Chapter 6. Type Conversion

Table of Contents
Overview
Operators
Functions
Query Targets
UNION Queries

SQL queries can, intentionally or not, require mixing of different data types in the same expression. Postgres has extensive facilities for evaluating mixed-type expressions.

In many cases a user will not need to understand the details of the type conversion mechanism. However, the implicit conversions done by Postgres can affect the apparent results of a query, and these results can be tailored by a user or programmer using explicit type coercion.

This chapter introduces the Postgres type conversion mechanisms and conventions. Refer to the relevant sections in the User's Guide and Programmer's Guide for more information on specific data types and allowed functions and operators.

The Programmer's Guide has more details on the exact algorithms used for implicit type conversion and coercion.

Overview

SQL is a strongly typed language. That is, every data item has an associated data type which determines its behavior and allowed usage. Postgres has an extensible type system which is much more general and flexible than other RDBMS implementations. Hence, most type conversion behavior in Postgres should be governed by general rules rather than by ad-hoc heuristics to allow mixed-type expressions to be meaningful, even with user-defined types.

The Postgres scanner/parser decodes lexical elements into only five fundamental categories: integers, floats, strings, names, and keywords. Most extended types are first tokenized into strings. The SQL language definition allows specifying type names with strings, and this mechanism is used by Postgres to start the parser down the correct path. For example, the query

tgl=> SELECT text 'Origin' AS "Label", point '(0,0)' AS "Value";
 Label  | Value
--------+-------
 Origin | (0,0)
(1 row)
has two strings, of type text and point. If a type is not specified, then the placeholder type unknown is assigned initially, to be resolved in later stages as described below.

There are four fundamental SQL constructs requiring distinct type conversion rules in the Postgres parser:

Operators

Postgres allows expressions with left- and right-unary (one argument) operators, as well as binary (two argument) operators.

Function calls

Much of the Postgres type system is built around a rich set of functions. Function calls have one or more arguments which, for any specific query, must be matched to the functions available in the system catalog.

Query targets

SQL INSERT statements place the results of query into a table. The expressions in the query must be matched up with, and perhaps converted to, the target columns of the insert.

UNION queries

Since all select results from a UNION SELECT statement must appear in a single set of columns, the types of each SELECT clause must be matched up and converted to a uniform set.

Many of the general type conversion rules use simple conventions built on the Postgres function and operator system tables. There are some heuristics included in the conversion rules to better support conventions for the SQL92 standard native types such as smallint, integer, and float.

The Postgres parser uses the convention that all type conversion functions take a single argument of the source type and are named with the same name as the target type. Any function meeting this criteria is considered to be a valid conversion function, and may be used by the parser as such. This simple assumption gives the parser the power to explore type conversion possibilities without hardcoding, allowing extended user-defined types to use these same features transparently.

An additional heuristic is provided in the parser to allow better guesses at proper behavior for SQL standard types. There are five categories of types defined: boolean, string, numeric, geometric, and user-defined. Each category, with the exception of user-defined, has a "preferred type" which is used to resolve ambiguities in candidates. Each "user-defined" type is its own "preferred type", so ambiguous expressions (those with multiple candidate parsing solutions) with only one user-defined type can resolve to a single best choice, while those with multiple user-defined types will remain ambiguous and throw an error.

Ambiguous expressions which have candidate solutions within only one type category are likely to resolve, while ambiguous expressions with candidates spanning multiple categories are likely to throw an error and ask for clarification from the user.

Guidelines

All type conversion rules are designed with several principles in mind: