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, GaussDB(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	&
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

last updated: 2024-11-13 15:46 UTC - commit: bdcb01d62e4f1de672b662d88ef6cb8eb3a27a29