This query identifies a semantic mismatch in data type selection for columns intended to store measurement data. It targets columns whose names imply a quantitative measurement (e.g., "length", "weight", "count", excluding boolean prefixes like "is_") but are not defined with a numeric data type (INTEGER, NUMERIC, etc.). Storing measurements as text (VARCHAR) prevents mathematical operations, aggregation, and proper sorting, and is considered a design flaw.
Notes
The query considers both column names in English and Estonian.
Type
Problem detection (Each row in the result could represent a flaw in the design)
Choose data types carefully. Be as precise as possible. In PostgreSQL one should use SMALLINT, INTEGER, BIGINT, OR NUMERIC (aka DECIMAL) type in case of storing length, height, width, depth, and weight data. Change the data type of the column.
Data Source
INFORMATION_SCHEMA only
SQL Query
SELECT table_schema, table_name, column_name, data_type
FROM INFORMATION_SCHEMA.columns
WHERE column_name~*'(?'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL)
ORDER BY table_schema, table_name, ordinal_position;
Collections
This query belongs to the following collections:
Name
Description
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
Data types
Queries of this category provide information about the data types and their usage.
Result quality depends on names
Queries of this category use names (for instance, column names) to try to guess the meaning of a database object. Thus, the goodness of names determines the number of false positive and false negative results.
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).