This query identifies semantic inconsistencies across the database schema by finding base table columns that share the same identifier (name) but are defined with differing data types. According to standard data modeling principles, a shared attribute name implies a shared domain concept (e.g., status_code should consistently be an SMALLINT or a CHAR). Discrepancies in data types for homonymous columns (e.g., is_active being BOOLEAN in one table and SMALLINT in another) hinder interoperability, complicate join logic, and confuse developers.
Notes
In case of the string_agg function, the line break (br) tag is used as a part of the separator for the better readability in case the query result is displayed in a web browser.
Type
Problem detection (Each row in the result could represent a flaw in the design)
Change the name of the column or the type of the column to ensure consistency.
Data Source
INFORMATION_SCHEMA only
SQL Query
WITH data_types AS (SELECT table_schema, table_name, column_name, data_type
FROM INFORMATION_SCHEMA.columns
WHERE (table_schema, table_name) IN (SELECT table_schema, table_name
FROM INFORMATION_SCHEMA.tables WHERE table_type='BASE TABLE') AND
table_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL))
SELECT column_name, Count(*) AS number_of_columns, Count(DISTINCT data_type) AS number_of_different_types,
string_agg(table_schema ||'.'|| table_name || ' ' || Upper(data_type),'; ' ORDER BY data_type, table_schema, table_name) AS types
FROM data_types AS dt
GROUP BY column_name
HAVING Count(DISTINCT data_type)>1
ORDER BY Count(DISTINCT data_type) DESC, Count(*) DESC, column_name;
Collections
This query belongs to the following collections:
Name
Description
Find problems about base tables
A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. 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:
Name
Description
Comfortability of data management
Queries of this category provide information about the means that have been used to make the use or management of database more comfortable and thus, more efficient.
Data types
Queries of this category provide information about the data types and their usage.
Inconsistencies
Queries of this catergory provide information about inconsistencies of solving the same problem in different places.
Naming
Queries of this category provide information about the style of naming.
Further reading and related materials:
Reference
The corresponding code smell in case of cleaning code is "G11: Inconsistency". (Robert C. Martin, Clean Code)
Smell "Overloaded attribute names": 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).