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MOD update readme
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Thomas Wilkerling
87
README.md
87
README.md
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</p>
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<h1></h1>
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<h3>Worlds fastest and most memory efficient full text search library with zero dependencies.</h3>
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<h3>World's fastest and most memory efficient full text search library with zero dependencies.</h3>
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When it comes to raw search speed <a href="https://jsperf.com/compare-search-libraries" target="_blank">FlexSearch outperforms every single searching library out there</a> and also provides flexible search capabilities like multi-word matching, phonetic transformations or partial matching. It also has the __most memory-efficient index__. Keep in mind that updating existing items from the index has a significant cost. When your index needs to be updated continuously then <a href="bulksearch/" target="_blank">BulkSearch</a> may be a better choice. FlexSearch also provides you a non-blocking asynchronous processing model as well as web workers to perform any updates on the index as well as queries through dedicated threads.
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@@ -206,8 +206,7 @@ var index = new FlexSearch({
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// default values:
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encode: "icase",
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mode: "forward",
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multi: false,
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mode: "ngram",
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async: false,
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cache: false
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});
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@@ -416,9 +415,49 @@ var index = FlexSearch.create()
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index.remove(0).update(1, 'foo').add(2, 'foobar');
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```
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#### Enable Contextual Index
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Create context-enabled index and also set the limit of relevance (depth):
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```js
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var index = new FlexSearch({
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encode: "icase",
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mode: "strict",
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depth: 3
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});
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```
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#### Use WebWorker (Browser only)
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Create worker-enabled index and also set the count of parallel threads:
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```js
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var index = new FlexSearch({
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encode: "icase",
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mode: "full",
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async: true,
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worker: 4
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});
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```
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Adding items to worker index as usual (async enabled):
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```js
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index.add(10025, "John Doe");
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```
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Perform search and simply pass in callback like:
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```js
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index.search("John Doe", function(results){
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// do something with array of results
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});
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```
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<a name="options"></a>
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## Options
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FlexSearch ist highly customizable. Make use of the the right options can really improve your results as well as memory economy or query time.
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<table>
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<tr></tr>
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<tr>
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@@ -436,7 +475,7 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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"full"
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</td>
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<td vertical-align="top">
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The <a href="#tokenizer">indexing mode (tokenizer)</a>.<br><br><br><br><br>
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The <a href="#tokenizer">indexing mode (tokenizer)</a>.<br>
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</td>
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</tr>
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<tr></tr>
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@@ -450,7 +489,7 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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"extra"<br>
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function()
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</td>
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<td>The encoding type.<br><br>Choose one of the <a href="#phonetic">built-ins</a> or pass a <a href="#flexsearch.encoder">custom encoding function</a>.<br><br><br><br></td>
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<td>The encoding type.<br><br>Choose one of the <a href="#phonetic">built-ins</a> or pass a <a href="#flexsearch.encoder">custom encoding function</a>.</td>
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</tr>
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<!--
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<tr></tr>
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true<br>
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false
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</td>
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<td>Enable multi word processing.<br><br></td>
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<td>Enable multi word processing.</td>
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</tr>
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-->
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<tr></tr>
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@@ -479,7 +518,7 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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true<br>
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false
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</td>
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<td>Enable/Disable caching.<br><br></td>
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<td>Enable/Disable caching.</td>
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</tr>
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<tr></tr>
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<tr>
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@@ -488,7 +527,7 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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true<br>
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false
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</td>
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<td>Enable/Disable asynchronous processing.<br><br></td>
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<td>Enable/Disable asynchronous processing.</td>
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</tr>
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<tr></tr>
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<tr>
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@@ -497,7 +536,7 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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false<br>
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{number}
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</td>
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<td>Enable/Disable and set count of running worker threads.<br><br></td>
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<td>Enable/Disable and set count of running worker threads.</td>
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</tr>
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<tr></tr>
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<tr>
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@@ -506,13 +545,15 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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false<br>
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{number}
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</td>
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<td>Enable/Disable contextual indexing and also sets relevance depth (experimental).<br><br></td>
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<td>Enable/Disable <a href="#contextual">contextual indexing</a> and also sets relevance depth (experimental).</td>
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</tr>
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</table>
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<a name="tokenizer"></a>
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## Tokenizer
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Tokenizer effects the required memory also as query time and flexibility of partial matches. Try to choose the most upper of these tokenizer which fits your needs:
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<table>
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<tr></tr>
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<tr>
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<td>* 1</td>
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</tr>
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<tr></tr>
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<tr>
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<td><b>"ngram"</b> (default)</td>
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<td>index words partially through phonetic n-grams</td>
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<td><b>foo</b>bar<br>foo<b>bar</b></td>
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<td>* n/3.5</td>
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</tr>
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<tr></tr>
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<tr>
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<td><b>"foward"</b></td>
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<td>incrementally index words in forward direction</td>
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<td>* 2n</td>
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</tr>
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<tr></tr>
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<tr>
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<td><b>"ngram"</b> (default)</td>
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<td>index words partially through phonetic n-grams</td>
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<td><b>foo</b>bar<br>foo<b>bar</b></td>
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<td>* n/4</td>
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</tr>
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<tr></tr>
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<tr>
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<td><b>"full"</b></td>
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<td>index every possible combination</td>
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<a name="phonetic"></a>
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## Phonetic Encoding
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Encoding effects the required memory also as query time and phonetic matches. Try to choose the most upper of these encoders which fits your needs, or pass in a <a href="#flexsearch.encoder">custom encoder</a>:
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<table>
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<tr></tr>
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<tr>
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@@ -613,9 +656,9 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
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</table>
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<a name="compare" id="compare"></a>
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#### Comparison
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#### Comparison (Matches)
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Reference String: __"Björn-Phillipp Mayer"__
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> Reference String: __"Björn-Phillipp Mayer"__
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<table>
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<tr></tr>
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@@ -725,13 +768,13 @@ Reference String: __"Björn-Phillipp Mayer"__
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<a name="memory" id="memory"></a>
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## Memory Usage
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__Note:__ The required memory depends on several options.
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The required memory for the index depends on several options:
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<table>
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<tr></tr>
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<tr>
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<td align="left">Encoding</td>
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<td align="left">Memory usage of every ~ 100,000 indexed words</td>
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<td align="left">Memory usage of every ~ 100,000 indexed word</td>
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</tr>
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<tr>
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<td>false</td>
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</tr>
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<tr>
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<td align="left">Mode</td>
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<td align="left">Multiplied with: (n = <u>average</u> length of all words)</td>
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<td align="left">Multiplied with: (n = <u>average</u> length of indexed words)</td>
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</tr>
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<tr>
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<td>"strict"</td>
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