SELECT

Synopsis

SELECT [ALL | DISTINCT [ON (expression [, ...])]]
  * | expression [[AS] output_name] [, ...]
  [FROM from_item [, ...]]
  [WHERE condition]
  [GROUP BY grouping_element [, ...]]
  [HAVING condition [, ...]]
  [{UNION | INTERSECT | EXCEPT} [ALL] select]
  [ORDER BY expression [ASC | DESC | USING operator] [, ...]]
  [LIMIT {count | ALL}]

Description

Parameters

1. WITH list
   The WITH list exists before the SELECT statement or serves as a subquery of the SELECT clause. It is usually located before the SELECT statement to define subqueries and declare a name and the names of returned columns for each subquery. Each WITH clause is defined as a common table expression (CTE). The syntax is as follows:

   with_query_name [ ( column_name [, ...] ) ] AS ( select )

   The with_query_name parameter specifies the name of the current CTE, which can be any valid identifier. The column_name list specifies the names of the columns returned by a subquery. Similar to the semantics of AS in the SELECT clause, a subquery can be a regular SELECT query.

   Separate CTEs with commas (,). Subsequent CTEs can reference the previously defined CTEs. However, CTEs cannot be called recursively. In subsequent queries, with_query_name can be used as a view. If the column_name list is not specified, the column_name list of the view contains the names of the columns returned by the corresponding subquery. If the column_name list is specified, you must use the specified column_name list. In addition, make sure that the number of columns in the column_name list is the same as the number of columns returned by the SELECT statement of the subquery.

2. SELECT list

   The SELECT list (between the keywords SELECT and FROM) specifies expressions that form the output rows of the SELECT statement. The expressions can (and usually do) indicate 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 only used to label the column for display. However, when the SELECT is a subquery of a larger query, the name is seen by the larger query as the column name of the virtual table produced by the subquery. 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. For protection against possible future keyword additions, we recommend 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, 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 indicate the column's value in ORDER BY and GROUP BY clauses, but not in the WHERE or HAVING clauses, where you must write out the expression instead.

   Instead of an expression, an asterisk (*) 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 only that table. In these cases, you cannot specify new names with AS. The output column names will be the same as the table columns' names.

3. 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. However, usually qualification conditions are added (through 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.

   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.

   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 statement. Note that the sub-SELECT must be surrounded by parentheses, and an alias must be provided for it. A VALUES statement can also be used here.

   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 statement.

   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, and so on. 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.

   join_type
   [ 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 join_condition, or USING (join_column [, ...]) . See below for the meaning. For CROSS JOIN, none of these clauses can appear. A JOIN clause combines two FROM items, which for convenience we will refer to as "tables", though in reality they can be any type of FROM item. Use parentheses if necessary to determine the order of nesting. In the absence of parentheses, JOINs nest left-to-right. In any case, JOIN binds more tightly than the commas separating FROM-list items.

   CROSS JOIN and INNER JOIN produce a simple Cartesian product, the same result as you get from listing the two tables at the top level of FROM, but restricted by the join condition (if any). CROSS JOIN is equivalent to INNER JOIN ON (TRUE), that is, no rows are removed by qualification. These join types are only for a notational convenience, since they do nothing you cannot do with plain FROM and WHERE.

   LEFT OUTER JOIN returns all rows in the qualified Cartesian product (that is, 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 only 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).

   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.

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

   NATURAL is shorthand for a USING list that mentions all columns in the two tables that have matching names.

4. WHERE clause
   The optional WHERE clause has this general form:

   WHERE condition

   In this clause, 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.

5. GROUP BY clause
   The optional GROUP BY clause has this 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, 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, 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.

   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. 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.

6. 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 make sure that the desired row appears first. Example:

   SELECT DISTINCT ON (location) location, time, report
       FROM weather_reports
       ORDER BY location, time DESC;

   This retrieves the most recent weather report for each location. However, if you do not use ORDER BY to force descending order of time values for each location, you will get a report from an unpredictable time for each location.

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

7. COUNT DISTINCT clause

   COUNT DISTINCT counts the number of unique values in a column. A value that appears multiple times in the column is counted only once. Null values are not counted. This clause is similar to the COUNT function.

   The sample syntax for accurate counting is as follows:

   SELECT c1, COUNT(DISTINCT c2) FROM table GROUP BY c1

   Accurate COUNT DISTINCT consumes many resources. Interactive Analytics also supports non-accurate COUNT DISTINCT. The sample syntax is as follows:

   SELECT c1, approx_count_distinct(c2) FROM table GROUP BY c1

8. UNION clause

   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 whenever possible. 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.

9. 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 or LIMIT 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).

10. 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 or LIMIT 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.

11. 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 expressions. 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. Therefore, 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, you can add the keyword 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 >. However, 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".

12. LIMIT clause
    The LIMIT clause consists of two independent sub-clauses:

    LIMIT { count | ALL }
    OFFSET start

    In the LIMIT clause, count specifies the maximum number of rows to return, whereas start specifies the number of rows to skip before rows are returned. 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, which means no limit. If start evaluates to NULL, it is treated the same as OFFSET 0.

    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 do not 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.

Examples

• This example shows how 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

• This example shows how to sum the column length of all films and group the results by kind:

  SELECT kind, sum(length) AS total FROM films GROUP BY kind;

• This example shows how to sum the column length of all films, group the results by kind, and show those group totals that are less than 5 hours:

  SELECT kind, sum(length) AS total FROM films GROUP BY kind 
  HAVING sum(length) < interval '5 hours';

• This example shows how to sort the returned results by name:

  SELECT * FROM distributors ORDER BY name;