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><H1
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><A
NAME="DATATYPE-TEXTSEARCH"
>8.11. Text Search Types</A
></H1
><A
NAME="AEN5853"
></A
><A
NAME="AEN5856"
></A
><P
> <SPAN
CLASS="PRODUCTNAME"
>PostgreSQL</SPAN
> provides two data types that
are designed to support full text search, which is the activity of
searching through a collection of natural-language <I
CLASS="FIRSTTERM"
>documents</I
>
to locate those that best match a <I
CLASS="FIRSTTERM"
>query</I
>.
The <TT
CLASS="TYPE"
>tsvector</TT
> type represents a document in a form suited
for text search, while the <TT
CLASS="TYPE"
>tsquery</TT
> type similarly represents
a query.
<A
HREF="textsearch.html"
>Chapter 12</A
> provides a detailed explanation of this
facility, and <A
HREF="functions-textsearch.html"
>Section 9.13</A
> summarizes the
related functions and operators.
</P
><DIV
CLASS="SECT2"
><H2
CLASS="SECT2"
><A
NAME="DATATYPE-TSVECTOR"
>8.11.1. <TT
CLASS="TYPE"
>tsvector</TT
></A
></H2
><A
NAME="AEN5870"
></A
><P
> A <TT
CLASS="TYPE"
>tsvector</TT
> value is a sorted list of distinct
<I
CLASS="FIRSTTERM"
>lexemes</I
>, which are words that have been
<I
CLASS="FIRSTTERM"
>normalized</I
> to make different variants of the same word look
alike (see <A
HREF="textsearch.html"
>Chapter 12</A
> for details). Sorting and
duplicate-elimination are done automatically during input, as shown in
this example:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT 'a fat cat sat on a mat and ate a fat rat'::tsvector;
tsvector
----------------------------------------------------
'a' 'on' 'and' 'ate' 'cat' 'fat' 'mat' 'rat' 'sat'</PRE
><P>
(As the example shows, the sorting is first by length and then
alphabetically, but that detail is seldom important.) To represent
lexemes containing whitespace or punctuation, surround them with quotes:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT $$the lexeme ' ' contains spaces$$::tsvector;
tsvector
-------------------------------------------
'the' ' ' 'lexeme' 'spaces' 'contains'</PRE
><P>
(We use dollar-quoted string literals in this example and the next one,
to avoid confusing matters by having to double quote marks within the
literals.) Embedded quotes and backslashes must be doubled:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT $$the lexeme 'Joe''s' contains a quote$$::tsvector;
tsvector
------------------------------------------------
'a' 'the' 'Joe''s' 'quote' 'lexeme' 'contains'</PRE
><P>
Optionally, integer <I
CLASS="FIRSTTERM"
>position(s)</I
>
can be attached to any or all of the lexemes:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT 'a:1 fat:2 cat:3 sat:4 on:5 a:6 mat:7 and:8 ate:9 a:10 fat:11 rat:12'::tsvector;
tsvector
-------------------------------------------------------------------------------
'a':1,6,10 'on':5 'and':8 'ate':9 'cat':3 'fat':2,11 'mat':7 'rat':12 'sat':4</PRE
><P>
A position normally indicates the source word's location in the
document. Positional information can be used for
<I
CLASS="FIRSTTERM"
>proximity ranking</I
>. Position values can
range from 1 to 16383; larger numbers are silently clamped to 16383.
Duplicate positions for the same lexeme are discarded.
</P
><P
> Lexemes that have positions can further be labeled with a
<I
CLASS="FIRSTTERM"
>weight</I
>, which can be <TT
CLASS="LITERAL"
>A</TT
>,
<TT
CLASS="LITERAL"
>B</TT
>, <TT
CLASS="LITERAL"
>C</TT
>, or <TT
CLASS="LITERAL"
>D</TT
>.
<TT
CLASS="LITERAL"
>D</TT
> is the default and hence is not shown on output:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT 'a:1A fat:2B,4C cat:5D'::tsvector;
tsvector
----------------------------
'a':1A 'cat':5 'fat':2B,4C</PRE
><P>
Weights are typically used to reflect document structure, for example
by marking title words differently from body words. Text search
ranking functions can assign different priorities to the different
weight markers.
</P
><P
> It is important to understand that the
<TT
CLASS="TYPE"
>tsvector</TT
> type itself does not perform any normalization;
it assumes that the words it is given are normalized appropriately
for the application. For example,
</P><PRE
CLASS="PROGRAMLISTING"
>select 'The Fat Rats'::tsvector;
tsvector
--------------------
'Fat' 'The' 'Rats'</PRE
><P>
For most English-text-searching applications the above words would
be considered non-normalized, but <TT
CLASS="TYPE"
>tsvector</TT
> doesn't care.
Raw document text should usually be passed through
<CODE
CLASS="FUNCTION"
>to_tsvector</CODE
> to normalize the words appropriately
for searching:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT to_tsvector('english', 'The Fat Rats');
to_tsvector
-----------------
'fat':2 'rat':3</PRE
><P>
Again, see <A
HREF="textsearch.html"
>Chapter 12</A
> for more detail.
</P
></DIV
><DIV
CLASS="SECT2"
><H2
CLASS="SECT2"
><A
NAME="DATATYPE-TSQUERY"
>8.11.2. <TT
CLASS="TYPE"
>tsquery</TT
></A
></H2
><A
NAME="AEN5901"
></A
><P
> A <TT
CLASS="TYPE"
>tsquery</TT
> value stores lexemes that are to be
searched for, and combines them using the boolean operators
<TT
CLASS="LITERAL"
>&</TT
> (AND), <TT
CLASS="LITERAL"
>|</TT
> (OR), and
<TT
CLASS="LITERAL"
>!</TT
> (NOT). Parentheses can be used to enforce grouping
of the operators:
</P><PRE
CLASS="PROGRAMLISTING"
> SELECT 'fat & rat'::tsquery;
tsquery
---------------
'fat' & 'rat'
SELECT 'fat & (rat | cat)'::tsquery;
tsquery
---------------------------
'fat' & ( 'rat' | 'cat' )
SELECT 'fat & rat & ! cat'::tsquery;
tsquery
------------------------
'fat' & 'rat' & !'cat'</PRE
><P>
In the absence of parentheses, <TT
CLASS="LITERAL"
>!</TT
> (NOT) binds most tightly,
and <TT
CLASS="LITERAL"
>&</TT
> (AND) binds more tightly than
<TT
CLASS="LITERAL"
>|</TT
> (OR).
</P
><P
> Optionally, lexemes in a <TT
CLASS="TYPE"
>tsquery</TT
> can be labeled with
one or more weight letters, which restricts them to match only
<TT
CLASS="TYPE"
>tsvector</TT
> lexemes with one of those weights:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT 'fat:ab & cat'::tsquery;
tsquery
------------------
'fat':AB & 'cat'</PRE
><P>
</P
><P
> Quoting rules for lexemes are the same as described above for
lexemes in <TT
CLASS="TYPE"
>tsvector</TT
>; and, as with <TT
CLASS="TYPE"
>tsvector</TT
>,
any required normalization of words must be done before putting
them into the <TT
CLASS="TYPE"
>tsquery</TT
> type. The <CODE
CLASS="FUNCTION"
>to_tsquery</CODE
>
function is convenient for performing such normalization:
</P><PRE
CLASS="PROGRAMLISTING"
>SELECT to_tsquery('Fat:ab & Cats');
to_tsquery
------------------
'fat':AB & 'cat'</PRE
><P>
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