OpenEdge Data Management:<br />SQL Reference Quantified Predicate

Release 10.1A: OpenEdge Data Management:
SQL Reference

Quantified Predicate

The quantified predicate compares a value with a collection of values using a relational operator. A quantified predicate has the same form as a basic predicate with the query_expression being preceded by the ALL, ANY, or SOME keyword. The result table returned by query_expression can contain only a single column.

When you specify ALL, the predicate evaluates to true if the query_expression returns no values or the specified relationship is true for all the values returned.

When you specify SOME or ANY, the predicate evaluates to true if the specified relationship is true for at least one value returned by the query_expression. There is no difference between the SOME and ANY keywords. The predicate evaluates to false if the query_expression returns no values or if the specified relationship is false for all the values returned.

This is the syntax for a quantified_predicate:
Syntax
expression relop { ALL | ANY | SOME } ( query_expression ) 
Example
10 < ANY ( SELECT COUNT(*) 
         FROM order_tbl
         GROUP BY custid ;
          ) 
BETWEEN Predicate

The BETWEEN predicate can be used to determine if a value is within a specified value range or not. The first expression specifies the lower bound of the range and the second expression specifies the upper bound of the range.

The predicate evaluates to true if the value is greater than or equal to the lower bound of the range and less than or equal to the upper bound of the range.

This is the syntax for a between_predicate:
Syntax
expression [ NOT ] BETWEEN expression AND expression 
Example
salary BETWEEN 20000.00 AND 100000.00 
NULL Predicate

The NULL predicate can be used for testing null values of database table columns.

This is the syntax for a null_predicate.
Syntax
column_name IS [ NOT ] NULL 
Example
contact_name IS NOT NULL 
LIKE Predicate

The LIKE predicate searches for strings that have a certain pattern. The pattern is specified after the LIKE keyword in a string constant. The pattern can be specified by a string in which the underscore ( _ ) and percent sign ( % ) characters have special semantics.

Use the ESCAPE clause to disable the special semantics given to the characters ( _ ) and
( % ). The escape character specified must precede the special characters in order to disable their special semantics.

This is the syntax for a like_predicate:
Syntax
column_name  [  NOT  ] LIKE string_constant  [  ESCAPE escape_character  ] 
Note

The column_name specified in the LIKE predicate can be a column, a string constant, or an arbitrary character expression (such as SUBSTRING or LTRIM).

The string_constant may be a string constant or a scalar function call.

The escape_character must be a one character string constant.

A percent sign ( % ) in the pattern matches zero or more characters of the column string.

A underscore symbol ( _ ) in the pattern matches any single character of the column string.

The LIKE predicate is multi-byte enabled. The string_constant and the escape_character may contain multi-byte characters, and the escape_character can be a multi-byte character. A percent sign ( % ) or an underscore ( _ ) in the string_constant can represent a multi-byte character. However, the percent sign or underscore itself must be the single-byte ASCII encoding.

Example

This example illustrates three ways to use the LIKE predicate:
cust_name LIKE ’%Computer%’
 
cust_name LIKE ’___’
 
item_name LIKE ’%\_%’ ESCAPE ’\’  
In the first LIKE clause, for all strings with the substring ’Computer’ the predicate evaluates to true. In the second LIKE clause, for all strings which are exactly three characters long the predicate evaluates to true. In the third LIKE clause the backslash character ( \ ) is specified as the escape character, which means that the special interpretation given to the underscore character ( _ ) is disabled. The pattern evaluates to TRUE if the item_name column has embedded underscore characters.

EXISTS Predicate

The EXISTS predicate can be used to check for the existence of specific rows. The query_expression returns rows rather than values. The predicate evaluates to true if the number of rows returned by the query_expression is nonzero.

This is the syntax for an exists_predicate:
Syntax
EXISTS (query_expression) 
Example

In this example, the predicate evaluates to true if the specified customer has any orders:
EXISTS (SELECT * FROM order_tbl
     WHERE order_tbl.custid = ’888’ ;) 
IN Predicate

The IN predicate can be used to compare a value with a set of values. If an IN predicate specifies a query expression, then the result table it returns can contain only a single column.

This is the syntax for an in_predicate:
Syntax
expression [ NOT ] IN
  { (query_expression) | (constant , constant [ , ... ] )  } 
Example
address.state IN (‘MA’, ‘NH’) 
OUTER JOIN Predicate

An outer join predicate specifies two tables and returns a result table that contains all the rows from one of the tables, even if there is no matching row in the other table.

This is the syntax for an outer_join_predicate:
Syntax
[ table_name.]column = [ table_name.]column (+)
  | [ table_name.]column (+) = [ table_name.]column 