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.
#461. Do not leave out the referential constraints (based on column names) (2)
INFORMATION_SCHEMA+system catalog base tablesTry to find missing foreign key constraints. Find columns of base tables that are not a part of any primary key, unique, and foreign key constraint, but have a name that reffers to the possibility that these are used to record references to a user. Exclude columns that have the default value CURRENT_USER or SESSION_USER.
#462. Do not leave out the referential constraints (islands)
system catalog base tables onlyTry to find missing foreign key constraints. Find base tables that do not participate in any referential constraint (as the referenced table or as the referencing table). These tables are like "islands" in the database schema.
#463. Do not leave out the referential constraints (pairs of tables)
INFORMATION_SCHEMA+system catalog base tablesTry to find missing foreign key constraints. Find pairs of base table columns that have the similar name, perhaps the same type, and that are not associated through a foreign key relationship.
#464. Do not refer to the table schema in the references to columns
INFORMATION_SCHEMA+system catalog base tablesFind routines where in SELECT or UPDATE statements references to columns are prefixed with references to the table schema. Referring to schema in this context bloats the code.
#465. Do not specify a list of values in a table column definition
INFORMATION_SCHEMA+system catalog base tablesFind cases where the list of valid data values in the column is specified in the column definition (in addition to specifying the type of the column) by using, for instance, check constraints or enumerated types. The check constraint is either associated directly with a table or is associated with a domain.
#466. Do not use a generic attribute table
INFORMATION_SCHEMA onlyFind base tables that implement a highly generic database design (EAV design - Entiry-Attribute-Value design), according to which attribute values are recorded in a generic table that contains attribute-value pairs.
#467. Do not use approach that one size fits all (primary key columns)
INFORMATION_SCHEMA+system catalog base tablesFind base base tables have the simple primary key that contains the column with the (case insensitive) name id and an integer type. In addition, the primary key values are generated automatically by the system by using a sequence generator.
#468. Do not use approach that one size fits all (unique index columns)
INFORMATION_SCHEMA+system catalog base tablesFind base base tables have a simple unique index (not associated with a constraint) that contains the column with the (case insensitive) name id and an integer type. In addition, the key values are generated automatically by the system by using a sequence generator.
#469. Do not use dual-purpose foreign keys
INFORMATION_SCHEMA onlyFind cases where the same column of a base table T is used to record references to multiple base tables. In addition, one has to add additional column to T for holding metadata about the parent table, referenced by the current row.
#470. Do not use FLOAT Data Type
INFORMATION_SCHEMA onlyFind base table columns that have FLOAT, REAL, or DOUBLE PRECISION type. "The data types real and double precision are inexact, variable-precision numeric types. On all currently supported platforms, these types are implementations of IEEE Standard 754 for Binary Floating-Point Arithmetic (single and double precision, respectively), to the extent that the underlying processor, operating system, and compiler support it." (PostgreSQL documentation) Do not use the approximate numeric types FLOAT, REAL, and DOUBLE PRECISION in order to present fractional numeric data. Due to the use of the IEEE 754 standard the results of calculations with the values, which have one of these types, can be inexact because out of necessity some numbers must be rounded to a value, which is very close. "Comparing two floating-point values for equality might not always work as expected." (PostgreSQL documentation)
#471. Do not use the money data type
INFORMATION_SCHEMA onlyFind base table columns with the Money data type. Each value of the money type has associated currency sign that depends on server settings. It could be $. Moreover, using the values for arithmetic operations requires casts that makes the code more complicated.
#472. Double negatives in Boolean expressions
INFORMATION_SCHEMA+system catalog base tablesWrite code that is simple to understand and not confusing. A double negative is a grammatical construction occurring when two forms of negation are used in the same expression (https://en.wikipedia.org/wiki/Double_negative). Double negatives in Boolean expressions make it more difficult to understand and maintain the code.
#473. Double negatives in regular expressions
INFORMATION_SCHEMA+system catalog base tablesFing regular expression patterns that use [^\S] instead of \s or [^\D] instead of \d or [^\W] instead of \w.
#474. Do you really need fractional seconds?
INFORMATION_SCHEMA onlyFind default values that return current timestamp with the maximum number of fractional seconds (6).
#475. Duplicate CHECK constraints that are connected directly to a table
INFORMATION_SCHEMA onlyThe same table should not have multiple CHECK constraints with exactly the same Boolean expression. Do remember that the same task can be solved in SQL usually in multiple different ways. Thus, the exact copies are not the only possible duplication.
#476. Duplicate CHECK constraints that are connected to a domain
INFORMATION_SCHEMA onlyThe same domain should not have multiple CHECK constraints with exactly the same Boolean expression. Do remember that the same task can be solved in SQL usually in multiple different ways. Thus, the exact copies are not the only possible duplication.
#477. Duplicate comments
INFORMATION_SCHEMA+system catalog base tablesFind comments that have been registered with a COMMENT statement and that are associated with more than one object. It would probably mean that a comment is incorrect or missing.
#478. Duplicate DEFAULT values of base table columns
INFORMATION_SCHEMA onlyFind base table columns that have both default value determined through a domain and default value that is directly attached to the column. Do not duplicate specifications of default values to avoid confusion and surprises. If column and domain both have a default value, then in case of inserting data the default value that is associated directly with the column is used.
#479. Duplicate domains
INFORMATION_SCHEMA onlyFind domains that have the same properties (base type, character length, not null + check constraints, default value, collation). There should not be multiple domains that have the same properties. Do remember that the same task can be solved in SQL usually in multiple different ways. Therefore, the domains may have syntactically different check constraints that solve the same task. Thus, the exact copies are not the only possible duplication.
#480. Duplicate enumerated types
INFORMATION_SCHEMA+system catalog base tablesFind enumerated types with exactly the same values. There should not be multiple types that have the same values.
| # | Name | Goal | Type | Data source | Last update (sorted descending) | License | Actions |
|---|---|---|---|---|---|---|---|
| 461 | Do not leave out the referential constraints (based on column names) (2) | Try to find missing foreign key constraints. Find columns of base tables that are not a part of any primary key, unique, and foreign key constraint, but have a name that reffers to the possibility that these are used to record references to a user. Exclude columns that have the default value CURRENT_USER or SESSION_USER. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 462 | Do not leave out the referential constraints (islands) | Try to find missing foreign key constraints. Find base tables that do not participate in any referential constraint (as the referenced table or as the referencing table). These tables are like "islands" in the database schema. | Problem detection | system catalog base tables only | MIT (opens in new tab) | View (opens in new tab) | |
| 463 | Do not leave out the referential constraints (pairs of tables) | Try to find missing foreign key constraints. Find pairs of base table columns that have the similar name, perhaps the same type, and that are not associated through a foreign key relationship. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 464 | Do not refer to the table schema in the references to columns | Find routines where in SELECT or UPDATE statements references to columns are prefixed with references to the table schema. Referring to schema in this context bloats the code. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 465 | Do not specify a list of values in a table column definition | Find cases where the list of valid data values in the column is specified in the column definition (in addition to specifying the type of the column) by using, for instance, check constraints or enumerated types. The check constraint is either associated directly with a table or is associated with a domain. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 466 | Do not use a generic attribute table | Find base tables that implement a highly generic database design (EAV design - Entiry-Attribute-Value design), according to which attribute values are recorded in a generic table that contains attribute-value pairs. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 467 | Do not use approach that one size fits all (primary key columns) | Find base base tables have the simple primary key that contains the column with the (case insensitive) name id and an integer type. In addition, the primary key values are generated automatically by the system by using a sequence generator. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 468 | Do not use approach that one size fits all (unique index columns) | Find base base tables have a simple unique index (not associated with a constraint) that contains the column with the (case insensitive) name id and an integer type. In addition, the key values are generated automatically by the system by using a sequence generator. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 469 | Do not use dual-purpose foreign keys | Find cases where the same column of a base table T is used to record references to multiple base tables. In addition, one has to add additional column to T for holding metadata about the parent table, referenced by the current row. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 470 | Do not use FLOAT Data Type | Find base table columns that have FLOAT, REAL, or DOUBLE PRECISION type. "The data types real and double precision are inexact, variable-precision numeric types. On all currently supported platforms, these types are implementations of IEEE Standard 754 for Binary Floating-Point Arithmetic (single and double precision, respectively), to the extent that the underlying processor, operating system, and compiler support it." (PostgreSQL documentation) Do not use the approximate numeric types FLOAT, REAL, and DOUBLE PRECISION in order to present fractional numeric data. Due to the use of the IEEE 754 standard the results of calculations with the values, which have one of these types, can be inexact because out of necessity some numbers must be rounded to a value, which is very close. "Comparing two floating-point values for equality might not always work as expected." (PostgreSQL documentation) | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 471 | Do not use the money data type | Find base table columns with the Money data type. Each value of the money type has associated currency sign that depends on server settings. It could be $. Moreover, using the values for arithmetic operations requires casts that makes the code more complicated. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 472 | Double negatives in Boolean expressions | Write code that is simple to understand and not confusing. A double negative is a grammatical construction occurring when two forms of negation are used in the same expression (https://en.wikipedia.org/wiki/Double_negative). Double negatives in Boolean expressions make it more difficult to understand and maintain the code. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 473 | Double negatives in regular expressions | Fing regular expression patterns that use [^\S] instead of \s or [^\D] instead of \d or [^\W] instead of \w. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 474 | Do you really need fractional seconds? | Find default values that return current timestamp with the maximum number of fractional seconds (6). | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 475 | Duplicate CHECK constraints that are connected directly to a table | The same table should not have multiple CHECK constraints with exactly the same Boolean expression. Do remember that the same task can be solved in SQL usually in multiple different ways. Thus, the exact copies are not the only possible duplication. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 476 | Duplicate CHECK constraints that are connected to a domain | The same domain should not have multiple CHECK constraints with exactly the same Boolean expression. Do remember that the same task can be solved in SQL usually in multiple different ways. Thus, the exact copies are not the only possible duplication. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 477 | Duplicate comments | Find comments that have been registered with a COMMENT statement and that are associated with more than one object. It would probably mean that a comment is incorrect or missing. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) | |
| 478 | Duplicate DEFAULT values of base table columns | Find base table columns that have both default value determined through a domain and default value that is directly attached to the column. Do not duplicate specifications of default values to avoid confusion and surprises. If column and domain both have a default value, then in case of inserting data the default value that is associated directly with the column is used. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 479 | Duplicate domains | Find domains that have the same properties (base type, character length, not null + check constraints, default value, collation). There should not be multiple domains that have the same properties. Do remember that the same task can be solved in SQL usually in multiple different ways. Therefore, the domains may have syntactically different check constraints that solve the same task. Thus, the exact copies are not the only possible duplication. | Problem detection | INFORMATION_SCHEMA only | MIT (opens in new tab) | View (opens in new tab) | |
| 480 | Duplicate enumerated types | Find enumerated types with exactly the same values. There should not be multiple types that have the same values. | Problem detection | INFORMATION_SCHEMA+system catalog base tables | MIT (opens in new tab) | View (opens in new tab) |