| Goal | Find how many tables with a certain range of the number of columns there are in the database. |
|---|---|
| Type | Sofware measure Numeric values (software measures) about the database |
| License | MIT (opens in new tab) |
| Data Source | INFORMATION_SCHEMA+system catalog |
| SQL Query |
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Collections
This query belongs to the following collections:
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 by overview
Queries that results point to different aspects of database that might have problems. A human reviewer has to decide based on the results as to whether there are problems or not .
Find quick numeric overview of the database
Queries that return numeric values showing mostly the number of different types of database objects in the database
| 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 by overview | Queries that results point to different aspects of database that might have problems. A human reviewer has to decide based on the results as to whether there are problems or not . |
| Find quick numeric overview of the database | Queries that return numeric values showing mostly the number of different types of database objects in the database |
Categories
This query is classified under the following categories:
Structure of base tables
Queries of this category provide information about the structuring of base tables at the database conceptual level
| Name | Description |
|---|---|
| Structure of base tables | Queries of this category provide information about the structuring of base tables at the database conceptual level |
Further reading and related materials:
| Reference |
|---|
| Factor, P.: SQL Code Smells. Redgate, http://assets.red-gate.com/community/books/sql-code-smells.pdf, last accessed 2019/12/29 (Creating tables as ‘God Objects’) |
| Dintyala, P., Narechania, A., Arulraj, J.: SQLCheck: automated detection and diagnosis of SQL anti-patterns. In: 2020 ACM SIGMOD International Conference on Management of Data, pp. 2331–2345. (2020). https://doi.org/10.1145/3318464.3389754 (God Table) |
| Sharma, T., Fragkoulis, M., Rizou, S., Bruntink, M. and Spinellis, D.: Smelly relations: measuring and understanding database schema quality. In: 40th International Conference on Software Engineering: Software Engineering in Practice, pp. 55–64. ACM, (2018). https://doi.org/10.1145/3183519.3183529 (God table) |
| Blaha, M.R., Premerlani, W.J.: Observed idiosyncracies of relational database designs. In: 2nd Working Conference on Reverse Engineering, pp. 116–125. IEEE, (1995). https://doi.org/10.1109/WCRE.1995.514700 (Multi-class tables) |
| Delplanque, J., Etien, A., Auverlot, O., Mens, T., Anquetil, N., Ducasse, S.: CodeCritics applied to database schema: Challenges and first results. In: 24th International Conference on Software Analysis, Evolution and Reengineering, pp. 432–436. IEEE, (2017). https://doi.org/10.1109/SANER.2017.7884648 (Too many columns in a table) |