reference/sql/SELECT.html.md.erb

---
title: SELECT
---

Retrieves rows from a table or view.

## Synopsis<a id="topic1__section2"></a>

``` pre
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_specification)]
  [{UNION | INTERSECT | EXCEPT} [ALL] select]
  [ORDER BY expression [ASC | DESC | USING operator] [, ...]]
  [LIMIT {count | ALL}]
  [OFFSET start]
```

where *grouping\_element* can be one of:

``` pre
  ()
  expression
  ROLLUP (expression [,...])
  CUBE (expression [,...])
  GROUPING SETS ((grouping_element [, ...]))
```

where *window\_specification* can be:

``` pre
  [window_name]
  [PARTITION BY expression [, ...]]
  [ORDER BY expression [ASC | DESC | USING operator] [, ...]
     [{RANGE | ROWS} 
          { UNBOUNDED PRECEDING
          | expression PRECEDING
          | CURRENT ROW
          | BETWEEN window_frame_bound AND window_frame_bound }]]
                    where window_frame_bound can be one of:
                        UNBOUNDED PRECEDING
                        expression PRECEDING
                        CURRENT ROW
                        expression FOLLOWING
                        UNBOUNDED FOLLOWING
```

where *from\_item* can be one of:

``` pre
[ONLY] table_name [[AS] alias [( column_alias [, ...] )]]
(select) [AS] alias [( column_alias [, ...] )]
function_name ( [argument [, ...]] ) [AS] alias
             [( column_alias [, ...] 
                | column_definition [, ...] )]
function_name ( [argument [, ...]] ) AS 
              ( column_definition [, ...] )
from_item [NATURAL] join_type
            from_item
          [ON join_condition | USING ( join_column [, ...] )]
```

## Description<a id="topic1__section3"></a>

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

1.  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.
2.  If the `WHERE` clause is specified, all rows that do not satisfy the condition are eliminated from the output.
3.  If the `GROUP BY` clause is specified, the output is divided into groups of rows that match on one or more of the defined grouping elements. If the `HAVING` clause is present, it eliminates groups that do not satisfy the given condition.
4.  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.
5.  `DISTINCT` eliminates duplicate rows from the result. `DISTINCT ON` eliminates rows that match on all the specified expressions. `ALL` (the default) will return all candidate rows, including duplicates.
6.  The actual output rows are computed using the `SELECT` output expressions for each selected row.
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.
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.
9.  If the `LIMIT` or `OFFSET` clause is specified, the `SELECT` statement only returns a subset of the result rows.

You must have `SELECT` privilege on a table to read its values.

## Parameters<a id="topic1__section4"></a>

**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.

Using the clause `[AS] ` *output\_name*, another name can be specified for an output column. This name is primarily used to label the column for display. It can also 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. The `AS` keyword is optional in most cases (such as when declaring an alias for column names, constants, function calls, and simple unary operator expressions). In cases where the declared alias is a reserved SQL keyword, the *output\_name* must be enclosed in double quotes to avoid ambiguity.

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. There are a number of constructs that can be classified as an expression but do not follow any general syntax rules.

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.

**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 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](#topic1__section19) section for limitations of using correlated sub-selects in HAWQ.

 *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. Use parentheses if necessary to determine the order of nesting. In the absence of parentheses, `JOIN`s nest left-to-right. In any case `JOIN` binds more tightly than the commas separating `FROM` items.

`CROSS JOIN` and `INNER JOIN` produce a simple Cartesian product, the same result as you get from listing the two items 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 inputs.

`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.

**The WHERE Clause**
The optional `WHERE` clause has the general form:

``` pre
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:

``` pre
GROUP BY grouping_element [, ...]
```

where *grouping\_element* can be one of:

``` pre
()
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 (whereas without `GROUP BY`, an aggregate produces a single value computed across all the selected rows). When `GROUP BY` is present, it is not valid for the `SELECT` list expressions to refer to ungrouped columns except within aggregate functions, since there would be more than one possible value to return for an ungrouped column.

HAWQ 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:

``` pre
GROUP BY ROLLUP (a,b,c) 
```

is equivalent to:

``` pre
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:

``` pre
GROUP BY CUBE (a,b,c) 
```

is equivalent to:

``` pre
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.

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:

``` pre
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 `WINDOW` clause is used to define a window that can be used in the `OVER()` expression of a window function such as `rank` or `avg`. For example:

``` pre
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:

``` pre
WINDOW window_name AS (window_specification)
```

where *window\_specification* can be:

``` pre
[window_name]
[PARTITION BY expression [, ...]]
[ORDER BY expression [ASC | DESC | USING operator] [, ...]
    [{RANGE | ROWS} 
      { UNBOUNDED PRECEDING
      | expression PRECEDING
      | CURRENT ROW
      | BETWEEN window_frame_bound AND window_frame_bound }]]
             where window_frame_bound can be one of:
               UNBOUNDED PRECEDING
               expression PRECEDING
               CURRENT ROW
               expression FOLLOWING
               UNBOUNDED FOLLOWING
```

 *window\_name*   
Gives a name to the window specification.

PARTITION BY  
The `PARTITION BY` clause organizes the result set into logical groups based on the unique values of the specified expression. 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.

ORDER BY  
The `ORDER BY` clause defines 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`

ROWS | RANGE   
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 currentrow (`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:

``` pre
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.

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:

``` pre
               select_statement UNION [ALL] select_statement
            
```

where *select\_statement* is any `SELECT` statement without an `ORDER BY`, `LIMIT`, `FOR UPDATE`, or `FOR 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.)

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

Currently, `FOR UPDATE` and `FOR SHARE` may not be specified either for a `UNION` result or for any input of a `UNION`.

**The INTERSECT Clause**
The `INTERSECT` clause has this general form:

``` pre
               select_statement INTERSECT [ALL] select_statement
            
```

where *select\_statement* is any SELECT statement without an `ORDER             BY`, `LIMIT`, `FOR UPDATE`, or `FOR             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.

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 UPDATE` and `FOR SHARE` may not be specified either for an `INTERSECT` result or for any input of an `INTERSECT`.

**The EXCEPT Clause**
The `EXCEPT` clause has this general form:

``` pre
               select_statement EXCEPT [ALL] select_statement
            
```

where *select\_statement* is any `SELECT` statement without an `ORDER BY`, `LIMIT`, `FOR UPDATE`, or `FOR 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.

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             UPDATE` and `FOR SHARE` may not 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:

``` pre
ORDER BY expression [ASC | DESC | USING operator] [, ...]
```

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 result 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 a result 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` result list. Thus the following statement is valid:

``` pre
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 a result column name and an input column name, `ORDER BY` will interpret it as the result 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.)

The null value sorts higher than any other value. In other words, with ascending sort order, null values sort at the end, and with descending sort order, null values sort at the beginning.

Character-string data is sorted according to the locale-specific collation order that was established when the HAWQ system was initialized.

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

`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`. 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:

``` pre
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 would have gotten a report from an unpredictable time for each location.

The `DISTINCT             ON` expression(s) must match the left-most `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 LIMIT Clause**
The `LIMIT` clause consists of two independent sub-clauses:

``` pre
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.

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 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 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.

## Examples<a id="topic1__section18"></a>

To join the table `films` with the table `distributors`:

``` pre
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`:

``` pre
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:

``` pre
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`.

``` pre
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:

``` pre
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`):

``` pre
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:

``` pre
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:

``` pre
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);
```

## Compatibility<a id="topic1__section19"></a>

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

**Omitted FROM Clauses**
HAWQ allows you to omit the `FROM` clause. It has a straightforward use to compute the results of simple expressions. For example:

``` pre
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 compatibility with applications that rely on this behavior the *add\_missing\_from* configuration variable can be enabled.

**The AS Key Word**
In the SQL standard, the optional key word `AS` is just noise and can be omitted without affecting the meaning. The HAWQ parser requires this key word when renaming output columns because the type extensibility features lead to parsing ambiguities without it. `AS` is optional in `FROM` items, however.

**Namespace Available to GROUP BY and ORDER BY**
In the SQL-92 standard, an `ORDER BY` clause may only use result column names or numbers, while a `GROUP BY` clause may only use expressions based on input column names. HAWQ extends each of these clauses to allow the other choice as well (but it uses the standard's interpretation if there is ambiguity). HAWQ 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 result-column names.

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

**Nonstandard Clauses**
The clauses `DISTINCT ON`, `LIMIT`, and `OFFSET` are 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 HAWQ, any function classified as `STABLE` or `VOLATILE` cannot be executed at the segment database level if it contains SQL or modifies the database in any way.

## See Also<a id="topic1__section25"></a>

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