PostgreSQL

8.11.1. tsvector

8.11.2. tsquery

PostgreSQL provides two data types that are designed to support full text search, which is the activity of searching through a collection of natural-language documents to locate those that best match a query. The tsvector type represents a document in a form optimized for text search; the tsquery type similarly represents a text query. Chapter 12 provides a detailed explanation of this facility, and Section 9.13 summarizes the related functions and operators.

A tsvector value is a sorted list of distinct lexemes, which are words that have been normalized to merge different variants of the same word (see Chapter 12 for details). Sorting and duplicate-elimination are done automatically during input, as shown in this example:

To represent lexemes containing whitespace or punctuation, surround them with quotes:

(We use dollar-quoted string literals in this example and the next one to avoid the confusion of having to double quote marks within the literals.) Embedded quotes and backslashes must be doubled:

Optionally, integer positions can be attached to lexemes:

A position normally indicates the source word’s location in the document. Positional information can be used for proximity ranking. Position values can range from 1 to 16383; larger numbers are silently set to 16383. Duplicate positions for the same lexeme are discarded.

Lexemes that have positions can further be labeled with a weight, which can be A, B, C, or D. D is the default and hence is not shown on output:

Weights are typically used to reflect document structure, for example by marking title words differently from body words. Text search ranking functions can assign different priorities to the different weight markers.

It is important to understand that the tsvector type itself does not perform any word normalization; it assumes the words it is given are normalized appropriately for the application. For example,

For most English-text-searching applications the above words would be considered non-normalized, but tsvector doesn’t care. Raw document text should usually be passed through to_tsvector to normalize the words appropriately for searching:

Again, see Chapter 12 for more detail.

A tsquery value stores lexemes that are to be searched for, and can combine them using the Boolean operators & (AND), | (OR), and ! (NOT), as well as the phrase search operator <-> (FOLLOWED BY). There is also a variant <`N>` of the FOLLOWED BY operator, where `N is an integer constant that specifies the distance between the two lexemes being searched for. `<-> is equivalent to <1>.

Parentheses can be used to enforce grouping of these operators. In the absence of parentheses, ! (NOT) binds most tightly, <-> (FOLLOWED BY) next most tightly, then & (AND), with | (OR) binding the least tightly.

Here are some examples:

Optionally, lexemes in a tsquery can be labeled with one or more weight letters, which restricts them to match only tsvector lexemes with one of those weights:

Also, lexemes in a tsquery can be labeled with * to specify prefix matching:

This query will match any word in a tsvector that begins with “[.quote]#super”#.

Quoting rules for lexemes are the same as described previously for lexemes in tsvector; and, as with tsvector, any required normalization of words must be done before converting to the tsquery type. The to_tsquery function is convenient for performing such normalization:

Note that to_tsquery will process prefixes in the same way as other words, which means this comparison returns true:

because postgres gets stemmed to postgr:

which will match the stemmed form of postgraduate.

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