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Parsers

Text search parsers are responsible for splitting raw document text into tokens and identifying each token's type, where the set of types is defined by the parser itself. Note that a parser does not modify the text at all — it simply identifies plausible word boundaries. Because of this limited scope, there is less need for application-specific custom parsers than there is for custom dictionaries.

Currently, DWS provides the following built-in parsers: pg_catalog.default for English configuration, and pg_catalog.ngram, pg_catalog.zhparser, and pg_catalog.pound for full text search in texts containing Chinese, or both Chinese and English.

The built-in parser is named pg_catalog.default. It recognizes 23 token types, shown in Table 1.

Table 1 Default parser's token types

Alias

Description

Examples

asciiword

Word, all ASCII letters

elephant

word

Word, all letters

mañana

numword

Word, letters and digits

beta1

asciihword

Hyphenated word, all ASCII

up-to-date

hword

Hyphenated word, all letters

lógico-matemática

numhword

Hyphenated word, letters and digits

postgresql-beta1

hword_asciipart

Hyphenated word part, all ASCII

postgresql in the context postgresql-beta1

hword_part

Hyphenated word part, all letters

lógico or matemática in the context lógico-matemática

hword_numpart

Hyphenated word part, letters and digits

beta1 in the context postgresql-beta1

email

Email address

foo@example.com

protocol

Protocol head

http://

url

URL

example.com/stuff/index.html

host

Host

example.com

url_path

URL path

/stuff/index.html, in the context of a URL

file

File or path name

/usr/local/foo.txt, if not within a URL

sfloat

Scientific notation

-1.23E+56

float

Decimal notation

-1.234

int

Signed integer

-1234

uint

Unsigned integer

1234

version

Version number

8.3.0

tag

XML tag

<a href="dictionaries.html">

entity

XML entity

&amp;

blank

Space symbols

(any whitespace or punctuation not otherwise recognized)

Note: The parser's notion of a "letter" is determined by the database's locale setting, specifically lc_ctype. Words containing only the basic ASCII letters are reported as a separate token type, since it is sometimes useful to distinguish them. In most European languages, token types word and asciiword should be treated alike.

email does not support all valid email characters as defined by RFC 5322. Specifically, the only non-alphanumeric characters supported for email user names are period, dash, and underscore.

It is possible for the parser to identify overlapping tokens in the same piece of text. As an example, a hyphenated word will be reported both as the entire word and as each component:

SELECT alias, description, token FROM ts_debug('english','foo-bar-beta1');
      alias      |               description                |     token     
-----------------+------------------------------------------+---------------
 numhword        | Hyphenated word, letters and digits      | foo-bar-beta1
 hword_asciipart | Hyphenated word part, all ASCII          | foo
 blank           | Space symbols                            | -
 hword_asciipart | Hyphenated word part, all ASCII          | bar
 blank           | Space symbols                            | -
 hword_numpart   | Hyphenated word part, letters and digits | beta1

This behavior is desirable since it allows searches to work for both the whole compound word and for components. Here is another instructive example:

SELECT alias, description, token FROM ts_debug('english','http://example.com/stuff/index.html');
  alias   |  description  |            token             
----------+---------------+------------------------------
 protocol | Protocol head | http://
 url      | URL           | example.com/stuff/index.html
 host     | Host          | example.com
 url_path | URL path      | /stuff/index.html

N-gram is a mechanical word segmentation method, and applies to no semantic Chinese segmentation scenarios. The N-gram segmentation method ensures the completeness of the segmentation. However, to cover all the possibilities, it but adds unnecessary words to the index, resulting in a large number of index items. N-gram supports Chinese coding, including GBK and UTF-8. Six built-in token types are shown in Table 2.

Table 2 Token types

Alias

Description

zh_words

chinese words

en_word

english word

numeric

numeric data

alnum

alnum string

grapsymbol

graphic symbol

multisymbol

multiple symbol

Zhparser is a dictionary-based semantic word segmentation method. The bottom-layer calls the Simple Chinese Word Segmentation (SCWS) algorithm (https://github.com/hightman/scws), which applies to Chinese segmentation scenarios. SCWS is a term frequency and dictionary-based mechanical Chinese words engine. It can split a whole paragraph Chinese text into words. The two Chinese coding formats, GBK and UTF-8, are supported. The 26 built-in token types are shown in Table 3.

Table 3 Token types

Alias

Description

A

Adjective

B

Differentiation

C

Conjunction

D

Adverb

E

Exclamation

F

Position

G

Lexeme

H

Preceding element

I

Idiom

J

Acronyms and abbreviations

K

Subsequent element

L

Common words

M

Numeral

N

Noun

O

Onomatopoeia

P

Preposition

Q

Quantifiers

R

Pronoun

S

Space

T

Time

U

Auxiliary word

V

Verb

W

Punctuation

X

Unknown

Y

Interjection

Z

Status words

Pound segments words in a fixed format. It is used to segment to-be-parsed nonsense Chinese and English words that are separated by fixed separators. It supports Chinese encoding (including GBK and UTF8) and English encoding (including ASCII). Pound has six pre-configured token types (as listed in Table 4) and supports five separators (as listed in Table 5). The default, the separator is #. Pound The maximum length of a token is 256 characters.

Table 4 Token types

Alias

Description

zh_words

chinese words

en_word

english word

numeric

numeric data

alnum

alnum string

grapsymbol

graphic symbol

multisymbol

multiple symbol

Table 5 Separator types

Delimiter

Description

@

Special character

#

Special character

$

Special character

%

Special character

/

Special character