Three-valued logic (non-Boolean columns)

Query goal:

Find non-foreign key columns of base tables that probably (based on the column name) contain values that represent truth values but do not have NOT NULL constraint. Use two-valued logic (TRUE, FALSE) instead of three-valued logic (TRUE, FALSE, UNKNOWN). Because NULL in a Boolean column means unknown make all the columns mandatory.

Notes about the query:

The query considers both column names in English and Estonian.

Query type:

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

Query reliability:

Medium (Medium number of false-positive results)

Query license:

MIT License

Fixing suggestion:

Make the column mandatory by declaring NOT NULL constraint to it.

Data source:

INFORMATION_SCHEMA+system catalog

SQL query:

Click on query to copy it

WITH fk_columns AS (select target_schema as table_schema, target_table as table_name, a.attname as column_name
from (select 
(select nspname from pg_namespace where oid=c.relnamespace) as target_schema,
c.relname as target_table, 
c.oid as target_table_oid,
unnest(o.conkey) AS target_col
from pg_constraint o inner join pg_class c on c.oid = o.conrelid
where o.contype = 'f') t
inner join pg_attribute a on t.target_col = a.attnum and t.target_table_oid = a.attrelid and a.attisdropped = false)

SELECT c.table_schema, c.table_name, c.column_name, c.data_type, c.character_maximum_length, 
coalesce(c.column_default, d.domain_default) AS column_default
FROM INFORMATION_SCHEMA.columns AS c LEFT JOIN INFORMATION_SCHEMA.domains AS d USING (domain_schema, domain_name)
WHERE column_name~*'^(is|has|on)_' 
AND (c.data_type<>'boolean') 
AND c.is_nullable='YES'
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 NOT EXISTS (SELECT *
FROM fk_columns
WHERE fk_columns.table_schema=c.table_schema
AND fk_columns.table_name=c.table_name
AND fk_columns.column_name=c.column_name)
ORDER BY c.table_schema, c.table_name, c.column_name;

SQL statements for generating SQL statements that help us to fix the problem

SQL query	Description
SELECT format('ALTER TABLE %1$I.%2$I ALTER COLUMN %3$I SET NOT NULL', A.table_schema, A.table_name , A.column_name) AS statements FROM information_schema.columns A INNER JOIN information_schema.tables T ON A.table_schema = T.table_schema AND A.table_name = T.table_name INNER JOIN information_schema.schemata S ON A.table_schema=S.schema_name WHERE A.data_type<>'boolean' AND column_name~*'^(is\|has\|on)_' AND is_nullable='YES' AND T.table_type='BASE TABLE' AND (A.table_schema = 'public' OR S.schema_owner<>'postgres') ORDER BY A.table_schema, A.table_name, A.column_name;	Apply the NOT NUL L constraint directly to the column.

SQL query

Description

SELECT format('ALTER TABLE %1$I.%2$I ALTER COLUMN %3$I SET NOT NULL', A.table_schema, A.table_name , A.column_name) AS statements
FROM information_schema.columns A
INNER JOIN information_schema.tables T
ON A.table_schema = T.table_schema
AND A.table_name = T.table_name
INNER JOIN information_schema.schemata S
ON A.table_schema=S.schema_name
WHERE A.data_type<>'boolean' 
AND column_name~*'^(is|has|on)_' 
AND is_nullable='YES' 
AND T.table_type='BASE TABLE'
AND (A.table_schema = 'public'
OR S.schema_owner<>'postgres')
ORDER BY A.table_schema, A.table_name, A.column_name;

Apply the NOT NUL L constraint directly to the column.

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
Boolean data	Queries of this category provide information about truth-values data that is kept in the database.
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.
Missing data	Queries of this category provide information about missing data (NULLs) in a database.
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.

Category name

Category description

Boolean data

Queries of this category provide information about truth-values data that is kept in the database.

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.

Missing data

Queries of this category provide information about missing data (NULLs) in a database.

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.