SELECT

Retrieves 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 <grouping_element> [, ...]]
  [HAVING <condition> [, ...]]
  [WINDOW <window_name> AS (<window_definition>) [, ...] ]
  [{UNION | INTERSECT | EXCEPT} [ALL | DISTINCT] <select>]
  [ORDER BY <expression> [ASC | DESC | USING <operator>] [NULLS {FIRST | LAST}] [, ...]]
  [LIMIT {<count> | ALL}]
  [OFFSET <start> [ ROW | ROWS ] ]
  [FETCH { FIRST | NEXT } [ <count> ] { ROW | ROWS } ONLY]
  [FOR {UPDATE | NO KEY UPDATE | SHARE | KEY SHARE} [OF <table_name> [, ...]] [NOWAIT] [...]]

TABLE { [ ONLY ] <table_name> [ * ] | <with_query_name> }

where with_query: is:

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

where from_item can be one of:

[ONLY] <table_name> [ * ] [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]
( <select> ) [ AS ] <alias> [( <column_alias> [, ...] ) ]
with\_query\_name [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]
<function_name> ( [ <argument> [, ...] ] )
            [ WITH ORDINALITY ] [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]
<function_name> ( [ <argument> [, ...] ] ) [ AS ] <alias> ( <column_definition> [, ...] )
<function_name> ( [ <argument> [, ...] ] ) AS ( <column_definition> [, ...] )
ROWS FROM( function_name ( [ argument [, ...] ] ) [ AS ( column_definition [, ...] ) ] [, ...] )
            [ WITH ORDINALITY ] [ [ AS ] <alias> [ ( <column_alias> [, ...] ) ] ]
<from_item> [ NATURAL ] <join_type> <from_item>
          [ ON <join_condition> | USING ( <join_column> [, ...] ) ]

where grouping_element can be one of:

  ()
  <expression>
  ROLLUP (<expression> [,...])
  CUBE (<expression> [,...])
  GROUPING SETS ((<grouping_element> [, ...]))

where window_definition is:

  [<existing_window_name>]
  [PARTITION BY <expression> [, ...]]
  [ORDER BY <expression> [ASC | DESC | USING <operator>] 
    [NULLS {FIRST | LAST}] [, ...]]
  [{ RANGE | ROWS} <frame_start> 
     | {RANGE | ROWS} BETWEEN <frame_start> AND <frame_end>

where frame_start and frame_end can be one of:

  UNBOUNDED PRECEDING
  <value> PRECEDING
  CURRENT ROW
  <value> FOLLOWING
  UNBOUNDED FOLLOWING

²When a locking clause is specified (the FOR clause), the Global Deadlock Detector affects how table rows are locked. See item 12 in Description and see "The Locking Clause" later in this section.

Description

SELECT retrieves rows from zero or more tables. The general processing of SELECT is as follows:

All queries in the WITH clause are computed. These effectively serve as temporary tables that can be referenced in the FROM list.
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.
If the WHERE clause is specified, all rows that do not satisfy the condition are eliminated from the output.
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.
The actual output rows are computed using the SELECT output expressions for each selected row or row group.
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.
If a window expression is specified (and optional WINDOW clause), the output is organized according to the positional (row) or value-based (range) window frame.
The actual output rows are computed using the SELECT output expressions for each selected row.
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.
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.
If the LIMIT (or FETCH FIRST) or OFFSET clause is specified, the SELECT statement only returns a subset of the result rows.
If FOR UPDATE, FOR NO KEY UPDATE, FOR SHARE, or FOR KEY SHARE is specified, the SELECT statement locks the entire table against concurrent updates.

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

The WITH Clause

The optional 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, INSERT, UPDATE, or DELETE statement. When writing a data-modifying statement (INSERT, UPDATE, or DELETE) in WITH, it is usual to include a RETURNING clause. It is the output of RETURNING, not the underlying table that the statement modifies, that forms the temporary table that is read by the primary query. If RETURNING is omitted, the statement is still run, but it produces no output so it cannot be referenced as a table by the primary query.

For a SELECT command that includes a WITH clause, the clause can contain at most a single clause that modifies table data (INSERT, UPDATE or DELETE command).

A with_query_name without schema qualification must be specified for each query in the WITH clause. Optionally, a list of column names can be specified; if the list of column names is omitted, the names are inferred from the subquery. The primary query and the WITH queries are all (notionally) run at the same time.

If RECURSIVE is specified, it allows a SELECT subquery to reference itself by name. Such a subquery has the general form

<non_recursive_term> UNION [ALL | DISTINCT] <recursive_term>

where the recursive self-reference appears 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.

If the RECURSIVE keyword is specified, the WITH queries need not be ordered: a query can reference another query that is later in the list. However, circular references, or mutual recursion, are not supported.

Without the RECURSIVE keyword, WITH queries can only reference sibling WITH queries that are earlier in the WITH list.

WITH RECURSIVE limitations. These items are not supported:

A recursive WITH clause that contains the following in the recursive_term.
- Subqueries with a self-reference
- DISTINCT clause
- GROUP BY clause
- A window function
A recursive WITH clause where the with_query_name is a part of a set operation.

Following is an example of the set operation limitation. This query returns an error because the set operation UNION contains a reference to the table foo.

WITH RECURSIVE foo(i) AS (
    SELECT 1
  UNION ALL
    SELECT i+1 FROM (SELECT * FROM foo UNION SELECT 0) bar
)
SELECT * FROM foo LIMIT 5;

This recursive CTE is allowed because the set operation UNION does not have a reference to the CTE foo.

WITH RECURSIVE foo(i) AS (
    SELECT 1
  UNION ALL
    SELECT i+1 FROM (SELECT * FROM bar UNION SELECT 0) bar, foo
    WHERE foo.i = bar.a
)
SELECT * FROM foo LIMIT 5;

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

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

See WITH Queries (Common Table Expressions) in the Greenplum Database Administrator Guide for additional information.

The 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.

An expression in the SELECT list can be a constant value, a column reference, an operator invocation, a function call, an aggregate expression, a window expression, a scalar subquery, and so on. A number of constructs can be classified as an expression but do not follow any general syntax rules. These generally have the semantics of a function or operator. For information about SQL value expressions and function calls, see "Querying Data" in the Greenplum Database Administrator Guide.

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 SQL keyword. For protection against possible future keyword additions, you can always either write AS or double-quote the output name.) If you do not specify a column name, Greenplum Database chooses a name is automatically. 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? or columnN.

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.

The 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.

The 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, only that table is scanned. If ONLY is not specified, the table and all its descendant tables (if any) are scanned.

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.

select

A sub- SELECT can appear in the FROM clause. This acts as though its output were created as a temporary table for the duration of this single SELECT command. Note that the sub- SELECT must be surrounded by parentheses, and an alias must be provided for it. A VALUES command can also be used here. See "Non-standard Clauses" in the Compatibility section for limitations of using correlated sub-selects in Greenplum Database.

with_query_name

A with_query is referenced in the FROM clause by specifying its with_query_name, just as though the name were a table name. The with_query_name cannot contain a schema qualifier. An alias can be provided in the same way as for a table.

The with_query hides a table of the same name for the purposes of the primary query. If necessary, you can refer to a table of the same name by qualifying the table name with the schema.

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 its output were created as a temporary table for the duration of this single SELECT command. An alias may also be used. 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. 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.

join_type

One of:

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

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

A JOIN clause combines two FROM items, which for convenience we will refer to as "tables", though in reality they can be any type of FROM item. Use parentheses if necessary to determine the order of nesting. In the absence of parentheses, JOINs nest left-to-right. In any case JOIN binds more tightly than the commas separating FROM-list items.

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

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

NATURAL

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

The 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.

The GROUP BY Clause

The optional GROUP BY clause has the general form:

GROUP BY <grouping_element >[, ...]

where grouping_element can be one of:

()
<expression>
ROLLUP (<expression> [,...])
CUBE (<expression> [,...])
GROUPING SETS ((<grouping_element> [, ...]))

GROUP BY will condense into a single row all selected rows that share the same values for the grouped expressions. expression 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.

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. See Aggregate Expressions.

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 Expression Evaluation Rules.

Greenplum Database has the following additional OLAP grouping extensions (often referred to as supergroups):

ROLLUP

A ROLLUP grouping is an extension to the GROUP BY clause that creates aggregate subtotals that roll up from the most detailed level to a grand total, following a list of grouping columns (or expressions). ROLLUP takes an ordered list of grouping columns, calculates the standard aggregate values specified in the GROUP BY clause, then creates progressively higher-level subtotals, moving from right to left through the list. Finally, it creates a grand total. A ROLLUP grouping can be thought of as a series of grouping sets. For example:

GROUP BY ROLLUP (a,b,c)

is equivalent to:

GROUP BY GROUPING SETS( (a,b,c), (a,b), (a), () )

Notice that the n elements of a ROLLUP translate to n+1 grouping sets. Also, the order in which the grouping expressions are specified is significant in a ROLLUP.

CUBE

A CUBE grouping is an extension to the GROUP BY clause that creates subtotals for all of the possible combinations of the given list of grouping columns (or expressions). In terms of multidimensional analysis, CUBE generates all the subtotals that could be calculated for a data cube with the specified dimensions. For example:

GROUP BY CUBE (a,b,c)

is equivalent to:

GROUP BY GROUPING SETS( (a,b,c), (a,b), (a,c), (b,c), (a), 
(b), (c), () )

Notice that n elements of a CUBE translate to 2n grouping sets. Consider using CUBE in any situation requiring cross-tabular reports. CUBE is typically most suitable in queries that use columns from multiple dimensions rather than columns representing different levels of a single dimension. For instance, a commonly requested cross-tabulation might need subtotals for all the combinations of month, state, and product.

Note
Greenplum Database supports specifying a maximum of 12 CUBE grouping columns.

GROUPING SETS: You can selectively specify the set of groups that you want to create using a GROUPING SETS expression within a GROUP BY clause. This allows precise specification across multiple dimensions without computing a whole ROLLUP or CUBE. For example:

GROUP BY GROUPING SETS( (a,c), (a,b) )

If using the grouping extension clauses ROLLUP, CUBE, or GROUPING SETS, two challenges arise. First, how do you determine which result rows are subtotals, and then the exact level of aggregation for a given subtotal. Or, how do you differentiate between result rows that contain both stored NULL values and "NULL" values created by the ROLLUP or CUBE. Secondly, when duplicate grouping sets are specified in the GROUP BY clause, how do you determine which result rows are duplicates? There are two additional grouping functions you can use in the SELECT list to help with this:

grouping(column [, ...]) — The grouping function can be applied to one or more grouping attributes to distinguish super-aggregated rows from regular grouped rows. This can be helpful in distinguishing a "NULL" representing the set of all values in a super-aggregated row from a NULL value in a regular row. Each argument in this function produces a bit — either 1 or 0, where 1 means the result row is super-aggregated, and 0 means the result row is from a regular grouping. The grouping function returns an integer by treating these bits as a binary number and then converting it to a base-10 integer.
group_id() — For grouping extension queries that contain duplicate grouping sets, the group_id function is used to identify duplicate rows in the output. All unique grouping set output rows will have a group_id value of 0. For each duplicate grouping set detected, the group_id function assigns a group_id number greater than 0. All output rows in a particular duplicate grouping set are identified by the same group_id number.

The WINDOW Clause

The optional WINDOW clause specifies 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.

For example:

SELECT vendor, rank() OVER (mywindow) FROM sale
GROUP BY vendor
WINDOW mywindow AS (ORDER BY sum(prc*qty));

A WINDOW clause has this 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>]

existing_window_name

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. 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.

PARTITION BY

The PARTITION BY clause organizes the result set into logical groups based on the unique values of the specified expression. The elements of the PARTITION BY clause 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. When used with window functions, the functions are applied to each partition independently. For example, if you follow PARTITION BY with a column name, the result set is partitioned by the distinct values of that column. If omitted, the entire result set is considered one partition.

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

ORDER BY

The elements of the ORDER BY clause define how to sort the rows in each partition of the result set. If omitted, rows are returned in whatever order is most efficient and may vary. > Note Columns of data types that lack a coherent ordering, such as time, are not good candidates for use in the ORDER BY clause of a window specification. Time, with or without time zone, lacks a coherent ordering because addition and subtraction do not have the expected effects. For example, the following is not generally true: x::time < x::time + '2 hour'::interval

frame_clause

The optional frame\_clause defines the window frame for window functions that depend on the frame (not all do). The window frame is a set of related rows for each row of the query (called the current row). The frame\_clause can be one of

{ RANGE | ROWS } <frame_start>
{ RANGE | ROWS } BETWEEN <frame_start> AND <frame_end>

where frame\_start and frame\_end can be one of

UNBOUNDED PRECEDING
value PRECEDING
CURRENT ROW
value FOLLOWING
UNBOUNDED FOLLOWING

If frame\_end is omitted it defaults to CURRENT ROW. Restrictions are that frame\_start cannot be UNBOUNDED FOLLOWING, frame\_end cannot be UNBOUNDED PRECEDING, and the frame\_end choice cannot appear earlier in the above list than the frame\_start choice — for example RANGE BETWEEN CURRENT ROW AND value 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 ORDER BY considers equivalent to the current row, or all rows if there is no ORDER BY). In general, UNBOUNDED PRECEDING means that the frame starts with the first row of the partition, and similarly UNBOUNDED FOLLOWING means that the frame ends with the last row of the partition (regardless of RANGE or ROWS mode). In ROWS mode, CURRENT ROW means that the frame starts or ends with the current row; but in RANGE mode it means that the frame starts or ends with the current row's first or last peer in the ORDER BY ordering. The value PRECEDING and value FOLLOWING cases are currently only allowed in ROWS mode. They indicate that the frame starts or ends with the row that many rows before or after the current row. value must be an integer expression not containing any variables, aggregate functions, or window functions. The value must not be null or negative; but it can be zero, which selects the current row itself.

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

Use either a ROWS or RANGE clause to express the bounds of the window. The window bound can be one, many, or all rows of a partition. You can express the bound of the window either in terms of a range of data values offset from the value in the current row (RANGE), or in terms of the number of rows offset from the current row (ROWS). When using the RANGE clause, you must also use an ORDER BY clause. This is because the calculation performed to produce the window requires that the values be sorted. Additionally, the ORDER BY clause cannot contain more than one expression, and the expression must result in either a date or a numeric value. When using the ROWS or RANGE clauses, if you specify only a starting row, the current row is used as the last row in the window.

PRECEDING — The PRECEDING clause defines the first row of the window using the current row as a reference point. The starting row is expressed in terms of the number of rows preceding the current row. For example, in the case of ROWS framing, 5 PRECEDING sets the window to start with the fifth row preceding the current row. In the case of RANGE framing, it sets the window to start with the first row whose ordering column value precedes that of the current row by 5 in the given order. If the specified order is ascending by date, this will be the first row within 5 days before the current row. UNBOUNDED PRECEDING sets the first row in the window to be the first row in the partition.

BETWEEN — The BETWEEN clause defines the first and last row of the window, using the current row as a reference point. First and last rows are expressed in terms of the number of rows preceding and following the current row, respectively. For example, BETWEEN 3 PRECEDING AND 5 FOLLOWING sets the window to start with the third row preceding the current row, and end with the fifth row following the current row. Use BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING to set the first and last rows in the window to be the first and last row in the partition, respectively. This is equivalent to the default behavior if no ROW or RANGE clause is specified.

FOLLOWING — The FOLLOWING clause defines the last row of the window using the current row as a reference point. The last row is expressed in terms of the number of rows following the current row. For example, in the case of ROWS framing, 5 FOLLOWING sets the window to end with the fifth row following the current row. In the case of RANGE framing, it sets the window to end with the last row whose ordering column value follows that of the current row by 5 in the given order. If the specified order is ascending by date, this will be the last row within 5 days after the current row. Use UNBOUNDED FOLLOWING to set the last row in the window to be the last row in the partition.

If you do not specify a ROW or a RANGE clause, the window bound starts with the first row in the partition ( UNBOUNDED PRECEDING) and ends with the current row ( CURRENT ROW) if ORDER BY is used. If an ORDER BY is not specified, the window starts with the first row in the partition ( UNBOUNDED PRECEDING) and ends with last row in the partition ( UNBOUNDED FOLLOWING).

The 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.

The UNION Clause

The UNION clause has this general form:

<select_statement> UNION [ALL | DISTINCT] <select_statement>

where 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 subquery expression 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.

The INTERSECT Clause

The INTERSECT clause has this general form:

<select_statement> INTERSECT [ALL | DISTINCT] <select_statement>

where 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.

The EXCEPT Clause

The EXCEPT clause has this general form:

<select_statement> EXCEPT [ALL | DISTINCT] <select_statement>

where 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.

The ORDER BY Clause

The optional ORDER BY clause has this general form:

ORDER BY <expression> [ASC | DESC | USING <operator>] [NULLS {FIRST | LAST}] [,...]

where 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 ORDER BY clause causes the result rows to be sorted according to the specified expressions. If two rows are equal according to the left-most 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.

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 may 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 may 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 may be specified in the USING clause. 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 upon 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 locale-specific collation order that was established when the database was created.

Character-string data is sorted according to the collation that applies to the column being sorted. That can be overridden as needed by including a COLLATE clause in the expression, for example ORDER BY mycolumn COLLATE "en_US". For information about defining collations, see CREATE COLLATION.

The LIMIT Clause

The LIMIT clause consists of two independent sub-clauses:

LIMIT {<count> | ALL}
OFFSET <start>

where 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, that is, 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 Greenplum Database also supports. It is:

OFFSET <start> [ ROW | ROWS ]
            FETCH { FIRST | NEXT } [ <count> ] { ROW | ROWS } ONLY

In this syntax, the start or count value is required by the standard to be a literal constant, a parameter, or a variable name; as a Greenplum Database extension, other expressions are allowed, but will generally need to be enclosed in parentheses to avoid ambiguity. If count is omitted in a FETCH clause, it defaults to 1. ROW and ROWS as well as FIRST and NEXT are noise words that don't influence the effects of these clauses. According to the standard, the OFFSET clause must come before the FETCH clause if both are present; but Greenplum Database 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 may 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 optimizer 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 defect; 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.

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 <table_name> [ , ... ] ] [ NOWAIT ]

where lock_strength can be one of

FOR UPDATE - Locks the table with an EXCLUSIVE lock.
FOR NO KEY UPDATE - Locks the table with an EXCLUSIVE lock.
FOR SHARE - Locks the table with a ROW SHARE lock.
FOR KEY SHARE - Locks the table with a ROW SHARE lock.

Note
By default Greenplum Database acquires the more restrictive EXCLUSIVE lock (rather than ROW EXCLUSIVE in PostgreSQL) for UPDATE, DELETE, and SELECT...FOR UPDATE operations on heap tables. When the Global Deadlock Detector is enabled the lock mode for UPDATE and DELETE operations on heap tables is ROW EXCLUSIVE. See Global Deadlock Detector. Greenplum always holds a table-level lock with SELECT...FOR UPDATE statements.

For more information on each row-level lock mode, refer to Explicit Locking in the PostgreSQL documentation.

To prevent the operation from waiting for other transactions to commit, use the NOWAIT option. With NOWAIT, the statement reports an error, rather than waiting, if a selected row cannot be locked immediately. Note that NOWAIT only affects whether the SELECT statement waits to obtain row-level locks. A required table-level lock is always taken in the ordinary way. For example, a SELECT FOR UPDATE NOWAIT statement will always wait for the required table-level lock; it behaves as if NOWAIT was omitted. 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 both 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.

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 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.

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

SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss ORDER BY column1;

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

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

The TABLE Command

The command

TABLE <name>

is completely 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.

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, films f WHERE f.did = d.did

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;

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';

Calculate the subtotals and grand totals of all sales for movie kind and distributor.

SELECT kind, distributor, sum(prc*qty) FROM sales
GROUP BY ROLLUP(kind, distributor)
ORDER BY 1,2,3;

Calculate the rank of movie distributors based on total sales:

SELECT distributor, sum(prc*qty), 
       rank() OVER (ORDER BY sum(prc*qty) DESC) 
FROM sale
GROUP BY distributor ORDER BY 2 DESC;

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;

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:

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

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);

CREATE FUNCTION distributors_2(int) RETURNS SETOF record AS 
$$ SELECT * FROM distributors WHERE did = $1; $$ LANGUAGE 
SQL;
SELECT * FROM distributors_2(111) AS (dist_id int, dist_name 
text);

This example uses a simple WITH clause:

WITH test AS (
  SELECT random() as x FROM generate_series(1, 3)
  )
SELECT * FROM test
UNION ALL
SELECT * FROM test;

This example uses the WITH clause to display per-product sales totals in only the top sales regions.

WITH regional_sales AS 
    SELECT region, SUM(amount) AS total_sales
    FROM orders
    GROUP BY region
  ), top_regions AS (
    SELECT region
    FROM regional_sales
    WHERE total_sales > (SELECT SUM(total_sales) FROM
       regional_sales)
  )
SELECT region, product, SUM(quantity) AS product_units,
   SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions) 
GROUP BY region, product;

The example could have been written without the WITH clause but would have required two levels of nested sub-SELECT statements.

This example uses the WITH RECURSIVE clause 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;

The typical form of recursive queries: an initial condition, followed by UNION [ALL], 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 WITH Queries (Common Table Expressions)in the Greenplum Database Administrator Guide for more examples.

Compatibility

The SELECT statement is compatible with the SQL standard, but there are some extensions and some missing features.

Omitted FROM Clauses

Greenplum Database allows one to omit the FROM clause. It has a straightforward use to compute the results of simple expressions. For example:

SELECT 2+2;

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

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

SELECT distributors.* WHERE distributors.name = 'Westward';

In earlier releases, setting a server configuration parameter, add_missing_from, to true allowed Greenplum Database to add an implicit entry to the query's FROM clause for each table referenced by the query. This is no longer allowed.

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). Greenplum Database 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 Greenplum Database allow AS to be omitted before an alias that is an unreserved keyword. But this is impractical for output column names, because of syntactic ambiguities.

ONLY and Inheritance

The SQL standard requires parentheses around the table name when writing ONLY, for example:

SELECT * FROM ONLY (tab1), ONLY (tab2) WHERE ...

Greenplum Database considers these parentheses to be optional.

Greenplum Database 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.)

Namespace Available to GROUP BY and ORDER BY

In the SQL-92 standard, an ORDER BY clause may only use output column names or numbers, while a GROUP BY clause may only use expressions based on input column names. Greenplum Database extends each of these clauses to allow the other choice as well (but it uses the standard's interpretation if there is ambiguity). Greenplum Database also allows both clauses to specify arbitrary expressions. Note that names appearing in an expression are always 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, Greenplum Database interprets an ORDER BY or GROUP BY expression the same way SQL:1999 does.

Functional Dependencies

Greenplum Database 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 Greenplum Database-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. This syntax is also used by IBM DB2. (Applications for Oracle frequently use a workaround involving the automatically generated rownum column, which is not available in Greenplum Database, to implement the effects of these clauses.)

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

Although FOR UPDATE appears in the SQL standard, the standard allows it only as an option of DECLARE CURSOR. Greenplum Database 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 option, do not appear in the standard.

Data-Modifying Statements in WITH

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

Nonstandard Clauses

The clause DISTINCT ON is not defined in the SQL standard.

Limited Use of STABLE and VOLATILE Functions

To prevent data from becoming out-of-sync across the segments in Greenplum Database, any function classified as STABLE or VOLATILE cannot be run at the segment database level if it contains SQL or modifies the database in any way. See CREATE FUNCTION for more information.