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<h1>Namazu Tips</h1>
<hr>
<h2>Table of contents</h2>
<ul>
<li><a href="#indexing">Fast indexing</a></li>
<li><a href="#saving-memory">Saving memory for indexing</a></li>
<li><a href="#weight">Score weighting by HTML elements</a></li>
<li><a href="#html">HTML processing</a></li>
<li><a href="#line-adjustment">Line Adjustment</a></li>
<li><a href="#digest">HTML documents digest</a></li>
<li><a href="#mailnews">Mail/News Digest</a></li>
<li><a href="#symbol">Symbol handling</a></li>
<li><a href="#phrase">(Pseudo) Phrase searching</a></li>
<li><a href="#update-index">Updating index for updated
documents and/or deleted documents</a></li>
</ul>
<h2><a name="indexing">Fast indexing</a></h2>
<ul>
<li>Use Perl Modules<br>
To handle Japanese documents, using NKF, KAKASI (or ChaSen, MeCab)
Perl modules makes 1.5 - 2 times faster.
<ul>
<li><a href="ftp://ftp.ie.u-ryukyu.ac.jp/pub/software/kono/nkf171.shar">NKF</a></li>
<li><a href="http://www.daionet.gr.jp/~knok/kakasi/">Text::Kakasi</a></li>
<li><a href="http://www.daionet.gr.jp/~knok/chasen/">Text::ChaSen1</a></li>
<li><a href="http://mecab.sourceforge.net/src/">MeCab</a></li>
</ul>
</li>
<li>Specify <code>--media-type=mtype</code> option<br>
mknmz uses File-MMagic module to automatically identify the
document type. If you know the document type of target
files in advance, you can avoid the automatic document
identification processing by specifying the
<code>--media-type=mtype</code> option. By doing so, you can
gain 10-20% speed improvement.
<br>
If the target file is Mail/News, you can use
<code>--mailnews</code> instead of
<code>--media-type=message/rfc822</code>. Similarly, if the
target file is MHonArc, you can use <code>--mhonarc</code>
instead of <code>--media-type='text/html;
x-type=mhonarc'</code>.
</li>
<li>Increase the value of <code>$ON_MEMORY_MAX</code> in mknmzrc<br>
By default, <code>$ON_MEMORY_MAX</code> is set to 5
MB. Through this value, mknmz limits the amounts of
documents processed in memory. If you use a machine with 1
GB memory, you will have no trouble setting
<code>$ON_MEMORY_MAX</code> to 100 MB. By doing so, the
number of times to write to working files will be reduced.
</li>
<li>Use fast computer<br>
Namazu is effective when you use a fast computer that has <br>
fast CPU + large memory + fast HDD . Do not forget to change
$ON_MEMORY_MAX.
</li>
</ul>
<h2><a name="saving-memory">Saving memory for indexing</a></h2>
<p>
Indexing takes a lot of memory. If you encounter "Out of
memory!" error at runtime of mknmz, the following
precautions can be considered.
</p>
<ul>
<li>Decrease the value of $ON_MEMORY_MAX in mknmzrc<br>
By default, <code>$ON_MEMORY_MAX</code> is set to 5
MB. This value assumes your machine has 64 MB memory. If your
machine have less memory, decrease this.
</li>
<li>Use --checkpoint option for mknmz<br>
mknmz limits the amounts of documents processed in memory
through $ON_MEMORY_MAX in mknmzrc. And mknmz writes
temporary files when the size of loaded documents reaches
the value.
Using --checkpoint option makes mknmz re-exec itself at
this time. As a result, the size of mknmz's process
decreases considerably. Use top command to see behavior if
you are curious.
</li>
</ul>
<h2><a name="weight">Score weighting by HTML elements</a></h2>
<p>
By default, the following rules are applied for score
weighting. These values are decided empirically, and has no
theoretical foundations.
</p>
<ul>
<li><code><title> 16</code></li>
<li><code><h1> 8</code></li>
<li><code><h2> 7</code></li>
<li><code><h3> 6</code></li>
<li><code><h4> 5</code></li>
<li><code><h5> 4</code></li>
<li><code><h6> 3</code></li>
<li><code><a> 4</code></li>
<li><code><strong>, <em>, <code>, <kbd>, <samp>, <cite>, <var> 2</code></li>
</ul>
<p>
Moreover, for <code><meta name="keywords"
content="</code><var>foo bar</var><code>"></code>
<var>foo bar</var> , score 32 is used.
</p>
<h2><a name="html">HTML processing</a></h2>
<p>
Namazu decodes &quot;, &amp;,&lt;, &gt; as
well as named and numbered entity in &#9-10 and
&#32-126. Since the internal encoding is
EUC-JP, the right half of ISO-8859-1 (0x80-0xff) cannot be
used. By the same reason, numbered entity in UCS-4
cannot be used.
</p>
<h2><a name="line-adjustment">Line Adjustment</a></h2>
<p>
Spaces, tabs at the beginning and the end of lines and >
| # : at the beginning are removed. If the line ends with a
Japanese character, the newline code will be ignored. (This
prevents segmentation of Japanese words at the end of line.)
These processing will be effective particularly for Mail
files. Moreover, recovery of English hyphenation will be
handled.
</p>
<h2><a name="digest">HTML documents digest</a></h2>
<p>
HTML defines the structure of documents. A simple digest can
be made by using the heading information of documents
defined by <h[1-6]>. By default, the length of digest
is set to 200 characters. If words from the heading are not
enough, more words are supplemented from the beginning of
the documents. If the target is text file, the first 200
characters of the documents are simply used.
</p>
<h2><a name="mailnews">Mail/News Digest</a></h2>
<p>
When dealing Mail/News files, quotation indicators as in
(foo@example.jp wrote:"), quotation bodies beginning, for
example, with <code>></code> are not included in the
Mail/News digest. Note that these messages are not included
in the digests, but are included in the search targets.
</p>
<h2><a name="symbol">Symbol handling</a></h2>
<p>
Symbol handling is rather a difficult task. Consider a
sentence <code>(foo is bar.)</code> . If we separate it with
spaces, <code>"(foo", "is", "bar.)"</code> will be indexed
and foo or bar cannot be searched.
</p>
<p>
To solve this problem, the easiest solution is to remove all
the symbols. However, we sometimes wish to search words that
has symbols as in <code>.emacs, TCP/IP</code> . For a
symbol-embedded string "<code>tcp/ip</code>", Namazu
decomposes it into 3 terms <code>"tcp/ip", "tcp",
"ip"</code> and registers independently.
</p>
<p>
For <code>(tcp/ip)</code>, Namazu decomposes it into 4 terms
<code>"(tcp/ip)", "tcp/ip", "tcp", "ip"</code> . Note that
no recursive processing is done, <code>((tcp/ip))</code>
will be decomposed into <code>"((tcp/ip))", "(tcp/ip)",
"tcp", "ip"</code>. The indexes for the first example
<code>(foo is bar.)</code> will be separated as
<code>"(foo", "foo", "is", "bar.)", "bar.", "bar"</code>, so
foo or bar can be searched.
</p>
<h2><a name="phrase">(Pseudo) Phrase searching</a></h2>
<p>
A straight-forward phrase searching implementation will lead
to an unacceptable index size. Namazu converts words into
hash values to reduce the index size.
</p>
<p>
If the search expression is given as a phrase "foo bar",
Namazu first performs AND searching for "foo" and "bar", and
then filters the results by the phrase information.
</p>
<p>
The phrase information is 2-word unit and is recorded as 16
bit hash value. For this reason, phrases with more than 2
words cannot be searched accurately. For a phrase searching
"foo bar baz", the documents only including "foo bar" and
"bar baz" will also be retrieved: </p>
<p>
...<br>
foo bar ...<br>
... bar baz
</p>
<p>
When collision of hash values occurred, wrong search results
may be returned. But, at least, words foo, bar, baz are all
included, for mistakenly retrieved documents.
</p>
<h2><a name="update-index">Updating index for updated
documents and/or deleted documents</a></h2>
<p>
Updating will be done by not updating/deleting of the
documents information from index, but recording the deleted
documents information. In other words, the index is intact
and simply records the ID of the document that is deleted in
addition to the original index.
</p>
<p>
If updates of an index caused by deleted/updated documents
are repeated, the information of deleted documents is
increased, and consequently the efficiency of index
recording will be lost. In this case, we recommend to clean
garbage by gcnmz.
</p>
<hr>
<p>
<a href="http://www.namazu.org/">Namazu Homepage</a>
</p>
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