<row>

<entry><function>substring_similarity(text, text)</function><indexterm><primary>substring_similarity</primary></indexterm></entry>

<entry><type>real</type></entry>

<entry>

Returns a number that indicates how similar the first string

to the most similar substring of the second string. The range of

the result is zero (indicating that the two strings are completely

dissimilar) to one (indicating that the first string is identical

to substring of the second substring).

</entry>

</row>

<row>

<entry><function>show_substring_limit()</function><indexterm><primary>show_substring_limit</primary></indexterm></entry>

<entry><type>real</type></entry>

<entry>

Returns the current similarity threshold used by the <literal>&lt;%</>

operator. This sets the minimum substring similarity between

two phrases.

</entry>

</row>

<row>

<entry><function>set_substring_limit(real)</function><indexterm><primary>set_substring_limit</primary></indexterm></entry>

<entry><type>real</type></entry>

<entry>

Sets the current substring similarity threshold that is used by

the <literal>&lt;%</> operator. The threshold must be between

0 and 1 (default is 0.6). Returns the same value passed in.

</entry>

</row>

<row>

<entry><type>text</> <literal>&lt;%</literal> <type>text</></entry>

<entry><type>boolean</type></entry>

<entry>

Returns <literal>true</> if its arguments have a substring similarity

that is greater than the current substring similarity threshold set by

<function>set_substring_limit</>.

</entry>

</row>

<para>

Also you can use an index on the <structfield>t</> column for substring

similarity. For example:

<programlisting>

SELECT t, substring_similarity('<replaceable>word</>', t) AS sml

FROM test_trgm

WHERE '<replaceable>word</>' &lt;% t

ORDER BY sml DESC, t;

</programlisting>

This will return all values in the text column that have a substring

which sufficiently similar to <replaceable>word</>, sorted from best

match to worst. The index will be used to make this a fast operation

even over very large data sets.

</para>