| Goal | This query identifies tables that use a single-column surrogate primary key but lack any other UNIQUE constraints or unique indexes. The absence of additional unique constraints suggests that the natural business key has not been enforced, creating a risk of data duplication that violates business rules. Tables consisting of only a single column are excluded from this check. |
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| Notes | This query is designed to be comprehensive, ensuring accuracy by accounting for various PostgreSQL features. It correctly identifies surrogate keys by recognizing sequences created both externally and internally (via an IDENTITY column), and can trace this association even when it is defined through a domain. Furthermore, it understands that uniqueness can be enforced through multiple mechanisms, checking not only for standard UNIQUE constraints but also for PostgreSQL-specific EXCLUDE constraints and unique indexes. |
| Type | Problem detection (Each row in the result could represent a flaw in the design) |
| Reliability | High (Few or no false-positive results) |
| License | MIT (opens in new tab) |
| Fixing Suggestion | Find and enforce natural keys, i.e., keys that values have a meaning to database end users and are used to refer to the entities outside the software system. |
| Data Source | INFORMATION_SCHEMA+system catalog |
| SQL Query |
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Collections
This query belongs to the following collections:
Find problems about integrity constraints
A selection of queries that return information about the state of integrity constraints in the datadabase. Contains all the types of queries - problem detection, software measure, and general overview
Find problems automatically
Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .
| Name | Description |
|---|---|
| Find problems about integrity constraints | A selection of queries that return information about the state of integrity constraints in the datadabase. Contains all the types of queries - problem detection, software measure, and general overview |
| Find problems automatically | Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not . |
Categories
This query is classified under the following categories:
Default value
Queries of this catergory provide information about the use of default values.
Sequence generators
Queries of this category provide information about sequence generators and their usage.
Uniqueness
Queries of this category provide information about uniqueness constraints (PRIMARY KEY, UNIQUE, EXCLUDE) as well as unique indexes.
Validity and completeness
Queries of this category provide information about whether database design represents the world (domain) correctly (validity) and whether database design captures all the information about the world (domain) that is correct and relevant (completeness).
| Name | Description |
|---|---|
| Default value | Queries of this catergory provide information about the use of default values. |
| Sequence generators | Queries of this category provide information about sequence generators and their usage. |
| Uniqueness | Queries of this category provide information about uniqueness constraints (PRIMARY KEY, UNIQUE, EXCLUDE) as well as unique indexes. |
| Validity and completeness | Queries of this category provide information about whether database design represents the world (domain) correctly (validity) and whether database design captures all the information about the world (domain) that is correct and relevant (completeness). |
Further reading and related materials:
| Reference |
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| Smell "Superfluous key": Sharma, T., Fragkoulis, M., Rizou, S., Bruntink, M. and Spinellis, D.: Smelly relations: measuring and understanding database schema quality. In: Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice, pp. 55-64. ACM, (2018). |