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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<title>tsearch-v2-intro</title>
</head>
<body class="content">
<div class="content">
<h2>Tsearch2 - Introduction</h2>
<p><a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/docs/tsearch-V2-intro.html">
[Online version]</a> of this document is available.</p>
<p>The tsearch2 module is available to add as an extension to the
PostgreSQL database to allow for Full Text Indexing. This document
is an introduction to installing, configuring, using and
maintaining the database with the tsearch2 module activated.</p>
<p>Please, note, tsearch2 module is fully incompatible with old
tsearch, which is deprecated in 7.4 and will be obsoleted in
8.0.</p>
<h3>USING TSEARCH2 AND POSTGRESQL FOR A WEB BASED SEARCH
ENGINE</h3>
<p>This documentation is provided as a short guide on how to
quickly get up and running with tsearch2 and PostgreSQL, for those
who want to implement a full text indexed based search engine. It
is not meant to be a complete in-depth guide into the full ins and
outs of the contrib/tsearch2 module, and is primarily aimed at
beginners who want to speed up searching of large text fields, or
those migrating from other database systems such as MS-SQL.</p>
<p>The README.tsearch2 file included in the contrib/tsearch2
directory contains a brief overview and history behind tsearch.
This can also be found online <a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/">[right
here]</a>.</p>
<p>Further in depth documentation such as a full function
reference, and user guide can be found online at the <a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/docs/">[tsearch
documentation home]</a>.</p>
<h3>ACKNOWLEDGEMENTS</h3>
<p>Robert John Shepherd originally wrote this documentation for the
previous version of tsearch module (v1) included with the postgres
release. I took his documentation and updated it to comply with the
tsearch2 modifications.</p>
<p>Robert's original acknowledgements:</p>
<p>"Thanks to Oleg Bartunov for taking the time to answer many of
my questions regarding this module, and also to Teodor Sigaev for
clearing up the process of making your own dictionaries. Plus of
course a big thanks to the pair of them for writing this module in
the first place!"</p>
<p>I would also like to extend my thanks to the developers, and
Oleg Bartunov for all of his direction and help with the new
features of tsearch2.</p>
<h3>OVERVIEW</h3>
<p>MS-SQL provides a full text indexing (FTI) system which enables
the fast searching of text based fields, very useful for websites
(and other applications) that require a results set based on key
words. PostgreSQL ships with a contributed module called tsearch2,
which implements a special type of index that can also be used for
full text indexing. Further more, unlike MS' offering which
requires regular incremental rebuilds of the text indexes
themselves, tsearch2 indexes are always up-to-date and keeping them
so induces very little overhead.</p>
<p>Before we get into the details, it is recommended that you have
installed and tested PostgreSQL, are reasonably familiar with
databases, the SQL query language and also understand the basics of
connecting to PostgreSQL from the local shell. This document isn't
intended for the complete PostgreSQL newbie, but anyone with a
reasonable grasp of the basics should be able to follow it.</p>
<h3>INSTALLATION</h3>
<p>Starting with PostgreSQL version 7.4 tsearch2 is now included in
the contrib directory with the PostgreSQL sources. contrib/tsearch2
is where you will find everything needed to install and use
tsearch2. Please note that tsearch2 will also work with PostgreSQL
version 7.3.x, but it is not the module included with the source
distribution. You will have to download the module separately and
install it in the same fashion.</p>
<p>I installed the tsearch2 module to a PostgreSQL 7.3 database
from the contrib directory without squashing the original (old)
tsearch module. What I did was move the modules tsearch src
driectory into the contrib tree under the name tsearchV2.</p>
<p>Step one is to download the tsearch V2 module :</p>
<p><a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/">[http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/]</a>
(check Development History for latest stable version !)</p>
<pre>
tar -zxvf tsearch-v2.tar.gz
mv tsearch2 $PGSQL_SRC/contrib/
cd $PGSQL_SRC/contrib/tsearch2
</pre>
<p>If you are installing from PostgreSQL version 7.4 or higher, you
can skip those steps and just change to the contrib/tsearch2
directory in the source tree and continue from there.</p>
<p>As of May 9, 2004 there is a source patch available for
tsearch2. The patch provides changes to the pg_ts_ configuration
tables to allow for easy dump and restore of a database containing
tsearch2. The patch is available here : <a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/regprocedure_7.4.patch.gz">
[http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/regprocedure_7.4.patch.gz]</a></p>
<p>To apply this patch, download the mentioned file and place it in
your postgreSQL source tree ($PGSQL_SRC). This patch is not
required for tsearch2 to work. I would however, highly recommend it
as it makes the backup and restore procedures very simple.</p>
<pre>
cd $PGSQL_SRC
gunzip regprocedure_7.4.patch.gz
patch -b -p1 &lt; regprocedure_7.4.patch
</pre>
<p>If you have a working version of tsearch2 in your database, you
do not need to re-install the tsearch2 module. Just apply the patch
and run make. This patch only affects the tsearch2.sql file. You
can run the SQL script found : <a href="
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/regprocedure_update.sql">
[right here]</a> This script will make the modifications found in
the patch, and update the fields from the existing data. From this
point on, you can dump and restore the database in a normal
fashion. Without this patch, you must follow the instructions later
in this document for backup and restore.</p>
<p>This patch is only needed for tsearch2 in PostgreSQL versions
7.3.x and 7.4.x. The patch has been applied to the sources for
8.0.x.</p>
<p>When you have your source tree for tsearch2 ready, you can
continue with the regular building and installation process</p>
<pre>
gmake
gmake install
gmake installcheck
</pre>
<p>That is pretty much all you have to do, unless of course you get
errors. However if you get those, you better go check with the
mailing lists over at <a href="
http://www.postgresql.org">http://www.postgresql.org</a> or
<a href="
http://openfts.sourceforge.net/">http://openfts.sourceforge.net/</a>
since its never failed for me.</p>
<p>If you ever need to revert this patch, and go back to the
unpatched version of tsearch2, it is simple if you followed the
above patch command. The -b option creates a backup of the original
file, so we can just copy it back.</p>
<pre>
cd $PGSQL_SRC/contrib/tsearch2
cp tsearch.sql.in.orig tsearch.sql.in
make
</pre>
<p>If you need the patched version again, just follow the patch
instructions again.</p>
<p>The directory in the contib/ and the directory from the archive
is called tsearch2. Tsearch2 is completely incompatible with the
previous version of tsearch. This means that both versions can be
installed into a single database, and migration the new version may
be much easier.</p>
<p>NOTE: the previous version of tsearch found in the
contrib/tsearch directory is depricated. Although it is still
available and included within PostgreSQL version 7.4. It will be
removed in version 8.0.</p>
<h3>ADDING TSEARCH2 FUNCTIONALITY TO A DATABASE</h3>
<p>We should create a database to use as an example for the
remainder of this file. We can call the database "ftstest". You can
create it from the command line like this:</p>
<pre>
#createdb ftstest
</pre>
<p>If you thought installation was easy, this next bit is even
easier. Change to the PGSQL_SRC/contrib/tsearch2 directory and
type:</p>
<pre>
psql ftstest &lt; tsearch2.sql
</pre>
<p>The file "tsearch2.sql" holds all the wonderful little goodies
you need to do full text indexing. It defines numerous functions
and operators, and creates the needed tables in the database. There
will be 4 new tables created after running the tsearch2.sql file :
pg_ts_dict, pg_ts_parser, pg_ts_cfg, pg_ts_cfgmap are added.</p>
<p>You can check out the tables if you like:</p>
<pre>
#psql ftstest
ftstest=# \d
List of relations
Schema | Name | Type | Owner
--------+--------------+-------+----------
public | pg_ts_cfg | table | kopciuch
public | pg_ts_cfgmap | table | kopciuch
public | pg_ts_dict | table | kopciuch
public | pg_ts_parser | table | kopciuch
(4 rows)
</pre>
<h3>TYPES AND FUNCTIONS PROVIDED BY TSEARCH2</h3>
<p>The first thing we can do is try out some of the types that are
provided for us. Lets look at the tsvector type provided for
us:</p>
<pre>
SELECT 'Our first string used today'::tsvector;
tsvector
---------------------------------------
'Our' 'used' 'first' 'today' 'string'
(1 row)
</pre>
<p>The results are the words used within our string. Notice they
are not in any particular order. The tsvector type returns a string
of space separated words.</p>
<pre>
SELECT 'Our first string used today first string'::tsvector;
tsvector
-----------------------------------------------
'Our' 'used' 'first' 'today' 'string'
(1 row)
</pre>
<p>Notice the results string has each unique word ('first' and
'string' only appear once in the tsvector value). Which of course
makes sense if you are searching the full text ... you only need to
know each unique word in the text.</p>
<p>Those examples were just casting a text field to that of type
tsvector. Lets check out one of the new functions created by the
tsearch2 module.</p>
<p>The function to_tsvector has 3 possible signatures:</p>
<pre>
to_tsvector(oid, text);
to_tsvector(text, text);
to_tsvector(text);
</pre>
<p>We will use the second method using two text fields. The
overloaded methods provide us with a way to specifiy the way the
searchable text is broken up into words (Stemming process). Right
now we will specify the 'default' configuration. See the section on
TSEARCH2 CONFIGURATION to learn more about this.</p>
<pre>
SELECT to_tsvector('default',
'Our first string used today first string');
to_tsvector
--------------------------------------------
'use':4 'first':2,6 'today':5 'string':3,7
(1 row)
</pre>
<p>The result returned from this function is of type tsvector. The
results came about by this reasoning: All of the words in the text
passed in are stemmed, or not used because they are stop words
defined in our configuration. Each lower case morphed word is
returned with all of the positons in the text.</p>
<p>In this case the word "Our" is a stop word in the default
configuration. That means it will not be included in the result.
The word "first" is found at positions 2 and 6 (although "Our" is a
stop word, it's position is maintained). The word(s) positioning is
maintained exactly as in the original string. The word "used" is
morphed to the word "use" based on the default configuration for
word stemming, and is found at position 4. The rest of the results
follow the same logic. Just a reminder again ... the order of the
'word' position in the output is not in any kind of order. (ie
'use':4 appears first)</p>
<p>If you want to view the output of the tsvector fields without
their positions, you can do so with the function
"strip(tsvector)".</p>
<pre>
SELECT strip(to_tsvector('default',
'Our first string used today first string'));
strip
--------------------------------
'use' 'first' 'today' 'string'
</pre>
<p>If you wish to know the number of unique words returned in the
tsvector you can do so by using the function "length(tsvector)"</p>
<pre>
SELECT length(to_tsvector('default',
'Our first string used today first string'));
length
--------
4
(1 row)
</pre>
<p>Lets take a look at the function to_tsquery. It also has 3
signatures which follow the same rational as the to_tsvector
function:</p>
<pre>
to_tsquery(oid, text);
to_tsquery(text, text);
to_tsquery(text);
</pre>
<p>Lets try using the function with a single word :</p>
<pre>
SELECT to_tsquery('default', 'word');
to_tsquery
-----------
'word'
(1 row)
</pre>
<p>I call the function the same way I would a to_tsvector function,
specifying the 'default' configuration for morphing, and the result
is the stemmed output 'word'.</p>
<p>Lets attempt to use the function with a string of multiple
words:</p>
<pre>
SELECT to_tsquery('default', 'this is many words');
ERROR: Syntax error
</pre>
<p>The function can not accept a space separated string. The
intention of the to_tsquery function is to return a type of
"tsquery" used for searching a tsvector field. What we need to do
is search for one to many words with some kind of logic (for now
simple boolean).</p>
<pre>
SELECT to_tsquery('default', 'searching|sentence');
to_tsquery
----------------------
'search' | 'sentenc'
(1 row)
</pre>
<p>Notice that the words are separated by the boolean logic "OR",
the text could contain boolean operators &amp;,|,!,() with their
usual meaning.</p>
<p>You can not use words defined as being a stop word in your
configuration. The function will not fail ... you will just get no
result, and a NOTICE like this:</p>
<pre>
SELECT to_tsquery('default', 'a|is&amp;not|!the');
NOTICE: Query contains only stopword(s)
or doesn't contain lexem(s), ignored
to_tsquery
-----------
(1 row)
</pre>
<p>That is a beginning to using the types, and functions defined in
the tsearch2 module. There are numerous more functions that I have
not touched on. You can read through the tsearch2.sql file built
when compiling to get more familiar with what is included.</p>
<h3>INDEXING FIELDS IN A TABLE</h3>
<p>The next stage is to add a full text index to an existing table.
In this example we already have a table defined as follows:</p>
<pre>
CREATE TABLE tblMessages
(
intIndex int4,
strTopic varchar(100),
strMessage text
);
</pre>
<p>We are assuming there are several rows with some kind of data in
them. Any data will do, just do several inserts with test strings
for a topic, and a message. here is some test data I inserted. (yes
I know it's completely useless stuff ;-) but it will serve our
purpose right now).</p>
<pre>
INSERT INTO tblMessages
VALUES ('1', 'Testing Topic', 'Testing message data input');
INSERT INTO tblMessages
VALUES ('2', 'Movie', 'Breakfast at Tiffany\'s');
INSERT INTO tblMessages
VALUES ('3', 'Famous Author', 'Stephen King');
INSERT INTO tblMessages
VALUES ('4', 'Political Topic',
'Nelson Mandella is released from prison');
INSERT INTO tblMessages
VALUES ('5', 'Nursery rhyme phrase',
'Little jack horner sat in a corner');
INSERT INTO tblMessages
VALUES ('6', 'Gettysburg address quotation',
'Four score and seven years ago'
' our fathers brought forth on this'
' continent a new nation, conceived in'
' liberty and dedicated to the proposition'
' that all men are created equal');
INSERT INTO tblMessages
VALUES ('7', 'Classic Rock Bands',
'Led Zeppelin Grateful Dead and The Sex Pistols');
INSERT INTO tblMessages
VALUES ('8', 'My birth address',
'18 Sommervile road, Regina, Saskatchewan');
INSERT INTO tblMessages
VALUES ('9', 'Joke', 'knock knock : who\'s there?'
' I will not finish this joke');
INSERT INTO tblMessages
VALUES ('10', 'Computer information',
'My computer is a pentium III 400 mHz'
' with 192 megabytes of RAM');
</pre>
<p>The next stage is to create a special text index which we will
use for FTI, so we can search our table of messages for words or a
phrase. We do this using the SQL command:</p>
<pre>
ALTER TABLE tblMessages ADD COLUMN idxFTI tsvector;
</pre>
<p>Note that unlike traditional indexes, this is actually a new
field in the same table, which is then used (through the magic of
the tsearch2 operators and functions) by a special index we will
create in a moment.</p>
<p>The general rule for the initial insertion of data will follow
four steps:</p>
<pre>
1. update table
2. vacuum full analyze
3. create index
4. vacuum full analyze
</pre>
<p>The data can be updated into the table, the vacuum full analyze
will reclaim unused space. The index can be created on the table
after the data has been inserted. Having the index created prior to
the update will slow down the process. It can be done in that
manner, this way is just more efficient. After the index has been
created on the table, vacuum full analyze is run again to update
postgres's statistics (ie having the index take effect).</p>
<pre>
UPDATE tblMessages SET idxFTI=to_tsvector('default', strMessage);
VACUUM FULL ANALYZE;
</pre>
<p>Note that this only inserts the field strMessage as a tsvector,
so if you want to also add strTopic to the information stored, you
should instead do the following, which effectively concatenates the
two fields into one before being inserted into the table:</p>
<pre>
UPDATE tblMessages
SET idxFTI=to_tsvector('default',coalesce(strTopic,'') ||' '|| coalesce(strMessage,''));
VACUUM FULL ANALYZE;
</pre>
<p><strong>Using the coalesce function makes sure this
concatenation also works with NULL fields.</strong></p>
<p>We need to create the index on the column idxFTI. Keep in mind
that the database will update the index when some action is taken.
In this case we _need_ the index (The whole point of Full Text
INDEXINGi ;-)), so don't worry about any indexing overhead. We will
create an index based on the gist function. GiST is an index
structure for Generalized Search Tree.</p>
<pre>
CREATE INDEX idxFTI_idx ON tblMessages USING gist(idxFTI);
VACUUM FULL ANALYZE;
</pre>
<p>After you have converted all of your data and indexed the
column, you can select some rows to see what actually happened. I
will not display output here but you can play around yourselves and
see what happened.</p>
<p>The last thing to do is set up a trigger so every time a row in
this table is changed, the text index is automatically updated.
This is easily done using:</p>
<pre>
CREATE TRIGGER tsvectorupdate BEFORE UPDATE OR INSERT ON tblMessages
FOR EACH ROW EXECUTE PROCEDURE tsearch2(idxFTI, strMessage);
</pre>
<p>Or if you are indexing both strMessage and strTopic you should
instead do:</p>
<pre>
CREATE TRIGGER tsvectorupdate BEFORE UPDATE OR INSERT ON tblMessages
FOR EACH ROW EXECUTE PROCEDURE
tsearch2(idxFTI, strTopic, strMessage);
</pre>
<p>Before you ask, the tsearch2 function accepts multiple fields as
arguments so there is no need to concatenate the two into one like
we did before.</p>
<p>If you want to do something specific with columns, you may write
your very own trigger function using plpgsql or other procedural
languages (but not SQL, unfortunately) and use it instead of
<em>tsearch2</em> trigger.</p>
<p>You could however call other stored procedures from within the
tsearch2 function. Lets say we want to create a function to remove
certain characters (like the @ symbol from all text).</p>
<pre>
CREATE FUNCTION dropatsymbol(text)
RETURNS text AS 'select replace($1, \'@\', \' \');' LANGUAGE SQL;
</pre>
<p>Now we can use this function within the tsearch2 function on the
trigger.</p>
<pre>
DROP TRIGGER tsvectorupdate ON tblmessages;
CREATE TRIGGER tsvectorupdate BEFORE UPDATE OR INSERT ON tblMessages
FOR EACH ROW EXECUTE PROCEDURE tsearch2(idxFTI, dropatsymbol, strMessage);
INSERT INTO tblmessages VALUES (69, 'Attempt for dropatsymbol', 'Test@test.com');
</pre>
<p>If at this point you receive an error stating: ERROR: Can't find
tsearch config by locale</p>
<p>Do not worry. You have done nothing wrong. And tsearch2 is not
broken. All that has happened here is that the configuration is
setup to use a configuration based on the locale of the server. All
you have to do is change your default configuration, or add a new
one for your specific locale. See the section on TSEARCH2
CONFIGURATION.</p>
<pre class="real">
SELECT * FROM tblmessages WHERE intindex = 69;
intindex | strtopic | strmessage | idxfti
----------+--------------------------+---------------+-----------------------
69 | Attempt for dropatsymbol | Test@test.com | 'test':1 'test.com':2
(1 row)
</pre>
Notice that the string content was passed throught the stored
procedure dropatsymbol. The '@' character was replaced with a
single space ... and the output from the procedure was then stored
in the tsvector column.
<p>This could be useful for removing other characters from indexed
text, or any kind of preprocessing needed to be done on the text
prior to insertion into the index.</p>
<h3>QUERYING A TABLE</h3>
<p>There are some examples in the README.tsearch2 file for querying
a table. One major difference between tsearch and tsearch2 is the
operator ## is no longer available. Only the operator @@ is
defined, using the types tsvector on one side and tsquery on the
other side.</p>
<p>Lets search the indexed data for the word "Test". I indexed
based on the the concatenation of the strTopic, and the
strMessage:</p>
<pre>
SELECT intindex, strtopic FROM tblmessages
WHERE idxfti @@ 'test'::tsquery;
intindex | strtopic
----------+---------------
1 | Testing Topic
(1 row)
</pre>
<p>The only result that matched was the row with a topic "Testing
Topic". Notice that the word I search for was all lowercase. Let's
see what happens when I query for uppercase "Test".</p>
<pre>
SELECT intindex, strtopic FROM tblmessages
WHERE idxfti @@ 'Test'::tsquery;
intindex | strtopic
----------+----------
(0 rows)
</pre>
<p>We get zero rows returned. The reason is because when the text
was inserted, it was morphed to my default configuration (because
of the call to to_tsvector in the UPDATE statement). If there was
no morphing done, and the tsvector field(s) contained the word
'Text', a match would have been found.</p>
<p>Most likely the best way to query the field is to use the
to_tsquery function on the right hand side of the @@ operator like
this:</p>
<pre>
SELECT intindex, strtopic FROM tblmessages
WHERE idxfti @@ to_tsquery('default', 'Test | Zeppelin');
intindex | strtopic
----------+--------------------
1 | Testing Topic
7 | Classic Rock Bands
(2 rows)
</pre>
<p>That query searched for all instances of "Test" OR "Zeppelin".
It returned two rows: the "Testing Topic" row, and the "Classic
Rock Bands" row. The to_tsquery function performed the correct
morphology upon the parameters, and searched the tsvector field
appropriately.</p>
<p>The last example here relates to searching for a phrase, for
example "minority report". This poses a problem with regard to
tsearch2, as it doesn't index phrases, only words. But there is a
way around which doesn't appear to have a significant impact on
query time, and that is to use a query such as the following:</p>
<pre>
SELECT intindex, strTopic FROM tblmessages
WHERE idxfti @@ to_tsquery('default', 'gettysburg &amp; address')
AND strMessage ~* '.*men are created equal.*';
intindex | strtopic
----------+------------------------------
6 | Gettysburg address quotation
(1 row)
SELECT intindex, strTopic FROM tblmessages
WHERE idxfti @@ to_tsquery('default', 'gettysburg &amp; address')
AND strMessage ~* '.*something that does not exist.*';
intindex | strtopic
----------+----------
(0 rows)
</pre>
<p>Of course if your indexing both strTopic and strMessage, and
want to search for this phrase on both, then you will have to get
out the brackets and extend this query a little more.</p>
<h3>TSEARCH2 CONFIGURATION</h3>
<p>Some words such as "and", "the", and "who" are automatically not
indexed, since they belong to a pre-existing dictionary of "Stop
Words" which tsearch2 does not perform indexing on. If someone
needs to search for "The Who" in your database, they are going to
have a tough time coming up with any results, since both are
ignored in the indexes. But there is a solution.</p>
<p>Lets say we want to add a word into the stop word list for
english stemming. We could edit the file
:'/usr/local/pgsql/share/english.stop' and add a word to the list.
I edited mine to exclude my name from indexing:</p>
<pre>
- Edit /usr/local/pgsql/share/english.stop
- Add 'andy' to the list
- Save the file.
</pre>
<p>When you connect to the database, the dict_init procedure is run
during initialization. And in my configuration it will read the
stop words from the file I just edited. If you were connected to
the DB while editing the stop words, you will need to end the
current session and re-connect. When you re-connect to the
database, 'andy' is no longer indexed:</p>
<pre>
SELECT to_tsvector('default', 'Andy');
to_tsvector
------------
(1 row)
</pre>
<p>Originally I would get the result :</p>
<pre>
SELECT to_tsvector('default', 'Andy');
to_tsvector
------------
'andi':1
(1 row)
</pre>
<p>But since I added it as a stop word, it would be ingnored on the
indexing. The stop word added was used in the dictionary "en_stem".
If I were to use a different configuration such as 'simple', the
results would be different. There are no stop words for the simple
dictionary. It will just convert to lower case, and index every
unique word.</p>
<pre>
SELECT to_tsvector('simple', 'Andy andy The the in out');
to_tsvector
-------------------------------------
'in':5 'out':6 'the':3,4 'andy':1,2
(1 row)
</pre>
<p>All this talk about which configuration to use is leading us
into the actual configuration of tsearch2. In the examples in this
document the configuration has always been specified when using the
tsearch2 functions:</p>
<pre>
SELECT to_tsvector('default', 'Testing the default config');
SELECT to_tsvector('simple', 'Example of simple Config');
</pre>
<p>The pg_ts_cfg table holds each configuration you can use with
the tsearch2 functions. As you can see the ts_name column contains
both the 'default' configurations based on the 'C' locale. And the
'simple' configuration which is not based on any locale.</p>
<pre>
SELECT * from pg_ts_cfg;
ts_name | prs_name | locale
-----------------+----------+--------------
default | default | C
default_russian | default | ru_RU.KOI8-R
simple | default |
(3 rows)
</pre>
<p>Each row in the pg_ts_cfg table contains the name of the
tsearch2 configuration, the name of the parser to use, and the
locale mapped to the configuration. There is only one parser to
choose from the table pg_ts_parser called 'default'. More parsers
could be written, but for our needs we will use the default.</p>
<p>There are 3 configurations installed by tsearch2 initially. If
your locale is set to 'en_US' for example (like my laptop), then as
you can see there is currently no dictionary configured to use with
that locale. You can either set up a new configuration or just use
one that already exists. If I do not specify which configuration to
use in the to_tsvector function, I receive the following error.</p>
<pre>
SELECT to_tsvector('learning tsearch is like going to school');
ERROR: Can't find tsearch config by locale
</pre>
<p>We will create a new configuration for use with the server
encoding 'en_US'. The first step is to add a new configuration into
the pg_ts_cfg table. We will call the configuration
'default_english', with the default parser and use the locale
'en_US'.</p>
<pre>
INSERT INTO pg_ts_cfg (ts_name, prs_name, locale)
VALUES ('default_english', 'default', 'en_US');
</pre>
<p>We have only declared that there is a configuration called
'default_english'. We need to set the configuration of how
'default_english' will work. The next step is creating a new
dictionary to use. The configuration of the dictionary is
completlely different in tsearch2. In the prior versions to make
changes, you would have to re-compile your changes into the
tsearch.so. All of the configuration has now been moved into the
system tables created by executing the SQL code from
tsearch2.sql</p>
<p>Lets take a first look at the pg_ts_dict table</p>
<pre>
ftstest=# \d pg_ts_dict
Table "public.pg_ts_dict"
Column | Type | Modifiers
-----------------+--------------+-----------
dict_name | text | not null
dict_init | regprocedure |
dict_initoption | text |
dict_lexize | regprocedure | not null
dict_comment | text |
Indexes: pg_ts_dict_pkey primary key btree (dict_name)
</pre>
<p>The dict_name column is the name of the dictionary, for example
'simple', 'en_stem' or 'ru_stem'. The dict_init column is a text
representation of a stored procedure to run for initialization of
that dictionary, for example 'snb_en_init(text)' or
'snb_ru_init(text)'. The initial configuration of tsearch2 had the
dict_init and dict_lexize columns as type oid. The patch mentioned
in the Installation Notes changes these types to regprocedure. The
data inserted, or updated can still be the oid of the stored
procedure. The representation is just different. This makes backup
and restore procedures much easier for tsearch2. The dict_init
option is used for options passed to the init function for the
stored procedure. In the cases of 'en_stem' or 'ru_stem' it is a
path to a stopword file for that dictionary, for example
'/usr/local/pgsql/share/english.stop'. This is however dictated by
the dictionary. ISpell dictionaries may require different options.
The dict_lexize column is another OID of a stored procedure to the
function used to lexize, for example 'snb_lexize(internal,
internal, integer)'. The dict_comment column is just a comment.</p>
<p>Next we will configure the use of a new dictionary based on
ISpell. We will assume you have ISpell installed on you machine.
(in /usr/local/lib)</p>
<p>There has been some confusion in the past as to which files are
used from ISpell. ISpell operates using a hash file. This is a
binary file created by the ISpell command line utility "buildhash".
This utility accepts a file containing the words from the
dictionary, and the affixes file and the output is the hash file.
The default installation of ISPell installs the english hash file
english.hash, which is the exact same file as american.hash. ISpell
uses this as the fallback dictionary to use.</p>
<p>This hash file is not what tsearch2 requires as the ISpell
interface. The file(s) needed are those used to create the hash.
Tsearch uses the dictionary words for morphology, so the listing is
needed not spellchecking. Regardless, these files are included in
the ISpell sources, and you can use them to integrate into
tsearch2. This is not complicated, but is not very obvious to begin
with. The tsearch2 ISpell interface needs only the listing of
dictionary words, it will parse and load those words, and use the
ISpell dictionary for lexem processing.</p>
<p>I found the ISPell make system to be very finicky. Their
documentation actually states this to be the case. So I just did
things the command line way. In the ISpell source tree under
languages/english there are several files in this directory. For a
complete description, please read the ISpell README. Basically for
the english dictionary there is the option to create the small,
medium, large and extra large dictionaries. The medium dictionary
is recommended. If the make system is configured correctly, it
would build and install the english.has file from the medium size
dictionary. Since we are only concerned with the dictionary word
listing ... it can be created from the /languages/english directory
with the following command:</p>
<pre>
sort -u -t/ +0f -1 +0 -T /usr/tmp -o english.med english.0 english.1
</pre>
<p>This will create a file called english.med. You can copy this
file to whever you like. I placed mine in /usr/local/lib so it
coincides with the ISpell hash files. You can now add the tsearch2
configuration entry for the ISpell english dictionary. We will also
continue to use the english word stop file that was installed for
the en_stem dictionary. You could use a different one if you like.
The ISpell configuration is based on the "ispell_template"
dictionary installed by default with tsearch2. We will use the OIDs
to the stored procedures from the row where the dict_name =
'ispell_template'.</p>
<pre>
INSERT INTO pg_ts_dict
(SELECT 'en_ispell',
dict_init,
'DictFile="/usr/local/lib/english.med",'
'AffFile="/usr/local/lib/english.aff",'
'StopFile="/usr/local/pgsql/share/contrib/english.stop"',
dict_lexize
FROM pg_ts_dict
WHERE dict_name = 'ispell_template');
</pre>
<p>Now that we have a dictionary we can specify it's use in a query
to get a lexem. For this we will use the lexize function. The
lexize function takes the name of the dictionary to use as an
argument. Just as the other tsearch2 functions operate. You will
need to stop your psql session and start it again in order for this
modification to take place.</p>
<pre>
SELECT lexize('en_ispell', 'program');
lexize
-----------
{program}
(1 row)
</pre>
<p>If you wanted to always use the ISpell english dictionary you
have installed, you can configure tsearch2 to always use a specific
dictionary.</p>
<pre>
SELECT set_curdict('en_ispell');
</pre>
<p>Lexize is meant to turn a word into a lexem. It is possible to
receive more than one lexem returned for a single word.</p>
<pre>
SELECT lexize('en_ispell', 'conditionally');
lexize
-----------------------------
{conditionally,conditional}
(1 row)
</pre>
<p>The lexize function is not meant to take a full string as an
argument to return lexems for. If you passed in an entire sentence,
it attempts to find that entire sentence in the dictionary. Since
the dictionary contains only words, you will receive an empty
result set back.</p>
<pre>
SELECT lexize('en_ispell', 'This is a senctece to lexize');
lexize
--------
(1 row)
If you parse a lexem from a word not in the dictionary, then you will receive an empty result. This makes sense because the word "tsearch" is not in the english dictionary. You can create your own additions to the dictionary if you like. This may be useful for scientific or technical glossaries that need to be indexed. SELECT lexize('en_ispell', 'tsearch'); lexize -------- (1 row)
</pre>
<p>This is not to say that tsearch will be ignored when adding text
information to the the tsvector index column. This will be
explained in greater detail with the table pg_ts_cfgmap.</p>
<p>Next we need to set up the configuration for mapping the
dictionay use to the lexxem parsings. This will be done by altering
the pg_ts_cfgmap table. We will insert several rows, specifying to
use the new dictionary we installed and configured for lexizing
within tsearch2. There are several type of lexims we would be
concerned with forcing the use of the ISpell dictionary.</p>
<pre>
INSERT INTO pg_ts_cfgmap (ts_name, tok_alias, dict_name)
VALUES ('default_english', 'lhword', '{en_ispell,en_stem}');
INSERT INTO pg_ts_cfgmap (ts_name, tok_alias, dict_name)
VALUES ('default_english', 'lpart_hword', '{en_ispell,en_stem}');
INSERT INTO pg_ts_cfgmap (ts_name, tok_alias, dict_name)
VALUES ('default_english', 'lword', '{en_ispell,en_stem}');
</pre>
<p>We have just inserted 3 records to the configuration mapping,
specifying that the lexem types for "lhword, lpart_hword and lword"
are to be stemmed using the 'en_ispell' dictionary we added into
pg_ts_dict, when using the configuration ' default_english' which
we added to pg_ts_cfg.</p>
<p>There are several other lexem types used that we do not need to
specify as using the ISpell dictionary. We can simply insert values
using the 'simple' stemming process dictionary.</p>
<pre>
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'url', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'host', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'sfloat', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'uri', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'int', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'float', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'email', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'word', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'hword', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'nlword', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'nlpart_hword', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'part_hword', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'nlhword', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'file', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'uint', '{simple}');
INSERT INTO pg_ts_cfgmap
VALUES ('default_english', 'version', '{simple}');
</pre>
<p>Our addition of a configuration for 'default_english' is now
complete. We have successfully created a new tsearch2
configuration. At the same time we have also set the new
configuration to be our default for en_US locale.</p>
<pre>
SELECT to_tsvector('default_english',
'learning tsearch is like going to school');
to_tsvector
--------------------------------------------------
'go':5 'like':4 'learn':1 'school':7 'tsearch':2
SELECT to_tsvector('learning tsearch is like going to school');
to_tsvector
--------------------------------------------------
'go':5 'like':4 'learn':1 'school':7 'tsearch':2
(1 row)
</pre>
<p>Notice here that words like "tsearch" are still parsed and
indexed in the tsvector column. There is a lexem returned for the
word becuase in the configuration mapping table, we specify words
to be used from the 'en_ispell' dictionary first, but as a fallback
to use the 'en_stem' dictionary. Therefore a lexem is not returned
from en_ispell, but is returned from en_stem, and added to the
tsvector.</p>
<pre>
SELECT to_tsvector('learning tsearch is like going to computer school');
to_tsvector
---------------------------------------------------------------------------
'go':5 'like':4 'learn':1 'school':8 'compute':7 'tsearch':2 'computer':7
(1 row)
</pre>
<p>Notice in this last example I added the word "computer" to the
text to be converted into a tsvector. Because we have setup our
default configuration to use the ISpell english dictionary, the
words are lexized, and computer returns 2 lexems at the same
position. 'compute':7 and 'computer':7 are now both indexed for the
word computer.</p>
<p>You can create additional dictionary lists, or use the extra
large dictionary from ISpell. You can read through the ISpell
documents, and source tree to make modifications as you see
fit.</p>
<p>In the case that you already have a configuration set for the
locale, and you are changing it to your new dictionary
configuration. You will have to set the old locale to NULL. If we
are using the 'C' locale then we would do this:</p>
<pre>
UPDATE pg_ts_cfg SET locale=NULL WHERE locale = 'C';
</pre>
<p>That about wraps up the configuration of tsearch2. There is much
more you can do with the tables provided. This was just an
introduction to get things working rather quickly.</p>
<h3>ADDING NEW DICTIONARIES TO TSEARCH2</h3>
<p>To aid in the addition of new dictionaries to the tsearch2
module you can use another additional module in combination with
tsearch2. The gendict module is included into tsearch2 distribution
and is available from gendict/ subdirectory.</p>
<p>I will not go into detail about installation and instructions on
how to use gendict to it's fullest extent right now. You can read
the README.gendict ... it has all of the instructions and
information you will need.</p>
<h3>BACKING UP AND RESTORING DATABASES THAT FEATURE TSEARCH2</h3>
<p><strong>Never rely on anyone elses instructions to backup and
restore a database system, always develop and understand your own
methodology, and test it numerous times before you need to do it
for real.</strong></p>
<p>The backup and restore procedure has changed over time. This is
not meant to be the bible for tsearch2 back up and restore. Please
read all sections so you have a complete understanding of some
backup and restore issues. Please test your own procedures, and do
not rely on these instructions solely.</p>
<p>If you come accross some issues in your own procedures, please
feel free to bring the question up on the Open-FTS, and PostgreSQL
mailing lists.</p>
<h3>ORIGINAL BACKUP PROCEDURES</h3>
<p>Originally, tsearch2 had problems when using the pg_dump, and or
the pg_dumpall utilities. The problem lies within the original use
of OIDs for column types. Since OIDs are not consistent accross
pg_dumps, when you reload the data values into the pg_ts_dict
table, for example, those oids no longer point to anything. You
would then end up trying to use a "broken" tsearch2
configuration.</p>
<p>The solution was to backup and restore a database using the
tsearch2 module into small unique parts, and then load them in the
correct order. You would have to edit the schema and remove the
tsearch stored procedure references in the sql file. You would have
to load your global objects, then the tsearch2 objects. You had to
re-create the tsearch module before restoring your schema so no
conflicts would arise. Then you could restore your data (all
schemas, and types needed for the data were now available).</p>
<p><strong>The original backup instructions were as
follows</strong></p>
<p>1) Backup any global database objects such as users and groups
(this step is usually only necessary when you will be restoring to
a virgin system)</p>
<pre>
pg_dumpall -g &gt; GLOBALobjects.sql
</pre>
<p>2) Backup the full database schema using pg_dump</p>
<pre>
pg_dump -s DATABASE &gt; DATABASEschema.sql
</pre>
<p>3) Backup the full database using pg_dump</p>
<pre>
pg_dump -Fc DATABASE &gt; DATABASEdata.tar
</pre>
<p><strong>The original restore procedures were as
follows</strong></p>
<p>1) Create the blank database</p>
<pre>
createdb DATABASE
</pre>
<p>2) Restore any global database objects such as users and groups
(this step is usually only necessary when you will be restoring to
a virgin system)</p>
<pre>
psql DATABASE &lt; GLOBALobjects.sql
</pre>
<p>3) Create the tsearch2 objects, functions and operators</p>
<pre>
psql DATABASE &lt; tsearch2.sql
</pre>
<p>4) Edit the backed up database schema and delete all SQL
commands which create tsearch2 related functions, operators and
data types, BUT NOT fields in table definitions that specify
tsvector types. If your not sure what these are, they are the ones
listed in tsearch2.sql. Then restore the edited schema to the
database</p>
<pre>
psql DATABASE &lt; DATABASEschema.sql
</pre>
<p>5) Restore the data for the database</p>
<pre>
pg_restore -N -a -d DATABASE DATABASEdata.tar
</pre>
<p>If you get any errors in step 4, it will most likely be because
you forgot to remove an object that was created in tsearch2.sql.
Any errors in step 5 will mean the database schema was probably
restored wrongly.</p>
<p><strong>Issues with this procedure</strong></p>
<p>As I mentioned before, it is vital that you test out your own
backup and restore procedures. These procedures were originally
adopted from this document's orignal author. Robert John Shepherd.
It makes use of the pg_dump custom archive functionality. I am not
that familiar with the formatting output of pg_dump, and using
pg_restore. I have always had the luxury of using text files
(Everything is DATABASE.sql).</p>
<p>One issue not forseen in the case of using a binary dump is the
when you have added more than the default tsearch2 configurations.
Upon reload of the data it will fail due to duplicate primary keys.
If you load the tsearch2 module, and then delete the data loaded by
tsearch2 into the configuration tables, the data will restore. The
configurations are incorrect because you can not remove the data
using OID references from the custom archive.</p>
<p>It would be very simple to fix this problem if the data was not
in an archive format. I do believe all of your data would have been
restored properly and you can get things working fairly easy. All
one would have to do is create the configurations as in the
tsearch2.sql file. And then create your custom configurations
again.</p>
<p>I have read in the pg_dump man page that if the tar archive
format is used, it is possible to limit which data is restored
using pg_restore. If anyone has more experience with pg_dump
archives, and pg_restore. Please feel free to test and contribute
your procedure(s).</p>
<h3>CURRENT BACKUP AND RESTORE PROCEDURES</h3>
<p>Currently a backup and restore of a database using the tsearch2
module can be quite simple. If you have applied the patch mentioned
in the installation instructions prior to tsearch2 installation.
This patch removes the use of the oid column. The text
representation for the stored procedures used are dumped with the
data and the restoration of the data works seemlessly.</p>
<p>1) to backup the database</p>
<pre>
pg_dump DATABASE &gt; DATABASE.sql
</pre>
<p>1) to restore the database</p>
<pre>
createdb DATABASE
psql -d DATABASE -f DATABASE.sql
</pre>
<p>This procedure is now like any normal backup and restore
procedure. I can say whether this has been proven using the pg_dump
archive, and restoring with pg_restore. In theory there should be
no problems with any format after the patch is applied.</p>
<p>This restoration procedure should never be an issue with the
patch applied to version 8.0 of PostgreSQL. Only versions 7.3 and
7.4 are affected. You can avoid any troubles by applying the patch
prior to installation, or running the SQL script provided to live
database before backup and restoring is done.</p>
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