This statement creates a unique constraint, but, because the constraint is disabled, a unique index is not required. This approach can be advantageous for many data warehousing environments because the constraint now ensures uniqueness without the cost of a unique index. Because this constraint is disabled, no DML statements that modify the unique column are permitted against the sales table. You can use one of two strategies for modifying this table in the presence of a constraint:.
Use DDL to add data to this table such as exchanging partitions. See the example in Chapter 15, " Maintaining the Data Warehouse". Before modifying this table, drop the constraint. Then, make all necessary data modifications. Finally, re-create the disabled constraint. Re-creating the constraint is more efficient than re-creating an enabled constraint. However, this approach does not guarantee that data added to the sales table while the constraint has been dropped is unique.
A sample constraint might be:.
The tables contain data that currently disobeys the constraint, but the data warehouse administrator wishes to create a constraint for future enforcement. Suppose that the data warehouse loaded new data into the fact tables every day, but refreshed the dimension tables only on the weekend.
The ETL process commonly verifies that certain constraints are true. For example, it can validate all of the foreign keys in the data coming into the fact table. This means that you can trust it to provide clean data, instead of implementing constraints in the data warehouse.
You create a RELY constraint as follows:. This statement assumes that the primary key is in the RELY state. RELY constraints, even though they are not used for data validation, can:. Enable more sophisticated query rewrites for materialized views. See Chapter 18, " Query Rewrite" for further details. Enable other data warehousing tools to retrieve information regarding constraints directly from the Oracle data dictionary.
Because the constraint is not being validated, no data processing is necessary to create it. All constraints can be validated in parallel. When validating constraints on very large tables, parallelism is often necessary to meet performance goals. The degree of parallelism for a given constraint operation is determined by the default degree of parallelism of the underlying table. You can create and maintain constraints before you partition the data.
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Later chapters discuss the significance of partitioning for data warehousing. Partitioning can improve constraint management just as it does to management of many other operations. You can create constraints on views. The only type of constraint supported on a view is a RELY constraint. This type of constraint is useful when queries typically access views instead of base tables, and the database administrator thus needs to define the data relationships between views rather than tables.
View constraints are particularly useful in OLAP environments, where they may enable more sophisticated rewrites for materialized views.
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The most common types of constraints include: Data cleanliness Constraints verify that the data in the data warehouse conforms to a basic level of data consistency and correctness, preventing the introduction of dirty data. Chapter 11, " Overview of Extraction, Transformation, and Loading". Overview of Constraint States To understand how bes t to use constraints in a data warehouse, you should first understand the basic purposes of constraints.
Some of these purposes are: Belief In some cases, you will know that the conditions for a given constraint are true, so you do not need to validate or enforce the constraint. Note that the RELY state only affects constraints that have not been validated. Typical Data Warehouse Integrity Constraints This section assumes that you are familiar with the typical use of constraints. The topics discussed are: One way to create the constraint is as follows: What are the types of constraints? Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.
Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center , please edit the question. They define certain properties that data in a database must comply with. They can apply to a column, a whole table, more than one table or an entire schema.
A reliable database system ensures that constraints hold at all times except possibly inside a transaction, for so called deferred constraints. Data Integrity refers to the validity of data. Are your data valid? Are your data representing what you have designed them to? What weird questions I ask you might think, but sadly enough all too often, databases are filled with garbage data, invalid references to rows in other tables, that are long gone All this garbage is not alone prone to reduce your performance, but is also a time-bomb under your application logic that eventually will retreive data that it is not designed to understand.
sql - What are database constraints? - Stack Overflow
Constraints are rules you create at design-time that protect your data from becoming corrupt. It is essential for the long time survival of your heart child of a database solution. Without constraints your solution will definitely decay with time and heavy usage. You have to acknowledge that designing your database design is only the birth of your solution.
Here after it must live for hopefully a long time, and endure all kinds of strange behaviour by its end-users ie. But this design-phase in development is crucial for the long-time success of your solution! Respect it, and pay it the time and attention it requires. A wise man once said: And this is what constraints do. It is rules that keep the data in your database as valid as possible. As I've hinted here, it takes some thorough considerations to construct the best and most defensive constraint approach for your database design. You first need to know the possibilities and limitations of the different constraint types above.
Further reading could include:. Foreign key constraint - w3schools. Constraints are nothing but the rules on the data. What data is valid and what is invalid can be defined using constraints. So, that integrity of data can be maintained.
Following are the widely used constraints:. Constraints dictate what values are valid for data in the database. Constraints can be used to enforce specific properties of data. A simple example is to limit an int column to values . This introduction looks good. Checks that all values of a given field are unique across the table. This is X -axis constraint records. Checks that a certain condition holds for the expression over the fields of the same record.
This is Y -axis constraint fields. Checks that a field's value is found among the values of a field in another table. This is Z -axis constraint tables. A database is the computerized logical representation of a conceptual or business model, consisting of a set of informal business rules. These rules are the user-understood meaning of the data.
SQL Create Constraints
Because computers comprehend only formal representations, business rules cannot be represented directly in a database. They must be mapped to a formal representation, a logical model, which consists of a set of integrity constraints. These constraints — the database schema — are the logical representation in the database of the business rules and, therefore, are the DBMS-understood meaning of the data.