Predicates in SQL
Predicates are keywords that specify a relationship between two expressions.
Comparison Predicate
The syntax for comparison predicates is as follows:
expression_1 comparison_operator expression_2
In a comparison predicate,
expression2 can be a subquery. If
expression2 is a subquery and does not return any rows, the comparison predicate evaluates to false. For information about subqueries, see
Subqueries in the WHERE Clause. For more information about comparison operators, see Comparison Operators.
Pattern-matching Predicates
Pattern-matching predicates (the LIKE family of predicates) are used to search for a specified pattern in text, an expression, or column. These predicates include:
• LIKE
• BEGINNING, ENDING, CONTAINING
The specific predicate to use depends on how complex the pattern needs to be. All predicates in the LIKE family have the same SQL syntax, operate on the same data types, and can control the case-sensitivity of the matching.
The LIKE family of predicates performs pattern matching for the character data types (char, varchar) and Unicode data types (nchar, nvarchar).
Note: Actian Data Platform supports constant LIKE patterns only.
The LIKE family of predicates has the following syntax:
expression [NOT] [LIKE|BEGINNING|CONTAINING|ENDING] pattern
[WITH CASE | WITHOUT CASE]
[ESCAPE escape_character]
where
expression
Is a column name or a string expression
pattern
Specifies the pattern to be matched. The pattern is typically a string literal but can be an arbitrary string expression.
The patterns supported depends upon the specific predicate used.
WITH CASE | WITHOUT CASE
Indicates whether to match the case of the pattern. This option can be used before, after, or instead of the ESCAPE clause.
Default: If not specified, the collation type of the expression is used, typically WITH CASE.
ESCAPE escape_character
Specifies the character to use to escape another character or to enable a character's special meaning in a pattern.
LIKE Predicate
Use LIKE in a WHERE clause to search for a specified pattern in a column.
LIKE performs pattern matching for the character and Unicode data types.
The LIKE predicate has the following syntax:
expression [NOT] LIKE pattern [WITH CASE | WITHOUT CASE]
[WITH DIACRITICAL | WITHOUT DIACRITICAL]
[ESCAPE escape_character]
where
expression
Is a column name or an expression containing string functions
pattern
Specifies the pattern to be matched. The pattern is typically a string literal but can be an arbitrary string expression.
The pattern-matching (wild card) characters are as follows:
% (percent sign)
Denotes 0 or more characters
_ (underscore)
Denotes a single character
\|
Denotes the alternation operator
WITH CASE | WITHOUT CASE
Indicates whether to match the case of the pattern. This option can be used before, after, or instead of the ESCAPE clause.
Default: WITH CASE
WITH DIACRITICAL | WITHOUT DIACRITICAL
Indicates whether to ignore diacritical marks. For example, Latin little “e” will match Latin little “e” with acute if the WITHOUT DIACRITICAL is specified.
Default: WITH DIACRITICAL
ESCAPE escape_character
Specifies an escape character, which suppresses any special meaning for the character following it, allowing the character to be entered literally. The following characters can be escaped:
• The pattern-matching characters % and _.
• The escape character itself. To enter the escape character literally, type it twice.
• The | character, which can be used to specify alternate patterns to match.
LIKE does not ignore the trailing blanks present with a char or nchar data type. If you are matching a char value (that is padded with blanks when it is inserted) or if the value has trailing blanks that were entered by the user, include these trailing blanks in your pattern. For example, if searching a char(10) column for rows that contain the name harold, specify the trailing blanks in the pattern to be matched:
name like 'harold '
Four blanks are added to the pattern after the name to include the trailing blanks.
Because blanks are not significant when performing comparisons of c data types, the LIKE predicate returns a correct result whether or not trailing blanks are included in the pattern.
LIKE Examples
The following examples illustrate some uses of the pattern-matching capabilities of the LIKE predicate.
To match any string starting with a:
name LIKE 'a%'
To match any two characters followed by 25%:
name LIKE '__25\%' ESCAPE '\'
To match a string starting with a backslash. Because there is no ESCAPE clause, the backslash is taken literally:
name LIKE '\%'
To match a string starting with a backslash and ending with a percent:
name LIKE '\\%\%' ESCAPE '\'
To detect names that start with S and end with h, disregarding any leading or trailing spaces:
SQUEEZE(name) LIKE 'S%h'
To detect a single quote, repeat the quote:
name LIKE ''''
To search for multiple patterns, use escaped | as a delimiter. For example, the following will match if string_1 contains ABC, 123, or xyz:
string_1 LIKE '%ABC%@|%123%@|%xyz%' ESCAPE '@'
BEGINNING, CONTAINING, and ENDING Predicates
Use BEGINNING, CONTAINING, or ENDING in a WHERE clause to search for a specified pattern in a column.
These predicates have the following syntax:
expression [NOT] BEGINNING | CONTAINING | ENDING pattern
[WITH CASE | WITHOUT CASE] [ESCAPE escape_character]
where
expression
Is a column name or an expression containing string functions.
BEGINNING
Matches if the pattern string is found at the beginning of the text.
CONTAINING
Matches if the pattern string is found within the text.
ENDING
Matches if the pattern string is found at the end of the text.
pattern
Specifies the pattern to be matched. The pattern must be a string literal.
BETWEEN Predicate
The following table explains the operators BETWEEN and NOT BETWEEN:
x, y, and z are expressions, and can include subqueries.
IN Predicate
The following table explains the operators IN and NOT IN:
Any-or-All Predicate
The any-or-all predicate takes the following form:
any-or-all-operator (subquery)
The subquery must have exactly one element in the target list of its outermost subselect (so that it evaluates to a set of single values rather than a set of rows). The any-or-all operator must be one of the following:
The != (instead of <>) can also be used to specify not equal. Include a space between the comparison operator and the keyword ANY or ALL.
A predicate that includes the ANY operator is true if the specified comparison is true for at least one value y in the set of values returned by the subquery. If the subquery returns no rows, the ANY comparison is false.
A predicate that includes the ALL operator is true if the specified comparison is true for all values y in the set of values returned by the subquery. If the subquery returns no rows, the ALL comparison is true.
The operator =ANY is equivalent to the operator IN. For example:
SELECT ename
FROM employee
WHERE dept = ANY
(SELECT dno
FROM dept
WHERE floor = 3);
can be rewritten as:
SELECT ename
FROM employee
WHERE dept IN
(SELECT dno
FROM dept
WHERE floor = 3);
The operator SOME is a synonym for operator ANY. For example:
SELECT name
FROM employee
WHERE dept = SOME
(SELECT dno
FROM dept
WHERE floor = 3);
EXISTS Predicate
The EXISTS predicate takes the following form:
[NOT] EXISTS (subquery)
It evaluates to true if the set returned by the subquery is not empty. For example:
SELECT ename
FROM employee
WHERE EXISTS
(SELECT *
FROM dept
WHERE dno = employee.dept
AND floor = 3);
It is typical, but not required, for the subquery argument to EXISTS to be of the form SELECT *.
IS NULL Predicate
Use IS NULL to determine whether an expression is null, because you cannot test for null by using the = comparison operator. When applied to row value expressions, all elements must test the same.
The IS NULL predicate takes the following form:
IS [NOT] NULL
For example:
x IS NULL
is true if x is a null.
IS UNKNOWN is a synonym for IS NULL when the expression is of the BOOLEAN type.
IS INTEGER Predicate
Use IS INTEGER to determine if a particular result can be assigned to a column of the given data type. It is especially useful for cleaning data or validating data input. When applied to row value expressions, all elements must test the same.
The IS INTEGER predicate takes the following form:
IS [NOT] INTEGER
For example:
x IS INTEGER
is true if x is integer in form. If x is a string, then this will be true if the value is a number where any fractional digits are zero and the signed result can be stored in an int8. Any leading or trailing white space is ignored. If x is a DECIMAL or a FLOAT value, then this predicate is true if the value can be stored in an int8 column and any fractional digits are zero.
If all values in a column pass this predicate, then the whole column can be coerced into a int8 column.
The following predicates are all true:
' +12345 ' IS INTEGER
'1.000000' IS INTEGER
1.0e10 IS INTEGER
DECIMAL('1234567890123456789012345', 25,0) IS NOT INTEGER
'number' IS NOT INTEGER
'123 456' IS NOT INTEGER
IS DECIMAL Predicate
Use IS DECIMAL to determine if a particular result can be assigned to a column of the given data type. It is especially useful for cleaning data or validating data input. When applied to row value expressions, all elements must test the same.
The IS DECIMAL predicate takes the following form:
IS [NOT] DECIMAL
For example:
x IS DECIMAL
is true if x is decimal in form. If x is a string, then this is true if the value is a number that can be stored as a decimal data type with no loss of accuracy. Any leading or trailing white space is ignored. If x is a FLOAT value then this predicate is true only if the number can be stored in a decimal column without loss of precision of overflow.
The following predicates are all true:
' +12345 ' IS DECIMAL
'1.000000' IS DECIMAL
1.0e10 IS DECIMAL
DECIMAL('1234567890123456789012345', 25,0) IS DECIMAL
'number' IS NOT DECIMAL
'123 456' IS NOT DECIMAL
'1.0e40' IS NOT DECIMAL
If all values in a column pass this predicate, then the whole column can be coerced into a decimal column.
IS FLOAT Predicate
Use IS FLOAT to determine if a particular result can be assigned to a column of the given data type. It is especially useful for cleaning data or validating data input. When applied to row value expressions, all elements must test the same.
The IS FLOAT predicate takes the following form:
IS [NOT] FLOAT
For example:
x IS FLOAT
is true if x is float in form. If x is a string, then this is true if the value is a number that can be stored as a float data type. All integers and decimals can be represented as float but there may be some loss of accuracy. Any leading or trailing white space is ignored.
If all values in a column pass this predicate then the whole column can be coerced into a float column.
The following predicates are all true:
' +12345 ' IS FLOAT
'1.000000' IS FLOAT
1.0e10 IS FLOAT
DECIMAL('1234567890123456789012345', 25,0) IS FLOAT
'number' IS NOT FLOAT
'123 456' IS NOT FLOAT
'1.0e4000' IS NOT FLOAT
IS TRUE, IS FALSE, IS UNKNOWN Predicates
The IS Boolean operator behaves according to the following truth table:
That is:
• IS TRUE is true for a BOOLEAN TRUE.
• IS FALSE is true for a BOOLEAN FALSE.
• IS UNKNOWN is true for an unknown (NULL) value.
• Every other comparison is false.
When applied to row value expressions, all elements must test the same.