NameSET -- change a run-time parameter Synopsis SET [ SESSION | LOCAL ] configuration_parameter { TO | = } { value | 'value' | DEFAULT } SET [ SESSION | LOCAL ] TIME ZONE { timezone | LOCAL | DEFAULT } Description The SET command changes run-time configuration parameters. Many of the run-time parameters listed in Chapter 19 can be changed on-the-fly with SET. (But some require superuser privileges to change, and others cannot be changed after server or session start.) SET only affects

In an index scan, the index access method is responsible for regurgitating the TIDs of all the tuples it has been told about that match the scan keys. The access method is not involved in actually fetching those tuples from the index's parent table, nor in determining whether they pass the scan's time qualification test or other conditions. A scan key is the internal representation of a WHERE clause of the form index_key operator constant, where the index key is one of the columns of the index

The catalog pg_shdepend records the dependency relationships between database objects and shared objects, such as roles. This information allows PostgreSQL to ensure that those objects are unreferenced before attempting to delete them. See also pg_depend, which performs a similar function for dependencies involving objects within a single database. Unlike most system catalogs, pg_shdepend is shared across all databases of a cluster: there is only one copy of pg_shdepend per cluster, not one per

Each index access method is described by a row in the pg_am system catalog. The pg_am entry specifies a name and a handler function for the access method. These entries can be created and deleted using the CREATE ACCESS METHOD and DROP ACCESS METHOD SQL commands. An index access method handler function must be declared to accept a single argument of type internal and to return the pseudo-type index_am_handler. The argument is a dummy value that simply serves to prevent handler functions from be

PostgreSQL databases require periodic maintenance known as vacuuming. For many installations, it is sufficient to let vacuuming be performed by the autovacuum daemon, which is described in Section 24.1.6. You might need to adjust the autovacuuming parameters described there to obtain best results for your situation. Some database administrators will want to supplement or replace the daemon's activities with manually-managed VACUUM commands, which typically are executed according to a schedule b

The parser stage consists of two parts: The parser defined in gram.y and scan.l is built using the Unix tools bison and flex. The transformation process does modifications and augmentations to the data structures returned by the parser. 49.3.1. Parser The parser has to check the query string (which arrives as plain text) for valid syntax. If the syntax is correct a parse tree is built up and handed back; otherwise an error is returned. The parser and lexer are implemented using the well-

SP-GiST offers an interface with a high level of abstraction, requiring the access method developer to implement only methods specific to a given data type. The SP-GiST core is responsible for efficient disk mapping and searching the tree structure. It also takes care of concurrency and logging considerations. Leaf tuples of an SP-GiST tree contain values of the same data type as the indexed column. Leaf tuples at the root level will always contain the original indexed data value, but leaf tupl

The catalog pg_constraint stores check, primary key, unique, foreign key, and exclusion constraints on tables. (Column constraints are not treated specially. Every column constraint is equivalent to some table constraint.) Not-null constraints are represented in the pg_attribute catalog, not here. User-defined constraint triggers (created with CREATE CONSTRAINT TRIGGER) also give rise to an entry in this table. Check constraints on domains are stored here, too. Table 50-13. pg_constraint Colu

This module implements a data type seg for representing line segments, or floating point intervals. seg can represent uncertainty in the interval endpoints, making it especially useful for representing laboratory measurements. F.34.1. Rationale The geometry of measurements is usually more complex than that of a point in a numeric continuum. A measurement is usually a segment of that continuum with somewhat fuzzy limits. The measurements come out as intervals because of uncertainty and randomne

The PostgreSQL formatting functions provide a powerful set of tools for converting various data types (date/time, integer, floating point, numeric) to formatted strings and for converting from formatted strings to specific data types. Table 9-23 lists them. These functions all follow a common calling convention: the first argument is the value to be formatted and the second argument is a template that defines the output or input format. Table 9-23. Formatting Functions Function Return Type De