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<h2 class="title"><a id="analysis-ngram-tokenizer"></a>NGram Tokenizer<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.3/docs/reference/analysis/tokenizers/ngram-tokenizer.asciidoc">edit</a></h2>
</div></div></div>
<p>The <code class="literal">ngram</code> tokenizer first breaks text down into words whenever it encounters
one of a list of specified characters, then it emits
<a href="https://en.wikipedia.org/wiki/N-gram" class="ulink" target="_top">N-grams</a> of each word of the specified
length.</p>
<p>N-grams are like a sliding window that moves across the word - a continuous
sequence of characters of the specified length. They are useful for querying
languages that don’t use spaces or that have long compound words, like German.</p>
<h3><a id="_example_output_15"></a>Example output<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.3/docs/reference/analysis/tokenizers/ngram-tokenizer.asciidoc">edit</a></h3>
<p>With the default settings, the <code class="literal">ngram</code> tokenizer treats the initial text as a
single token and produces N-grams with minimum length <code class="literal">1</code> and maximum length
<code class="literal">2</code>:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST _analyze
{
"tokenizer": "ngram",
"text": "Quick Fox"
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/721.console"></div>
<p>The above sentence would produce the following terms:</p>
<div class="pre_wrapper lang-text">
<pre class="programlisting prettyprint lang-text">[ Q, Qu, u, ui, i, ic, c, ck, k, "k ", " ", " F", F, Fo, o, ox, x ]</pre>
</div>
<h3><a id="_configuration_16"></a>Configuration<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.3/docs/reference/analysis/tokenizers/ngram-tokenizer.asciidoc">edit</a></h3>
<p>The <code class="literal">ngram</code> tokenizer accepts the following parameters:</p>
<div class="informaltable">
<table border="0" cellpadding="4px">
<colgroup>
<col/>
<col/>
</colgroup>
<tbody valign="top">
<tr>
<td valign="top">
<p>
<code class="literal">min_gram</code>
</p>
</td>
<td valign="top">
<p>
Minimum length of characters in a gram. Defaults to <code class="literal">1</code>.
</p>
</td>
</tr>
<tr>
<td valign="top">
<p>
<code class="literal">max_gram</code>
</p>
</td>
<td valign="top">
<p>
Maximum length of characters in a gram. Defaults to <code class="literal">2</code>.
</p>
</td>
</tr>
<tr>
<td valign="top">
<p>
<code class="literal">token_chars</code>
</p>
</td>
<td valign="top">
<p>
<p>
Character classes that should be included in a token. Elasticsearch
will split on characters that don’t belong to the classes specified.
Defaults to <code class="literal">[]</code> (keep all characters).
</p>
<p>Character classes may be any of the following:</p>
<div class="ulist itemizedlist">
<ul class="itemizedlist">
<li class="listitem">
<code class="literal">letter</code> —  for example <code class="literal">a</code>, <code class="literal">b</code>, <code class="literal">ï</code> or <code class="literal">京</code>
</li>
<li class="listitem">
<code class="literal">digit</code> —  for example <code class="literal">3</code> or <code class="literal">7</code>
</li>
<li class="listitem">
<code class="literal">whitespace</code> —  for example <code class="literal">" "</code> or <code class="literal">"\n"</code>
</li>
<li class="listitem">
<code class="literal">punctuation</code> — for example <code class="literal">!</code> or <code class="literal">"</code>
</li>
<li class="listitem">
<code class="literal">symbol</code> —  for example <code class="literal">$</code> or <code class="literal">√</code>
</li>
</ul>
</div>
</p>
</td>
</tr>
</tbody>
</table>
</div>
<div class="tip admon">
<div class="icon"></div>
<div class="admon_content">
<p>It usually makes sense to set <code class="literal">min_gram</code> and <code class="literal">max_gram</code> to the same
value. The smaller the length, the more documents will match but the lower
the quality of the matches. The longer the length, the more specific the
matches. A tri-gram (length <code class="literal">3</code>) is a good place to start.</p>
</div>
</div>
<p>The index level setting <code class="literal">index.max_ngram_diff</code> controls the maximum allowed
difference between <code class="literal">max_gram</code> and <code class="literal">min_gram</code>.</p>
<h3><a id="_example_configuration_9"></a>Example configuration<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.3/docs/reference/analysis/tokenizers/ngram-tokenizer.asciidoc">edit</a></h3>
<p>In this example, we configure the <code class="literal">ngram</code> tokenizer to treat letters and
digits as tokens, and to produce tri-grams (grams of length <code class="literal">3</code>):</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "ngram",
"min_gram": 3,
"max_gram": 3,
"token_chars": [
"letter",
"digit"
]
}
}
}
}
}
POST my_index/_analyze
{
"analyzer": "my_analyzer",
"text": "2 Quick Foxes."
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/722.console"></div>
<p>The above example produces the following terms:</p>
<div class="pre_wrapper lang-text">
<pre class="programlisting prettyprint lang-text">[ Qui, uic, ick, Fox, oxe, xes ]</pre>
</div>
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