Base tables that have a unique constraint but not the primary key

Query goal:

A common style is to declare in each base table one of the candidate keys as the primary key. All the other candidate keys would be alternate keys that will be enforce with the help of UNIQUE + NOT NULL constraints.

Query type:

Problem detection (Each row in the result could represent a flaw in the design)

Query reliability:

High (Few or no false-positive results)

Query license:

MIT License

Fixing suggestion:

Be consistent and declare in each base table one of the candidate keys as the primary key.

Data source:

INFORMATION_SCHEMA only

SQL query:

Click on query to copy it

SELECT A.table_schema, A.table_name 
FROM INFORMATION_SCHEMA.tables A
INNER JOIN INFORMATION_SCHEMA.schemata B
ON A.table_schema=B.schema_name
WHERE (A.table_schema, A.table_name) NOT IN 
(SELECT table_schema, table_name FROM INFORMATION_SCHEMA.table_constraints
WHERE constraint_type IN ('PRIMARY KEY'))
AND (A.table_schema, A.table_name) IN 
(SELECT table_schema, table_name FROM INFORMATION_SCHEMA.table_constraints
WHERE constraint_type IN ('UNIQUE'))
AND A.table_type='BASE TABLE'
AND (A.table_schema = 'public'
OR B.schema_owner<>'postgres')
ORDER BY A.table_schema, A.table_name;

Collections where the query belongs to

Collection name	Collection 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 .

Collection name

Collection 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 where the query belongs to

Category name	Category description
Inconsistencies	Queries of this catergory provide information about inconsistencies of solving the same problem in different places.
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).

Category name

Category description

Inconsistencies

Queries of this catergory provide information about inconsistencies of solving the same problem in different places.

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).

Reference materials for further reading

Reference
The corresponding code smell in case of cleaning code is "G11: Inconsistency". (Robert C. Martin, Clean Code)
Rule 4 in: Delplanque, J., Etien, A., Auverlot, O., Mens, T., Anquetil, N., Ducasse, S.: CodeCritics applied to database schema: Challenges and first results. In: 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 432-436. IEEE, (2017).

Reference

The corresponding code smell in case of cleaning code is "G11: Inconsistency". (Robert C. Martin, Clean Code)

Rule 4 in: Delplanque, J., Etien, A., Auverlot, O., Mens, T., Anquetil, N., Ducasse, S.: CodeCritics applied to database schema: Challenges and first results. In: 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 432-436. IEEE, (2017).