Find base table columns that have the DECIMAL/NUMERIC type, but do not have precision and scale specified. "Specifying: NUMERIC without any precision or scale creates a column in which numeric values of any precision and scale can be stored, up to the implementation limit on precision. A column of this kind will not coerce input values to any particular scale, whereas numeric columns with a declared scale will coerce input values to that scale."
Type
Problem detection (Each row in the result could represent a flaw in the design)
Specify precision and scale in the type declaration.
Data Source
INFORMATION_SCHEMA only
SQL Query
SELECT table_schema, table_name, column_name, data_type, numeric_precision, numeric_scale
FROM INFORMATION_SCHEMA.columns
WHERE data_type IN ('decimal', 'numeric') AND
(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) AND
(numeric_precision IS NULL AND numeric_scale IS NULL)
ORDER BY table_schema, table_name, ordinal_position;
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
Field size
Queries of this category provide information about the maximum size of values that can be recorded in column fields
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).