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 Data Types and SubtypesData Definition (DDL) Statements 
Quantifiers

A question mark (‘?’) immediately following a character or class indicates that the preceding item may occur 0 or 1 times to match:

'Hallon' similar to 'Hal?on'                   -- false
'Hallon' similar to 'Hal?lon'                  -- true
'Hallon' similar to 'Halll?on'                 -- true
'Hallon' similar to 'Hallll?on'                -- false
'Hallon' similar to 'Halx?lon'                 -- true
'Hallon' similar to 'H[a-c]?llon[x-z]?'        -- true

An asterisk (‘*’) immediately following a character or class indicates that the preceding item may occur 0 or more times to match:

'Icaque' similar to 'Ica*que'                  -- true
'Icaque' similar to 'Icar*que'                 -- true
'Icaque' similar to 'I[a-c]*que'               -- true
'Icaque' similar to '_*'                       -- true
'Icaque' similar to '[[:ALPHA:]]*'             -- true
'Icaque' similar to 'Ica[xyz]*e'               -- false

A plus sign (‘+’) immediately following a character or class indicates that the preceding item must occur 1 or more times to match:

'Jujube' similar to 'Ju_+'                     -- true
'Jujube' similar to 'Ju+jube'                  -- true
'Jujube' similar to 'Jujuber+'                 -- false
'Jujube' similar to 'J[jux]+be'                -- true
'Jujube' sililar to 'J[[:DIGIT:]]+ujube'       -- false

If a character or class is followed by a number enclosed in braces (‘{’ and ‘}’), it must be repeated exactly that number of times to match:

'Kiwi' similar to 'Ki{2}wi'                    -- false
'Kiwi' similar to 'K[ipw]{2}i'                 -- true
'Kiwi' similar to 'K[ipw]{2}'                  -- false
'Kiwi' similar to 'K[ipw]{3}'                  -- true

If the number is followed by a comma (‘,’), the item must be repeated at least that number of times to match:

'Limone' similar to 'Li{2,}mone'               -- false
'Limone' similar to 'Li{1,}mone'               -- true
'Limone' similar to 'Li[nezom]{2,}'            -- true

If the braces contain two numbers separated by a comma, the second number not smaller than the first, then the item must be repeated at least the first number and at most the second number of times to match:

'Mandarijn' similar to 'M[a-p]{2,5}rijn'       -- true
'Mandarijn' similar to 'M[a-p]{2,3}rijn'       -- false
'Mandarijn' similar to 'M[a-p]{2,3}arijn'      -- true

The quantifiers ‘?’, ‘*’ and ‘+’ are shorthand for {0,1}, {0,} and {1,}, respectively.

OR-ing Terms

Regular expression terms can be OR’ed with the ‘|’ operator.A match is made when the argument string matches at least one of the terms:

'Nektarin' similar to 'Nek|tarin'              -- false
'Nektarin' similar to 'Nektarin|Persika'       -- true
'Nektarin' similar to 'M_+|N_+|P_+'            -- true
Subexpressions

One or more parts of the regular expression can be grouped into subexpressions (also called subpatterns) by placing them between parentheses (‘(’ and ‘)’).A subexpression is a regular expression in its own right.It can contain all the elements allowed in a regular expression, and can also have quantifiers added to it.

'Orange' similar to 'O(ra|ri|ro)nge'           -- true
'Orange' similar to 'O(r[a-e])+nge'            -- true
'Orange' similar to 'O(ra){2,4}nge'            -- false
'Orange' similar to 'O(r(an|in)g|rong)?e'      -- true
IS [NOT] DISTINCT FROM
Syntax
<operand1> IS [NOT] DISTINCT FROM <operand2>

Two operands are considered DISTINCT (different) if they have a different value or if one of them is NULL and the other non-null.They are considered NOT DISTINCT (equal) if they have the same value or if both of them are NULL.

IS [NOT] DISTINCT FROM always returns TRUE or FALSE and never UNKNOWN (NULL) (unknown value).Operators ‘=’ and ‘<>’, conversely, will return UNKNOWN (NULL) if one or both operands are NULL.

Table 1. Results of Various Comparison Predicates

Operand values

Result of various predicates

=

IS NOT DISTINCT FROM

<>

IS DISTINCT FROM

Same value

TRUE

TRUE

FALSE

FALSE

Different values

FALSE

FALSE

TRUE

TRUE

Both NULL

UNKNOWN

TRUE

UNKNOWN

FALSE

One NULL, one non-NULL

UNKNOWN

FALSE

UNKNOWN

TRUE
Examples
SELECT ID, NAME, TEACHER
FROM COURSES
WHERE START_DAY IS NOT DISTINCT FROM END_DAY;

-- PSQL fragment
IF (NEW.JOB IS DISTINCT FROM OLD.JOB)
THEN POST_EVENT 'JOB_CHANGED';
See also

[fblangref50-commons-isnotnull], [fblangref50-commons-isnotboolean]

Boolean IS [NOT]
Syntax
<value> IS [NOT] { TRUE | FALSE | UNKNOWN }

The IS predicate with Boolean literal values checks if the expression on the left side matches the Boolean value on the right side.The expression on the left side must be of type BOOLEAN, otherwise an exception is raised.

The IS [NOT] UNKNOWN is equivalent to IS [NOT] NULL.

Note

The right side of the predicate only accepts the literals TRUE, FALSE, UNKNOWN, and NULL.It does not accept expressions.
Using the IS predicate with a Boolean data type
-- Checking FALSE value
SELECT * FROM TBOOL WHERE BVAL IS FALSE;

ID            BVAL
============= =======
2             <false>

-- Checking UNKNOWN value
SELECT * FROM TBOOL WHERE BVAL IS UNKNOWN;

ID            BVAL
============= =======
3             <null>
See also

[fblangref50-commons-isnotnull]

IS [NOT] NULL
Syntax
<value> IS [NOT] NULL

Since NULL is not a value, these operators are not comparison operators.The IS [NOT] NULL predicate tests that the expression on the left side has a value (IS NOT NULL) or has no value (IS NULL).

Example

Search for sales entries that have no shipment date set for them:

SELECT * FROM SALES
WHERE SHIP_DATE IS NULL;
Note
Note regarding the IS predicates

The IS predicates take precedence above the others.

Existential Predicates

This group of predicates includes those that use subqueries to submit values for all kinds of assertions in search conditions.Existential predicates are so called because they use various methods to test for the existence or non-existence of some condition, returning TRUE if the existence or non-existence is confirmed or FALSE otherwise.

EXISTS

Syntax
[NOT] EXISTS (<select_stmt>)

The EXISTS predicate uses a subquery expression as its argument.It returns TRUE if the subquery result contains at least one row, otherwise it returns FALSE.

NOT EXISTS returns FALSE if the subquery result contains at least one row, otherwise it returns TRUE.

Note

The subquery can specify multiple columns, or SELECT *, because the evaluation is made on the number of rows that match its criteria, not on the data.
Examples

  1. Find those employees who have projects.

    SELECT *
FROM employee
WHERE EXISTS(SELECT *
             FROM  employee_project ep
             WHERE ep.emp_no = employee.emp_no)

  2. Find those employees who have no projects.

    SELECT *
FROM employee
WHERE NOT EXISTS(SELECT *
                 FROM employee_project ep
                 WHERE ep.emp_no = employee.emp_no)

IN

Syntax
<value> [NOT] IN (<select_stmt> | <value_list>)

<value_list> ::= <value_1> [, <value_2> ...]

The IN predicate tests whether the value of the expression on the left side is present in the set of values specified on the right side.The set of values cannot have more than 65535 items.The IN predicate can be replaced with the following equivalent forms:

(<value> = <value_1> [OR <value> = <value_2> ...])

<value> = { ANY | SOME } (<select_stmt>)

When the IN predicate is used in the search conditions of DML queries, the Firebird optimizer can use an index on the searched column, if a suitable one exists.Lists that are known to be constant are pre-evaluated as invariants and cached as a binary search tree, making comparisons faster if the condition needs to be tested for many rows or if the value list is long.

In its second form, the IN predicate tests whether the value of the expression on the left side is present — or not present, if NOT IN is used — in the result of the subquery on the right side.

The subquery must specify only one column, otherwise the error “count of column list and variable list do not match” will occur.

Queries using an IN predicate with a subquery can be replaced with a similar query using the EXISTS predicate.For example, the following query:

SELECT
  model, speed, hd
FROM PC
WHERE
model IN (SELECT model
          FROM product
          WHERE maker = 'A');

can be replaced with a similar one using the EXISTS predicate:

SELECT
  model, speed, hd
FROM PC
WHERE
 EXISTS (SELECT *
         FROM product
         WHERE maker = 'A'
           AND product.model = PC.model);

However, a query using NOT IN with a subquery does not always give the same result as its NOT EXISTS counterpart.The reason is that EXISTS always returns TRUE or FALSE, whereas IN returns NULL in one of these two cases:

  1. when the test value is NULL and the IN () list is not empty

  2. when the test value has no match in the IN () list and at least one list element is NULL

It is in only these two cases that IN () will return NULL while the EXISTS predicate will return FALSE (“no matching row found”).In a search or, for example, an IF (…​) statement, both results mean “failure”, and it makes no difference to the outcome.

For the same data, NOT IN () will return NULL, while NOT EXISTS will return TRUE, leading to opposite results.

As an example, suppose you have the following query:

-- Looking for people who were not born
-- on the same day as any famous New York citizen
SELECT P1.name AS NAME
FROM Personnel P1
WHERE P1.birthday NOT IN (SELECT C1.birthday
                          FROM Celebrities C1
                          WHERE C1.birthcity = 'New York');

Now, assume that the NY celebrities list is not empty and contains at least one NULL birthday.Then for every citizen who does not share his birthday with a NY celebrity, NOT IN will return NULL, because that is what IN does.The search condition is thereby not satisfied and the citizen will be left out of the SELECT result, which is wrong.

For citizens whose birthday does match with a celebrity’s birthday, NOT IN will correctly return FALSE, so they will be left out too, and no rows will be returned.

If the NOT EXISTS form is used:

-- Looking for people who were not born
-- on the same day as any famous New York citizen
SELECT P1.name AS NAME
FROM Personnel P1
WHERE NOT EXISTS (SELECT *
                  FROM Celebrities C1
                  WHERE C1.birthcity = 'New York'
                    AND C1.birthday = P1.birthday);

non-matches will have a NOT EXISTS result of TRUE and their records will be in the result set.

Tip

If there is any chance of NULLs being encountered when searching for a non-match, you will want to use NOT EXISTS.
Examples of use

  1. Find employees with the names “Pete”, “Ann” and “Roger”:

    SELECT *
FROM EMPLOYEE
WHERE FIRST_NAME IN ('Pete', 'Ann', 'Roger');

  2. Find all computers that have models whose manufacturer starts with the letter “A”:

    SELECT
  model, speed, hd
FROM PC
WHERE
  model IN (SELECT model
            FROM product
            WHERE maker STARTING WITH 'A');
See also

EXISTS

SINGULAR

Syntax
[NOT] SINGULAR (<select_stmt>)

The SINGULAR predicate takes a subquery as its argument and evaluates it as TRUE if the subquery returns exactly one row, otherwise the predicate is evaluated as FALSE.The subquery may list several output columns since the rows are not returned anyway, they are only tested for (singular) existence.For brevity, people usually specify ‘SELECT *’.The SINGULAR predicate can return only two values: TRUE or FALSE.

Example

Find those employees who have only one project.

SELECT *
FROM employee
WHERE SINGULAR(SELECT *
               FROM employee_project ep
               WHERE ep.emp_no = employee.emp_no)

Quantified Subquery Predicates

A quantifier is a logical operator that sets the number of objects for which this condition is true.It is not a numeric quantity, but a logical one that connects the condition with the full set of possible objects.Such predicates are based on logical universal and existential quantifiers that are recognised in formal logic.

In subquery expressions, quantified predicates make it possible to compare separate values with the results of subqueries;they have the following common form:

<value expression> <comparison operator> <quantifier> <subquery>

ALL

Syntax
<value> <op> ALL (<select_stmt>)

When the ALL quantifier is used, the predicate is TRUE if every value returned by the subquery satisfies the condition in the predicate of the main query.

Example

Show only those clients whose ratings are higher than the rating of every client in Paris.

SELECT c1.*
FROM Customers c1
WHERE c1.rating > ALL
      (SELECT c2.rating
       FROM Customers c2
       WHERE c2.city = 'Paris')
Important

If the subquery returns an empty set, the predicate is TRUE for every left-side value, regardless of the operator.This may appear to be contradictory, because every left-side value will thus be considered both smaller and greater than, both equal to and unequal to, every element of the right-side stream.

Nevertheless, it aligns perfectly with formal logic: if the set is empty, the predicate is true for every row in the set.

ANY and SOME

Syntax
<value> <op> {ANY | SOME} (<select_stmt>)

The quantifiers ANY and SOME are identical in their behaviour.Both are specified in the SQL standard, and they be used interchangeably to improve the readability of operators.When the ANY or the SOME quantifier is used, the predicate is TRUE if any of the values returned by the subquery satisfies the condition in the predicate of the main query.If the subquery returns no rows at all, the predicate is automatically considered as FALSE.

Example

Show only those clients whose ratings are higher than those of one or more clients in Rome.

SELECT *
FROM Customers
WHERE rating > ANY
      (SELECT rating
       FROM Customers
       WHERE city = 'Rome')