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areas are for the lifetime of the backend and in the interests of not breaking something that's not broken I left alone. Note for anyone reading this and wanting it for tsearch-v2-stable (i.e. for 7.3 backend) this patch probably will not apply cleanly to that source. It should be simple enough to see what's going on and apply the changes by hand if need be. -- Nigel J. Andrews |
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data | ||
docs | ||
expected | ||
gendict | ||
ispell | ||
snowball | ||
sql | ||
stopword | ||
wordparser | ||
common.c | ||
common.h | ||
crc32.c | ||
crc32.h | ||
dict_ex.c | ||
dict_ispell.c | ||
dict_snowball.c | ||
dict_syn.c | ||
dict.c | ||
dict.h | ||
gistidx.c | ||
gistidx.h | ||
Makefile | ||
prs_dcfg.c | ||
query.c | ||
query.h | ||
rank.c | ||
README.tsearch2 | ||
rewrite.c | ||
rewrite.h | ||
snmap.c | ||
snmap.h | ||
stopword.c | ||
ts_cfg.c | ||
ts_cfg.h | ||
ts_stat.c | ||
ts_stat.h | ||
tsearch.sql.in | ||
tsvector_op.c | ||
tsvector.c | ||
tsvector.h | ||
untsearch.sql.in | ||
wparser_def.c | ||
wparser.c | ||
wparser.h |
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. OpenFTS vs Tsearch2 OpenFTS is a middleware between application and database, so it uses tsearch2 as a storage, while database engine is used as a query executor (searching). Everything else (parsing of documents, query processing, linguistics) carry outs on client side. That's why OpenFTS has its own configuration table (fts_conf) and works with its own set of dictionaries. OpenFTS is more flexible, because it could be used in multi-server architecture with separated machines for repository of documents (documents could be stored in file system), database and query engine. 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/