computes the set intersection of the rows
   returned by the involved SELECT statements. A row is in the
   intersection of two result sets if it appears in both result sets.

   The result of INTERSECT does not contain any duplicate rows unless the
   ALL option is specified. With ALL, a row that has m duplicates in the
   left table and n duplicates in the right table will appear min(m,n)
   times in the result set. DISTINCT can be written to explicitly specify
   the default behavior of eliminating duplicate rows.

   Multiple INTERSECT operators in the same SELECT statement are evaluated
   left to right, unless parentheses dictate otherwise. INTERSECT binds
   more tightly than UNION. That is, A UNION B INTERSECT C will be read as
   A UNION (B INTERSECT C).

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified either for an INTERSECT result or for any input of
   an INTERSECT.

EXCEPT Clause

   The EXCEPT clause has this general form:
select_statement EXCEPT [ ALL | DISTINCT ] select_statement

   select_statement is any SELECT statement without an ORDER BY, LIMIT,
   FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE, or FOR KEY SHARE clause.

   The EXCEPT operator computes the set of rows that are in the result of
   the left SELECT statement but not in the result of the right one.

   The result of EXCEPT does not contain any duplicate rows unless the ALL
   option is specified. With ALL, a row that has m duplicates in the left
   table and n duplicates in the right table will appear max(m-n,0) times
   in the result set. DISTINCT can be written to explicitly specify the
   default behavior of eliminating duplicate rows.

   Multiple EXCEPT operators in the same SELECT statement are evaluated
   left to right, unless parentheses dictate otherwise. EXCEPT binds at
   the same level as UNION.

   Currently, FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE and FOR KEY SHARE
   cannot be specified either for an EXCEPT result or for any input of an
   EXCEPT.

ORDER BY Clause

   The optional ORDER BY clause has this general form:
ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [
, ...]

   The ORDER BY clause causes the result rows to be sorted according to
   the specified expression(s). If two rows are equal according to the
   leftmost expression, they are compared according to the next expression
   and so on. If they are equal according to all specified expressions,
   they are returned in an implementation-dependent order.

   Each expression can be the name or ordinal number of an output column
   (SELECT list item), or it can be an arbitrary expression formed from
   input-column values.

   The ordinal number refers to the ordinal (left-to-right) position of
   the output column. This feature makes it possible to define an ordering
   on the basis of a column that does not have a unique name. This is
   never absolutely necessary because it is always possible to assign a
   name to an output column using the AS clause.

   It is also possible to use arbitrary expressions in the ORDER BY
   clause, including columns that do not appear in the SELECT output list.
   Thus the following statement is valid:
SELECT name FROM distributors ORDER BY code;

   A limitation of this feature is that an ORDER BY clause applying to the
   result of a UNION, INTERSECT, or EXCEPT clause can only specify an
   output column name or number, not an expression.

   If an ORDER BY expression is a simple name that matches both an output
   column name and an input column name, ORDER BY will interpret it as the
   output column name. This is the opposite of the choice that GROUP BY
   will make in the same situation. This inconsistency is made to be
   compatible with the SQL standard.

   Optionally one can add the key word ASC (ascending) or DESC
   (descending) after any expression in the ORDER BY clause. If not
   specified, ASC is assumed by default. Alternatively, a specific
   ordering operator name can be specified in the USING clause. An
   ordering operator must be a less-than or greater-than member of some
   B-tree operator family. ASC is usually equivalent to USING < and DESC
   is usually equivalent to USING >. (But the creator of a user-defined
   data type can define exactly what the default sort ordering is, and it
   might correspond to operators with other names.)

   If NULLS LAST is specified, null values sort after all non-null values;
   if NULLS FIRST is specified, null values sort before all non-null
   values. If neither is specified, the default behavior is NULLS LAST
   when ASC is specified or implied, and NULLS FIRST when DESC is
   specified (thus, the default is to act as though nulls are larger than
   non-nulls). When USING is specified, the default nulls ordering depends
   on whether the operator is a less-than or greater-than operator.

   Note that ordering options apply only to the expression they follow;
   for example ORDER BY x, y DESC does not mean the same thing as ORDER BY
   x DESC, y DESC.

   Character-string data is sorted according to the collation that applies
   to the column being sorted. That can be overridden at need by including
   a COLLATE clause in the expression, for example ORDER BY mycolumn
   COLLATE "en_US". For more information see Section 4.2.10 and
   Section 23.2.

LIMIT Clause

   The LIMIT clause consists of two independent sub-clauses:
LIMIT { count | ALL }
OFFSET start

   The parameter count specifies the maximum number of rows to return,
   while start specifies the number of rows to skip before starting to
   return rows. When both are specified, start rows are skipped before
   starting to count the count rows to be returned.

   If the count expression evaluates to NULL, it is treated as LIMIT ALL,
   i.e., no limit. If start evaluates to NULL, it is treated the same as
   OFFSET 0.

   SQL:2008 introduced a different syntax to achieve the same result,
   which PostgreSQL also supports. It is:
OFFSET start { ROW | ROWS }
FETCH { FIRST | NEXT } [ count ] { ROW | ROWS } { ONLY | WITH TIES }

   In this syntax, the start or count value is required by the standard to
   be a literal constant, a parameter, or a variable name; as a PostgreSQL
   extension, other expressions are allowed, but will generally need to be
   enclosed in parentheses to avoid ambiguity. If count is omitted in a
   FETCH clause, it defaults to 1. The WITH TIES option is used to return
   any additional rows that tie for the last place in the result set
   according to the ORDER BY clause; ORDER BY is mandatory in this case,
   and SKIP LOCKED is not allowed. ROW and ROWS as well as FIRST and NEXT
   are noise words that don't influence the effects of these clauses.
   According to the standard, the OFFSET clause must come before the FETCH
   clause if both are present; but PostgreSQL is laxer and allows either
   order.

   When using LIMIT, it is a good idea to use an ORDER BY clause that
   constrains the result rows into a unique order. Otherwise you will get
   an unpredictable subset of the query's rows — you might be asking for
   the tenth through twentieth rows, but tenth through twentieth in what
   ordering? You don't know what ordering unless you specify ORDER BY.

   The query planner takes LIMIT into account when generating a query
   plan, so you are very likely to get different plans (yielding different
   row orders) depending on what you use for LIMIT and OFFSET. Thus, using
   different LIMIT/OFFSET values to select different subsets of a query
   result will give inconsistent results unless you enforce a predictable
   result ordering with ORDER BY. This is not a bug; it is an inherent
   consequence of the fact that SQL does not promise to deliver the
   results of a query in any particular order unless ORDER BY is used to
   constrain the order.

   It is even possible for repeated executions of the same LIMIT query to
   return different subsets of the rows of a table, if there is not an
   ORDER BY to enforce selection of a deterministic subset. Again, this is
   not a bug; determinism of the results is simply not guaranteed in such
   a case.

The Locking Clause

   FOR UPDATE, FOR NO KEY UPDATE, FOR SHARE and FOR KEY SHARE are locking
   clauses; they affect how SELECT locks rows as they are obtained from
   the table.

   The locking clause has the general form
FOR lock_strength [ OF from_reference [, ...] ] [ NOWAIT | SKIP LOCKED ]

   where lock_strength can be one of
UPDATE
NO KEY UPDATE
SHARE
KEY SHARE

   from_reference must be a table alias or non-hidden table_name
   referenced in the FROM clause. For more information on each row-level
   lock mode, refer to Section 13.3.2.

   To prevent the operation from waiting for other transactions to commit,
   use either the NOWAIT or SKIP LOCKED option. With NOWAIT, the statement
   reports an error, rather than waiting, if a selected row cannot be
   locked immediately. With SKIP LOCKED, any selected rows that cannot be
   immediately locked are skipped. Skipping locked rows provides an
   inconsistent view of the data, so this is not suitable for general
   purpose work, but can be used to avoid lock contention with multiple
   consumers accessing a queue-like table. Note that NOWAIT and SKIP
   LOCKED apply only to the row-level lock(s) — the required ROW SHARE
   table-level lock is still taken in the ordinary way (see Chapter 13).
   You can use LOCK with the NOWAIT option first, if you need to acquire
   the table-level lock without waiting.

   If specific tables are named in a locking clause, then only rows coming
   from those tables are locked; any other tables used in the SELECT are
   simply read as usual. A locking clause without a table list affects all
   tables used in the statement. If a locking clause is applied to a view
   or sub-query, it affects all tables used in the view or sub-query.
   However, these clauses do not apply to WITH queries referenced by the
   primary query. If you want row locking to occur within a WITH query,
   specify a locking clause within the WITH query.

   Multiple locking clauses can be written if it is necessary to specify
   different locking behavior for different tables. If the same table is
   mentioned (or implicitly affected) by more than one locking clause,
   then it is processed as if it was only specified by the strongest one.
   Similarly, a table is processed as NOWAIT if that is specified in any
   of the clauses affecting it. Otherwise, it is processed as SKIP LOCKED
   if that is specified in any of the clauses affecting it.

   The locking clauses cannot be used in contexts where returned rows
   cannot be clearly identified with individual table rows; for example
   they cannot be used with aggregation.

   When a locking clause appears at the top level of a SELECT query, the
   rows that are locked are exactly those that are returned by the query;
   in the case of a join query, the rows locked are those that contribute
   to returned join rows. In addition, rows that satisfied the query
   conditions as of the query snapshot will be locked, although they will
   not be returned if they were updated after the snapshot and no longer
   satisfy the query conditions. If a LIMIT is used, locking stops once
   enough rows have been returned to satisfy the limit (but note that rows
   skipped over by OFFSET will get locked). Similarly, if a locking clause
   is used in a cursor's query, only rows actually fetched or stepped past
   by the cursor will be locked.

   When a locking clause appears in a sub-SELECT, the rows locked are
   those returned to the outer query by the sub-query. This might involve
   fewer rows than inspection of the sub-query alone would suggest, since
   conditions from the outer query might be used to optimize execution of
   the sub-query. For example,
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss WHERE col1 = 5;

   will lock only rows having col1 = 5, even though that condition is not
   textually within the sub-query.

   Previous releases failed to preserve a lock which is upgraded by a
   later savepoint. For example, this code:
BEGIN;
SELECT * FROM mytable WHERE key = 1 FOR UPDATE;
SAVEPOINT s;
UPDATE mytable SET ... WHERE key = 1;
ROLLBACK TO s;

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

Caution

   It is possible for a SELECT command running at the READ COMMITTED
   transaction isolation level and using ORDER BY and a locking clause to
   return rows out of order. This is because ORDER BY is applied first.
   The command sorts the result, but might then block trying to obtain a
   lock on one or more of the rows. Once the SELECT unblocks, some of the
   ordering column values might have been modified, leading to those rows
   appearing to be out of order (though they are in order in terms of the
   original column values). This can be worked around at need by placing
   the FOR UPDATE/SHARE clause in a sub-query, for example
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss ORDER BY column1;

   Note that this will result in locking all rows of mytable, whereas FOR
   UPDATE at the top level would lock only the actually returned rows.
   This can make for a significant performance difference, particularly if
   the ORDER BY is combined with LIMIT or other restrictions. So this
   technique is recommended only if concurrent updates of the ordering
   columns are expected and a strictly sorted result is required.

   At the REPEATABLE READ or SERIALIZABLE transaction isolation level this
   would cause a serialization failure (with an SQLSTATE of '40001'), so
   there is no possibility of receiving rows out of order under these
   isolation levels.

TABLE Command

   The command
TABLE name

   is equivalent to
SELECT * FROM name

   It can be used as a top-level command or as a space-saving syntax
   variant in parts of complex queries. Only the WITH, UNION, INTERSECT,
   EXCEPT, ORDER BY, LIMIT, OFFSET, FETCH and FOR locking clauses can be
   used with TABLE; the WHERE clause and any form of aggregation cannot be
   used.

Examples

   To join the table films with the table distributors:
SELECT f.title, f.did, d.name, f.date_prod, f.kind
    FROM distributors d JOIN films f USING (did);

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

   To sum the column len of all films and group the results by kind:
SELECT kind, sum(len) AS total FROM films GROUP BY kind;

   kind   | total
----------+-------
 Action   | 07:34
 Comedy   | 02:58
 Drama    | 14:28
 Musical  | 06:42
 Romantic | 04:38

   To sum the column len of all films, group the results by kind and show
   those group totals that are less than 5 hours:
SELECT kind, sum(len) AS total
    FROM films
    GROUP BY kind
    HAVING sum(len) < interval '5 hours';

   kind   | total
----------+-------
 Comedy   | 02:58
 Romantic | 04:38

   The following two examples are identical ways of sorting the individual
   results according to the contents of the second column (name):
SELECT * FROM distributors ORDER BY name;
SELECT * FROM distributors ORDER BY 2;

 did |       name
-----+------------------
 109 | 20th Century Fox
 110 | Bavaria Atelier
 101 | British Lion
 107 | Columbia
 102 | Jean Luc Godard
 113 | Luso films
 104 | Mosfilm
 103 | Paramount
 106 | Toho
 105 | United Artists
 111 | Walt Disney
 112 | Warner Bros.
 108 | Westward

   The next example shows how to obtain the union of the tables
   distributors and actors, restricting the results to those that begin
   with the letter W in each table. Only distinct rows are wanted, so the
   key word ALL is omitted.
distributors:               actors:
 did |     name              id |     name
-----+--------------        ----+----------------
 108 | Westward               1 | Woody Allen
 111 | Walt Disney            2 | Warren Beatty
 112 | Warner Bros.           3 | Walter Matthau
 ...                         ...

SELECT distributors.name
    FROM distributors
    WHERE distributors.name LIKE 'W%'
UNION
SELECT actors.name
    FROM actors
    WHERE actors.name LIKE 'W%';

      name
----------------
 Walt Disney
 Walter Matthau
 Warner Bros.
 Warren Beatty
 Westward
 Woody Allen

   This example shows how to use a function in the FROM clause, both with
   and without a column definition list:
CREATE FUNCTION distributors(int) RETURNS SETOF distributors AS $$
    SELECT * FROM distributors WHERE did = $1;
$$ LANGUAGE SQL;

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

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

SELECT * FROM distributors_2(111) AS (f1 int, f2 text);
 f1  |     f2
-----+-------------
 111 | Walt Disney

   Here is an example of a function with an ordinality column added:
SELECT * FROM unnest(ARRAY['a','b','c','d','e','f']) WITH ORDINALITY;
 unnest | ordinality
--------+----------
 a      |        1
 b      |        2
 c      |        3
 d      |        4
 e      |        5
 f      |        6
(6 rows)

   This example shows how to use a simple WITH clause:
WITH t AS (
    SELECT random() as x FROM generate_series(1, 3)
  )
SELECT * FROM t
UNION ALL
SELECT * FROM t;
         x
--------------------
  0.534150459803641
  0.520092216785997
 0.0735620250925422
  0.534150459803641
  0.520092216785997
 0.0735620250925422

   Notice that the WITH query was evaluated only once, so that we got two
   sets of the same three random values.

   This example uses WITH RECURSIVE to find all subordinates (direct or
   indirect) of the employee Mary, and their level of indirectness, from a
   table that shows only direct subordinates:
WITH RECURSIVE employee_recursive(distance, employee_name, manager_name) AS (
    SELECT 1, employee_name, manager_name
    FROM employee
    WHERE manager_name = 'Mary'
  UNION ALL
    SELECT er.distance + 1, e.employee_name, e.manager_name
    FROM employee_recursive er, employee e
    WHERE er.employee_name = e.manager_name
  )
SELECT distance, employee_name FROM employee_recursive;

   Notice the typical form of recursive queries: an initial condition,
   followed by UNION, followed by the recursive part of the query. Be sure
   that the recursive part of the query will eventually return no tuples,
   or else the query will loop indefinitely. (See Section 7.8 for more
   examples.)

   This example uses LATERAL to apply a set-returning function
   get_product_names() for each row of the manufacturers table:
SELECT m.name AS mname, pname
FROM manufacturers m, LATERAL get_product_names(m.id) pname;

   Manufacturers not currently having any products would not appear in the
   result, since it is an inner join. If we wished to include the names of
   such manufacturers in the result, we could do:
SELECT m.name AS mname, pname
FROM manufacturers m LEFT JOIN LATERAL get_product_names(m.id) pname ON true;

Compatibility

   Of course, the SELECT statement is compatible with the SQL standard.
   But there are some extensions and some missing features.

Omitted FROM Clauses

   PostgreSQL allows one to omit the FROM clause. It has a straightforward
   use to compute the results of simple expressions:
SELECT 2+2;

 ?column?
----------
        4

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

Empty SELECT Lists

   The list of output expressions after SELECT can be empty, producing a
   zero-column result table. This is not valid syntax according to the SQL
   standard. PostgreSQL allows it to be consistent with allowing
   zero-column tables. However, an empty list is not allowed when DISTINCT
   is used.

Omitting the AS Key Word

   In the SQL standard, the optional key word AS can be omitted before an
   output column name whenever the new column name is a valid column name
   (that is, not the same as any reserved keyword). PostgreSQL is slightly
   more restrictive: AS is required if the new column name matches any
   keyword at all, reserved or not. Recommended practice is to use AS or
   double-quote output column names, to prevent any possible conflict
   against future keyword additions.

   In FROM items, both the standard and PostgreSQL allow AS to be omitted
   before an alias that is an unreserved keyword. But this is impractical
   for output column names, because of syntactic ambiguities.

Omitting Sub-SELECT Aliases in FROM

   According to the SQL standard, a sub-SELECT in the FROM list must have
   an alias. In PostgreSQL, this alias may be omitted.

ONLY and Inheritance

   The SQL standard requires parentheses around the table name when
   writing ONLY, for example SELECT * FROM ONLY (tab1), ONLY (tab2) WHERE
   .... PostgreSQL considers these parentheses to be optional.

   PostgreSQL allows a trailing * to be written to explicitly specify the
   non-ONLY behavior of including child tables. The standard does not
   allow this.

   (These points apply equally to all SQL commands supporting the ONLY
   option.)

TABLESAMPLE Clause Restrictions

   The TABLESAMPLE clause is currently accepted only on regular tables and
   materialized views. According to the SQL standard it should be possible
   to apply it to any FROM item.

Function Calls in FROM

   PostgreSQL allows a function call to be written directly as a member of
   the FROM list. In the SQL standard it would be necessary to wrap such a
   function call in a sub-SELECT; that is, the syntax FROM func(...) alias
   is approximately equivalent to FROM LATERAL (SELECT func(...)) alias.
   Note that LATERAL is considered to be implicit; this is because the
   standard requires LATERAL semantics for an UNNEST() item in FROM.
   PostgreSQL treats UNNEST() the same as other set-returning functions.

Namespace Available to GROUP BY and ORDER BY

   In the SQL-92 standard, an ORDER BY clause can only use output column
   names or numbers, while a GROUP BY clause can only use expressions
   based on input column names. PostgreSQL extends each of these clauses
   to allow the other choice as well (but it uses the standard's
   interpretation if there is ambiguity). PostgreSQL also allows both
   clauses to specify arbitrary expressions. Note that names appearing in
   an expression will always be taken as input-column names, not as
   output-column names.

   SQL:1999 and later use a slightly different definition which is not
   entirely upward compatible with SQL-92. In most cases, however,
   PostgreSQL will interpret an ORDER BY or GROUP BY expression the same
   way SQL:1999 does.

Functional Dependencies

   PostgreSQL recognizes functional dependency (allowing columns to be
   omitted from GROUP BY) only when a table's primary key is included in
   the GROUP BY list. The SQL standard specifies additional conditions
   that should be recognized.

LIMIT and OFFSET

   The clauses LIMIT and OFFSET are PostgreSQL-specific syntax, also used
   by MySQL. The SQL:2008 standard has introduced the clauses OFFSET ...
   FETCH {FIRST|NEXT} ... for the same functionality, as shown above in
   LIMIT Clause. This syntax is also used by IBM DB2. (Applications
   written for Oracle frequently use a workaround involving the
   automatically generated rownum column, which is not available in
   PostgreSQL, to implement the effects of these clauses.)

FOR NO KEY UPDATE, FOR UPDATE, FOR SHARE, FOR KEY SHARE

   Although FOR UPDATE appears in the SQL standard, the standard allows it
   only as an option of DECLARE CURSOR. PostgreSQL allows it in any SELECT
   query as well as in sub-SELECTs, but this is an extension. The FOR NO
   KEY UPDATE, FOR SHARE and FOR KEY SHARE variants, as well as the NOWAIT
   and SKIP LOCKED options, do not appear in the standard.

Data-Modifying Statements in WITH

   PostgreSQL allows INSERT, UPDATE, DELETE, and MERGE to be used as WITH
   queries. This is not found in the SQL standard.

Nonstandard Clauses

   DISTINCT ON ( ... ) is an extension of the SQL standard.

   ROWS FROM( ... ) is an extension of the SQL standard.

   The MATERIALIZED and NOT MATERIALIZED options of WITH are extensions of
   the SQL standard.