Craig S. Mullins
Using Check Constraints to Simulate Domains.by Craig S. Mullins
DB2 has provided table check constraints for a number of releases now, but many organizations have yet to capitalize on their functionality. Check constraints enable enhanced data integrity without requiring procedural logic (such as in stored procedures and triggers). Let’s examine the basics of table check constraints.
A constraint is basically a restriction placed upon
the data values that can be stored in a column or columns of a table. Of course,
most RDBMS products provide several different types of constraints, such as
referential constraints (to define primary and foreign keys) and unique
constraints (to prohibit duplicates).
constraints place specific data value restrictions on the contents of a column
through the specification of a Boolean expression. The expression is explicitly
defined in the table DDL and is formulated in much the same way that SQL WHERE
clauses are formulated. Any attempt to modify the column data (i.e. during
INSERT and UPDATE processing) will cause the expression to be evaluated. If the
modification conforms to the Boolean expression, the modification is permitted
to continue. If not, the statement
will fail with a constraint violation.
functionality is great for simulating the relational concept of a domain. A
domain is basically the set of valid values that a column or data type can take
on. Check constraints only simulate domains, though, because there are other
features provided by domains that are not provided by check constraints. One
such feature is that columns pooled from separate domains must not be compared
or operated on by expressions that require the same type of data for both
operands. For domains to truly be supported the DBMS should support both check
constraints and user-defined data types with strong type checking. This
prohibits allowing ridiculous operations, such as comparing IQ to shoe size or
adding Australian dollars to Euros.
constraints are written using recognizable SQL syntax. This makes them easy to
implement for anyone who has even a passing familiarity with SQL. The check
constraint consists of two components: a constraint name and a check condition.
constraint name is an SQL identifier and is used to reference or identify the
constraint. The same constraint name cannot be specified more than once for the
same table. If a constraint name is not explicitly coded, DB2 will create a
unique name automatically for the constraint.
check condition defines the actual constraint logic. The check condition can be defined using any of the basic
predicates (>, <, =, <>, <=, >=), as well as BETWEEN, IN,
LIKE, and NULL. Furthermore, AND
and OR can be used to string conditions together.
are, however, restrictions on how check constraints are formulated. Some of
these restrictions include:
on the entire length of the check condition.
tables may not be accessed in the check condition.
limited subset of SQL operations are permitted (for example subselects and
column functions are prohibited in a check constraint).
the operands (usually the first) of the check constraint must be the name of a
column contained in the table for which the constraint is defined.
operand (usually the second) must be either another column name in the same
table or a constant value.
second operand is a constant, it must be compatible with the data type of the
first operand. If the second
operand is a column, it must be the same data type as the first column
constraints enable the DBA or database designer to specify more robust data
integrity rules directly into the database.
Consider the following example:
CREATE statement for the EMP table contains three different check constraints:
The name of the first check constraint for the EMP table is CHECK_EMPNO.
It is defined on the EMPNO column. The
constraint ensures that the EMPNO column can contain values that range from 100
to 25000 (instead of the domain of all valid integers).
2. The second check constraint for this table is on the EMP_TYPE column. This is an example of an unnamed constraint. Though this is possible, it is not recommended. It is best to always provide an explicit constraint name in order to ease identification and administration. This specific constraint restricts the values that can be placed into EMP_TYPE as: 'TEMP', 'FULLTIME', and 'CONTRACT'; no other values would be accepted.
The last check constraint on this table is named CHECK_SALARY.
It effectively ensures that no employee can be entered with a salary of
more than $50,000. (Now who would want to work there?)
vs. Table Level Constraints
first check constraint example we reviewed showed a column-level check
constraint. However, check constraints also may be coded at the table-level. A
column-level check constraint is defined in the DDL immediately after the
column. Appropriately enough, a table-level check constraint is defined after
all of the columns of the table have already been defined.
is quite common for business rules to require access to multiple columns within
a single table. When this situation
occurs, it is wise to code the business rule into a check constraint at the
table-level, instead of at the column level.
Of course, any column-level check constraint can also be defined at the
table-level, as well. In terms of
functionality, there is no difference between an integrity constraint defined at
the table-level and the same constraint defined at the column-level.
augment our sample table DDL to add two table-level check constraints:
CREATE statement for the EMP table has been modified to contain two table-level
check constraints having the following ramifications:
The name of the first table-level check constraint for the EMP table is
COMM_VS_SALARY. This constraint
will ensure that no employee can earn more commission than salary.
The second table-level check constraint is named COMM_BONUS.
This constraint will ensure that every employee either earns a commission
or a bonus (or possibly, both).
what are the benefits of check constraints? The primary benefit is the ability
to enforce business rules directly in each database without requiring additional
application logic. Once defined, the business rule is physically implemented and
cannot be bypassed. Check constraints also provide the following benefits:
there is no additional programming required, DBAs can implement check
constraints without involving the application programming staff. This
effectively minimizes the amount of code that must be written by the programming
staff. With the significant
application backlog within most organizations, this can be the most crucial
reason to utilize check constraints.
constraints provide better data integrity.
As check constraints are always executed whenever the data in the column
upon which they are defined is to be modified, the business rule is not bypassed
during ad hoc processing and dynamic SQL. When business rules are enforced using
application programming logic instead, the rules can not be checked during ad
constraints promote consistency. Because they are implemented once, in the table
DDL, each constraint is always enforced. Constraints written in application
logic, on the other hand, must be executed within each program that modifies any
data to which the constraint applies. This can cause code duplication and
inconsistent maintenance resulting in inaccurate business rule support.
check constraints coded in DDL will outperform the corresponding application
overall impact of check constraints will be to increase application development
productivity while at the same time promoting higher data integrity.
Constraints, NULLs, and Defaults
additional consideration for check constraints is the relational NULL. Any
nullable column also defined with a check constraint can be set to null. When
the column is set to null, the check constraint evaluates to unknown.
Because null indicates the lack of a value, the presence of a null will
not violate the check constraint.
DB2 provides the ability to specify defaults for table columns – both
system-defined defaults (pre-defined and automatically set by the DBMS) and
user-defined defaults. When a row is inserted or loaded into the table and no
value is specified for the column, the column will be set to the value that has
been identified in the column default specification. For example, we could define a default for the EMP_TYPE
column of our sample EMP table as follows:
a row is inserted without specifying an EMP_TYPE, the column will default to the
problem can arise when using defaults with check constraints. Most DBMS products
do not perform semantic checking on constraints and defaults. The DBMS,
therefore, will allow the DBA to define defaults that contradict check
constraints. Furthermore, it is
possible to define check constraints that contradict one another. Care must be
taken to avoid creating this type of problem.
of contradictory constraints are depicted below:
(EMPNO > 10 AND EMPNO <9)
this case, no value is both greater than 10 and less than 9, so nothing could
ever be inserted.
(EMP_TYPE IN (‘TEMP’,
this case, the default value is not one of the permitted EMP_TYPE values
according to the defined constraint. No
defaults would ever be inserted.
(EMPNO > 10)
(EMPNO >= 11)
this case, the constraints are redundant. No
logical harm is done, but both constraints will be checked, thereby impacting
the performance of applications that modify the table in which the constraints
potential semantic problems could occur if the constraints contradicts a
referential integrity DELETE or UPDATE rule, if two constraints are defined on
the same column with contradictory conditions, or if the constraint requires
that the column be NULL, but the column is defined as NOT NULL.
care when using the LOAD utility on a table with check constraints defined to
it. By specifying the ENFORCE NO parameter you can permit DB2 to load data that
does not conform to the check constraints (as well as the referential
constraints). Although this eases the load process by enabling DB2 to bypass
constraint checking, it will place the table space into a check pending state.
You can run CHECK DATA to clear this state (or force the check pending off by
using START with the FORCE option or the REPAIR utility). If you do not run
CHECK DATA, constraint violations may occur causing dirty data.
constraints provide a very powerful vehicle for supporting business rules in the
database. They can be used to simulate relational domains. Because check
constraints are non-bypassable, they provide better data integrity than
corresponding logic programmed into the application. It is a wise course of
action to use check constraints in your database designs to support data
integrity, domains, and business rules in all of your relational database
From DB2 Update (Xephon) December 2001.
© 2002 Craig S. Mullins, All rights reserved.