| Query goal: | Make sure that in case of using the type DECIMAL/NUMERIC as the type of a base table column the precision (the permitted number of digits in the number) is not too small. For instance, the biggest value in the type NUMERIC(1,1) is 0.9. |
| 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 |
| Data source: | INFORMATION_SCHEMA only |
| SQL query: | Click on query to copy it
SELECT table_schema, table_name, column_name, data_type, numeric_precision, numeric_scale FROM INFORMATION_SCHEMA.columns WHERE data_type ='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=numeric_scale ORDER BY table_schema, table_name, ordinal_position; |
| Collection name | Collection 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 . |
| Category name | Category description |
|---|---|
| Data types | Queries of this category provide information about the data types and their usage. |
| 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). |