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Chapter 5. Type Conversion

Table of Contents
5.1. Overview
5.2. Operators
5.3. Functions
5.4. Query Targets
5.5. UNION and CASE Constructs

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 results of a query. When necessary, 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.

5.1. 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 that 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 can be used in 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 for a string, 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. Since Postgres permits function overloading, the function name alone does not uniquely identify the function to be called --- the parser must select the right function based on the data types of the supplied arguments.

Query targets

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

UNION and CASE constructs

Since all select results from a UNION SELECT statement must appear in a single set of columns, the types of the results of each SELECT clause must be matched up and converted to a uniform set. Similarly, the result expressions of a CASE construct must be coerced to a common type so that the CASE expression as a whole has a known output type.

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 these 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 several basic type categories defined: boolean, numeric, string, bitstring, datetime, timespan, geometric, network, and user-defined. Each category, with the exception of user-defined, has a preferred type which is preferentially selected when there is ambiguity. In the user-defined category, each type is its own preferred type. Ambiguous expressions (those with multiple candidate parsing solutions) can often be resolved when there are multiple possible built-in types, but they will raise an error when there are multiple choices for user-defined types.

5.1.1. Guidelines

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

  • Implicit conversions should never have surprising or unpredictable outcomes.

  • User-defined types, of which the parser has no a-priori knowledge, should be "higher" in the type hierarchy. In mixed-type expressions, native types shall always be converted to a user-defined type (of course, only if conversion is necessary).

  • User-defined types are not related. Currently, Postgres does not have information available to it on relationships between types, other than hardcoded heuristics for built-in types and implicit relationships based on available functions in the catalog.

  • There should be no extra overhead from the parser or executor if a query does not need implicit type conversion. That is, if a query is well formulated and the types already match up, then the query should proceed without spending extra time in the parser and without introducing unnecessary implicit conversion functions into the query.

    Additionally, if a query usually requires an implicit conversion for a function, and if then the user defines an explicit function with the correct argument types, the parser should use this new function and will no longer do the implicit conversion using the old function.

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