subdir = contrib/tsearch2

top_builddir = ../..

include$(top_builddir)/src/Makefile.global

overrideCPPFLAGS := -I. -I./snowball -I./ispell -I./wordparser$(CPPFLAGS)

MODULE_big = tsearch2

OBJS = dict_ex.o dict.o snmap.o stopword.o common.o prs_dcfg.o\

snowball/english_stem.o snowball/api.o snowball/russian_stem.o snowball/utilities.o\

dict_snowball.o ispell/spell.o dict_ispell.o dict_syn.o\

wparser.o wordparser/parser.o wordparser/deflex.o wparser_def.o\

ts_cfg.o tsvector.o rewrite.o crc32.o query.o gistidx.o\

tsvector_op.o rank.o ts_stat.o

DATA_built = tsearch2.sql untsearch2.sql

DOCS = README.tsearch2

REGRESS = tsearch2

wordparser/parser.c: wordparser/parser.l

$(FLEX) $(FLEXFLAGS) -8 -Ptsearch2_yy -o'$@' $<

else

@$(missing) flex $< $@

EXTRA_CLEAN = wordparser/parser.c tsearch2.sql.in

SHLIB_LINK := -lm

include$(top_srcdir)/contrib/contrib-global.mk

install: installstop

installstop:

cp stopword/*.stop$(datadir)

tsearch2.sql.in: tsearch.sql._in

sed's,DATA_PATH,$(datadir),g'<$<>$@

untsearch2.sql: untsearch.sql.in

cp$<$@

Tsearch2 - full text search extension for PostgreSQL

[10][Online version] of this document is available

This module is sponsored by Delta-Soft Ltd., Moscow, Russia.

Notice: This version is fully incompatible with old tsearch (V1),

which is considered as deprecated in upcoming 7.4 release and

obsoleted in 7.5.

The Tsearch2 contrib module contains an implementation of a new data

type tsvector - a searchable data type with indexed access. In a

nutshell, tsvector is a set of unique words along with their

positional information in the document, organized in a special

structure optimized for fast access and lookup. Actually, each word

entry, besides its position in the document, could have a weight

attribute, describing importance of this word (at a specific) position

in document. A set of bit-signatures of a fixed length, representing

tsvectors, are stored in a search tree (developed using PostgreSQL

GiST), which provides online update of full text index and fast query

lookup. The module provides indexed access methods, queries,

operations and supporting routines for the tsvector data type and easy

conversion of text data to tsvector. Table driven configuration allows

creation of custom configuration optimized for specific searches using

standard SQL commands.

Configuration allows you to:

* specify the type of lexemes to be indexed and the way they are

processed.

* specify dictionaries to be used along with stop words recognition.

* specify the parser used to process a document.

See [11]Documentation Roadmap for links to documentation.

Authors

* Oleg Bartunov <oleg@sai.msu.su>, Moscow, Moscow University, Russia

* Teodor Sigaev <teodor@sigaev.ru>, Moscow, Delta-Soft Ltd.,Russia

Contributors

* Robert John Shepherd and Andrew J. Kopciuch submitted

"Introduction to tsearch" (Robert - tsearch v1, Andrew - tsearch

v2)

* Brandon Craig Rhodes wrote "Tsearch2 Guide" and "Tsearch2

Reference" and proposed new naming convention for tsearch V2

New features

* Relevance ranking of search results

* Table driven configuration

* Morphology support (ispell dictionaries, snowball stemmers)

* Headline support (text fragments with highlighted search terms)

* Ability to plug-in custom dictionaries and parsers

* Synonym dictionary

* Generator of templates for dictionaries (built-in snowball stemmer

support)

* Statistics of indexed words is available

Limitations

* Lexeme should be not longer than 2048 bytes

* The number of lexemes is limited by 2^32. Note, that actual

capacity of tsvector is depends on whether positional information

is stored or not.

* tsvector - the size is limited by approximately 2^20 bytes.

* tsquery - the number of entries (lexemes and operations) < 32768

* Positional information

+ maximal position of lexeme < 2^14 (16384)

+ lexeme could have maximum 256 positions

References

* GiST development site -

[12]http://www.sai.msu.su/~megera/postgres/gist

* OpenFTS home page - [13]http://openfts.sourceforge.net/

* Mailing list -

[14]http://sourceforge.net/mailarchive/forum.php?forum=openfts-gen

eral

[15]Documentation Roadmap

Documentation Roadmap

* Several docs are available from docs/ subdirectory

+ "Tsearch V2 Introduction" by Andrew Kopciuch

+ "Tsearch2 Guide" by Brandon Rhodes

+ "Tsearch2 Reference" by Brandon Rhodes

* Readme.gendict in gendict/ subdirectory

+ [16][Gendict tutorial]

Online version of documentation is always available from Tsearch V2

home page -

[17]http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/

Support

Authors urgently recommend people to use [18][openfts-general] or

[19][pgsql-general] mailing lists for questions and discussions.

Caution

In spite of apparent easy full text searching with our tsearch module

(authors hope it's so), any serious search engine require profound

study of various aspects, such as stop words, dictionaries, special

parsers. Tsearch module was designed to facilitate both those cases.

Development History

Pre-tsearch era

Development of OpenFTS began in 2000 after realizing that we

needed a search engine optimized for online updates and able to

access metadata from the database. This is essential for online

news agencies, web portals, digital libraries, etc. Most search

engines available utilize an inverted index which is very fast

for searching but very slow for online updates. Incremental

updates of an inverted index is a complex engineering task

while we needed something light, free and with the ability to

access metadata from the database. The last requirement is very

important because in a real life application a search engine

should always consult metadata ( topic, permissions, date

range, version, etc.). We extensively use PostgreSQL as a

database backend and have no intention to move from it, so the

problem was to find a data structure and a fast way to access

it. PostgreSQL has rather unique data type for storing sets

(think about words) - arrays, but lacks index access to them. A

document is parsed into lexemes, which are identified in

various ways (e.g. stemming, morphology, dictionary), and as a

result is reduced to an array of integer numbers. During our

research we found a paper of Joseph Hellerstein which

introduced an interesting data structure suitable for sets -

RD-tree (Russian Doll tree). It looked very attractive, but

implementing it in PostgreSQL seemed difficult because of our

ignorance of database internals. Further research lead us to

the idea to use GiST for implementing RD-tree, but at that time

the GiST code had for a long while remained untouched and

contained several bugs. After work on improving GiST for

version 7.0.3 of PostgreSQL was done, we were able to implement

RD-Tree and use it for index access to arrays of integers. This

implementation was ideally suited for small arrays and

eliminated complex joins, but was practically useless for

indexing large arrays. The next improvement came from an idea

to represent a document by a single bit-signature, a so-called

superimposed signature (see "Index Structures for Databases

Containing Data Items with Set-valued Attributes", 1997, Sven

Helmer for details). We developeded the contrib/intarray module

and used it for full text indexing.

tsearch v1

It was inconvenient to use integer id's instead of words, so we

introduced a new data type called 'txtidx' - a searchable data

type (textual) with indexed access. This was a first step of

our work on an implementation of a built-in PostgreSQL full

text search engine. Even though tsearch v1 had many features of

a search engine it lacked configuration support and relevance

ranking. People were encouraged to use OpenFTS, which provided

relevance ranking based on coordinate information and flexible

configuration. OpenFTS v.0.34 is the last version based on

tsearch v1.

tsearch V2

People recognized tsearch as a powerful tool for full text

searching and insisted on adding ranking support, better

configurability, etc. We already thought about moving most of

the features of OpenFTS to tsearch, and in the early 2003 we

decided to work on a new version of tsearch - tsearch v2. We've

abandoned auxiliary index tables which were used by OpenFTS to

store coordinate information and modified the txtidx type to

store them internally. Also, we've added table-driven

configuration, support of ispell dictionaries, snowball

stemmers and the ability to specify which types of lexemes to

index. Also, it's now possible to generate headlines of

documents with highlighted search terms. These changes make

tsearch more user friendly and turn it into a really powerful

full text search engine. After announcing the alpha version, we

received a proposal from Brandon Rhodes to rename tsearch

functions to be more consistent. So, we have renamed txtidx

type to tsvector and other things as well.

To allow users of tsearch v1 smooth upgrade, we named the module as

tsearch2.

Future release of OpenFTS (v.0.35) will be based on tsearch2. Brave

people could download it from OpenFTS CVS (see link from [20][OpenFTS

page]

References

10. http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/docs/Tsearch_V2_Readme.html

11. http://www.sai.msu.su/~megera/oddmuse/index.cgi/Tsearch_V2_Readme#Documentation_Roadmap

12. http://www.sai.msu.su/~megera/postgres/gist

13. http://openfts.sourceforge.net/

14. http://sourceforge.net/mailarchive/forum.php?forum=openfts-general

15. http://www.sai.msu.su/~megera/oddmuse/index.cgi?action=anchor&id=Documentation_Roadmap#Documentation_Roadmap

16. http://www.sai.msu.su/~megera/oddmuse/index.cgi?Gendict

17. http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/

18. http://sourceforge.net/mailarchive/forum.php?forum=openfts-general

19. http://archives.postgresql.org/pgsql-general/

20. http://openfts.sourceforge.net/

char2text(char*in) {

returncharl2text(in,strlen(in));

}

text*charl2text(char*in,intlen) {

text*out=(text*)palloc(len+VARHDRSZ);

memcpy(VARDATA(out),in,len);

VARATT_SIZEP(out)=len+VARHDRSZ;

returnout;

}

*text2char(text*in) {

char*out=palloc(VARSIZE(in) );

memcpy(out,VARDATA(in),VARSIZE(in)-VARHDRSZ);

out[VARSIZE(in)-VARHDRSZ ]='\0';

returnout;

}

*pnstrdup(char*in,intlen) {

char*out=palloc(len+1 );

memcpy(out,in,len);

out[len]='\0';

returnout;

}

*ptextdup(text*in) {

text*out=(text*)palloc(VARSIZE(in) );

memcpy(out,in,VARSIZE(in));

returnout;

}

*mtextdup(text*in) {

text*out=(text*)malloc(VARSIZE(in) );

if ( !out )

ts_error(ERROR,"No memory");

memcpy(out,in,VARSIZE(in));

returnout;

}

ts_error(intstate,constchar*format, ...) {

va_listargs;

inttlen=128,len=0;

char*buf;

reset_cfg();

reset_dict();

reset_prs();

va_start(args,format);

buf=palloc(tlen);

len=vsnprintf(buf,tlen-1,format,args);

if (len >=tlen ) {

tlen=len+1;

buf=repalloc(buf,tlen );

vsnprintf(buf,tlen-1,format,args);

}

va_end(args);

elog(state,buf);

pfree(buf);

}

text_cmp(text*a,text*b) {

if (VARSIZE(a)==VARSIZE(b) )

returnstrncmp(VARDATA(a),VARDATA(b),VARSIZE(a)-VARHDRSZ );

return (int)VARSIZE(a)- (int)VARSIZE(b);

}

#definePG_NARGS() (fcinfo->nargs)

text*char2text(char*in);

text*charl2text(char*in,intlen);

char*text2char(text*in);

char*pnstrdup(char*in,intlen);

text*ptextdup(text*in);

text*mtextdup(text*in);

inttext_cmp(text*a,text*b);

#defineNEXTVAL(x) ( (text*)( (char*)(x) + INTALIGN( VARSIZE(x) ) ) )

#defineARRNELEMS(x) ArrayGetNItems( ARR_NDIM(x), ARR_DIMS(x))

voidts_error(intstate,constchar*format, ...);