PostgreSQL Query Catalog

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Filter Queries

Found 1053 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
481 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 2025-11-07 10:11 MIT License View
482 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 2025-11-07 10:11 MIT License View
483 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 2025-11-07 10:11 MIT License View
484 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 2025-11-07 10:11 MIT License View
485 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 2025-11-07 10:11 MIT License View
486 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 2025-11-07 10:11 MIT License View
487 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 2025-11-07 10:11 MIT License View
488 Meaningless terms in routines Find routines that subquery contains terms "foo", "bar", "foobar", or "baz". Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-07 10:11 MIT License View
489 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 2025-11-07 10:11 MIT License View
490 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 2025-11-07 10:11 MIT License View
491 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 2025-11-07 10:11 MIT License View
492 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 2025-11-07 10:11 MIT License View
493 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 2025-11-07 10:11 MIT License View
494 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 2025-11-07 10:11 MIT License View
495 Multi-column CHECK constraints with unnecessary NULL checks This query identifies multiple-column CHECK constraints that explicitly check for NULL values. In general, constraint definitions should be kept as simple as possible. Because a NULL value causes a logical condition to evaluate to UNKNOWN—and CHECK constraints inherently allow rows that evaluate to either TRUE or UNKNOWN—there is usually no need to explicitly allow missing values. For instance, instead of writing CHECK (last_update_time IS NULL OR last_update_time >= creation_time), the constraint should simply be written as CHECK (last_update_time >= creation_time). However, a valid exception exists for implication rules (P ⇒ Q), which can be rewritten as NOT (P) OR Q. For example, the constraint CHECK (NOT (product IS NOT NULL) OR service IS NULL) properly enforces the rule that if a product is present, the service must be NULL. Such logical constructs are entirely appropriate. Problem detection INFORMATION_SCHEMA+system catalog base tables 2026-06-02 14:29 MIT License View
496 Multiple deletes from the same table in a routine Code should be as compact as possible and system should make as little work as necessary in order to solve a task. Thus, instead of deleting different rows of the same table with different DELETE statements one should try to do it with one statement. The query excludes routines where IF statement is used. Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-07 10:11 MIT License View
497 Multiple RETURNING clauses in a SQL function Find SQL functions that have multiple statements with the RETURNING clause. Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-07 10:11 MIT License View
498 Multiple selects from the same table in a routine Code should be as compact as possible and system should make as little work as necessary in order to solve a task. Thus, instead of selecting different fields of the same row with different SELECT INTO statements one should try to do it with one statement. Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-07 10:11 MIT License View
499 Multiple simple keys with integer values This query identifies base tables with a potentially redundant key structure, specifically those having more than one PRIMARY KEY or UNIQUE constraint defined on a single integer-type column. This pattern may suggest the presence of multiple surrogate keys for the same entity, which can indicate overcomplicated data model. A single entity should typically have only one system-generated identifier to maintain schema clarity, simplify join logic, and avoid redundancy. The presence of multiple such keys warrants a review to determine if one is superfluous. Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-15 11:35 MIT License View
500 Multiple updates of the same table in a routine Code should be as compact as possible and system should make as little work as necessary in order to solve a task. Thus, instead of updating different fields of the same table with different UPDATE statements one should try to do it with one statement. Problem detection INFORMATION_SCHEMA+system catalog base tables 2025-11-07 10:11 MIT License View