| 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 | 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 |
| Reliability | Medium Medium number of false-positive results |
| License | MIT (opens in new tab) |
| Fixing Suggestion | Make the column mandatory by declaring NOT NULL constraint to it. |
| Data Source | INFORMATION_SCHEMA+system catalog |
| SQL Query |
|
SQL statements that help generate fixes for the identified problem.
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 to Generate Fix | Description |
|---|---|
| Apply the NOT NUL L constraint directly to the column. |
Collections
This query belongs to the following collections:
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 .
| Name | 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
This query is classified under the following categories:
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.
| Name | 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. |