Query goal: | Find mandatory (NOT NULL) base table columns that name, column type, and field size refers to the possibility that these are used to register large textual values like comments, descriptions, and explanations. |
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: | Low (Many false-positive results) |
Query license: | MIT License |
Fixing suggestion: | Be precise. Are you sure you have such value for each row. Perhaps, the NOT NULL constraint should be dropped. |
Data source: | INFORMATION_SCHEMA+system catalog |
SQL query: | Click on query to copy it
WITH domains AS (SELECT (SELECT nspname FROM pg_namespace WHERE pg_namespace.oid=pg_type.typnamespace) AS domain_schema, typname AS domain_name, typdefault AS domain_default, CASE WHEN typnotnull=TRUE THEN 'NO' ELSE 'YES' END AS is_nullable FROM pg_type WHERE typtype='d') 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 domains AS d USING (domain_schema, domain_name) WHERE column_name~*'(komment|kirjeldus|comment|descr|selgitus)' AND column_name!~*'_(id|nr|kood|code|aeg|time|kp|date)$' AND ((c.data_type='text') OR (c.data_type='character varying' AND c.character_maximum_length IS NULL) OR (c.data_type='character varying' AND c.character_maximum_length>=1000)) AND (d.is_nullable='NO' OR c.is_nullable='NO') 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) ORDER BY table_schema, table_name, ordinal_position; |
Category name | Category description |
---|---|
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. |
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). |