PostgreSQL Query Catalog

Project on GitHub
Filter Queries

Found 997 queries.

  • All the queries about database objects contain a subcondition to exclude from the result information about the system catalog.
  • Although the statements use SQL constructs (common table expressions; NOT in subqueries) that could cause performance problems in case of large datasets it shouldn't be a problem in case of relatively small amount of data, which is in the system catalog of a database.
  • Statistics about the catalog content and project home in GitHub that has additional information.

# Name ▲ Goal Type Data source Last update License
461 LIKE with a regular expression pattern Find expressions that use LIKE (including ILIKE) predicate with a regular expression patterns. In a LIKE pattern one can use only _ and % metasymbols to construct a pattern. Problem detection INFORMATION_SCHEMA+system catalog base tables 2023-10-21 10:38 MIT License View
462 LIKE without a pattern with % or _ Find expressions that use LIKE predicate witout a pattern that contains at least one % or _ sign. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-02-25 17:30 MIT License View
463 Logical size of a schema The schema size is the sum of the sizes of all tables in the schema. Sofware measure INFORMATION_SCHEMA+system catalog base tables 2022-10-21 16:18 MIT License View
464 Logical size of a table The table size is the sum of the total size of the simple columns and the total size of the complex columns in the table. In case of SQL databases large base tables in terms of number of columns could be a side effect of the problems with cloned columns or multiple columns for the same attribute. A base table with a low normalization level, which is meant to hold data that corresponds to multiple entity types has typically also relatively large number of columns compared with other base tables. Thus, the normalization level of base tables with a large number of columns should be checked as well. Sofware measure INFORMATION_SCHEMA+system catalog base tables 2022-10-21 16:17 MIT License View
465 Mandatory columns for holding large textual values (comments, descriptions, etc.) 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. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-02-25 17:29 MIT License View
466 Mandatory non-primary key columns Find mandatory non-primary key columns, i.e., the columns that have NOT NULL constraint. General INFORMATION_SCHEMA+system catalog base tables 2020-12-05 19:35 MIT License View
467 Many-to-many relationship types that do not have additional attributes Find base tables that implement many-to-many relationship types that do not permit repeating relationships. More specifically find tables that have two or more foreign keys and all the columns of the table are either foreign key columns or a surrogate key column. It could be that during the system analysis a mistake has been made and some attributes of the entity type that represents the relationship type have not been discovered. Problem detection INFORMATION_SCHEMA+system catalog base tables 2022-01-21 10:48 MIT License View
468 Many-to-many relationship types that do not permit repeating relationships and do not have additional attributes Find base tables that implement many-to-many relationship types that do not permit repeating relationships. More specifically find tables that have two or more foreign keys and all the columns of the table belong to a foreign key. In addition, all the table columns must be covered by a primary key or unique constraint. It could be that during the system analysis a mistake has been made and some attributes of the entity type that represents the relationship type have not been discovered. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-03-28 12:04 MIT License View
469 Meaningless terms in derived tables Find derived tables that subquery contains terms "foo", "bar", "foobar", or "baz". Problem detection INFORMATION_SCHEMA+system catalog base tables 2023-01-06 14:08 MIT License View
470 Meaningless terms in names Find names of database objects that contain terms "foo", "bar", "foobar", or "baz". Problem detection INFORMATION_SCHEMA+system catalog base tables 2024-12-21 16:36 MIT License View
471 Meaningless terms in routines Find routines that subquery contains terms "foo", "bar", "foobar", or "baz". Problem detection INFORMATION_SCHEMA+system catalog base tables 2023-01-06 14:09 MIT License View
472 Median and average number of subcomponents in the names of database objects "Names in software are 90 percent of what make software readable. You need to take the time to choose them wisely and keep them relevant. Names are too important to treat carelessly. Names should not cause confusion." (Robert C. Martin, Clean Code) Names should be expressive. Find the median and average (arithmetic mean) number of subcomponents in the names of user-defined database objects. The values could be used to compare different databases. Sofware measure INFORMATION_SCHEMA+system catalog base tables 2024-12-21 16:47 MIT License View
473 Median and average of the length of names of database objects "Names in software are 90 percent of what make software readable. You need to take the time to choose them wisely and keep them relevant. Names are too important to treat carelessly. Names should not cause confusion." (Robert C. Martin, Clean Code) Names should be expressive. Find the median length and average (arithmetic mean) length of the names (identifiers) of user-defined database objects. The values could be used to compare different databases. Sofware measure INFORMATION_SCHEMA+system catalog base tables 2024-12-21 17:25 MIT License View
474 Median and average of the length of names of database objects by the object type "Names in software are 90 percent of what make software readable. You need to take the time to choose them wisely and keep them relevant. Names are too important to treat carelessly. Names should not cause confusion." (Robert C. Martin, Clean Code) Names should be expressive. Find the median length and average (arithmetic mean) length of the names (identifiers) of user-defined database objects by the object type. The values could be used to compare different databases. Sofware measure INFORMATION_SCHEMA+system catalog base tables 2024-12-21 16:37 MIT License View
475 Middle-man Find a routine that's only task is to invoke another routine. If a routine performs only one action, delegating work to another routine, why does it exist at all? Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-11-05 12:48 MIT License View
476 Minimum tuple length required before trying to move long column values into TOAST tables has been changed Find base tables in case of which toast_tuple_target storage parameter value is not the default value (2040). "Changing this value may not be useful for very short or very long rows. Note that the default setting is often close to optimal, and it is possible that setting this parameter could have negative effects in some cases. " Make sure that the parameter has an optimal value. General INFORMATION_SCHEMA+system catalog base tables 2020-11-06 14:51 MIT License View
477 Missing USAGE privileges on schema If a user has a privilege to use a schema object, then the user must also have the usage privilege on the schema that contains the object. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-11-21 12:06 MIT License View
478 Mixing Concat and || Find cases where different means are used to concatenate text within the same object. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-12-03 14:36 MIT License View
479 Mixing Concat and Coalesce Find cases where different means are used to deal with NULLs in case of concatenating texsts. Problem detection INFORMATION_SCHEMA+system catalog base tables 2021-12-08 14:25 MIT License View
480 Mixing different mechanisms to generate surrogate values Use the same mechanism of generating surrogate key values throughout the database. The use of SERIAL notation/explicitly creating a sequence generator and declaration of a column as an identity column will cause the creation of an external and internal sequence generator, respectively. Nevertheless, one should try to stick with using one of the mechanisms in order to cause less confusion. "If you do something a certain way, do all similar things in the same way." (Robert C. Martin, Clean Code) Problem detection INFORMATION_SCHEMA only 2021-03-08 00:42 MIT License View