Full text search

YDN-DB full text search module.

Full text search module for YDN-DB database library. This library build on top of two excellent full text search libraries, natural for stemming, normalization, analyzer and fullproof for tokenization.


  • Unicode-base tokenization supporting full language spectrum.
  • Stemming and phonetic normalization for English language.
  • Free text query base ranking with
    • index weight
    • implicit logical (and, or)
    • positional
  • Support exact match and prefix match.
  • Being based on YDN-DB, IndexedDB, WebSQL or localStorage storage mechanisms are supported.
  • Flexible index configuration using fulltext catalog.

API Reference

Use search method to query full text search.

db.search(catalog, query)

Documents are indexed during storing into the database using add or put methods.

Query format is free text, in which implicit and/or/near logic operator apply for each token. Use double quote for exact match, - to subtract from the result and * for prefix search.


  • {string} catalog Full text search catalog name, as defined in schema.
  • {string} query Free text query string.


{!ydn.db.Request} Returns a request object.

done: {Array} Return list of inverted index. An inverted index has the following attributes: storeName, primaryKey, score, tokens, representing for store name of original document, primary key of original document, match quality score and array of token objects. Token object has the following attributes: keyPath, value and loc representing key path of index of the original document, original word from the original document and array list of position of word in the document.

fail: {Error} If any one of deleting a key fail, fail callback is invoked, with the resulting error in respective elements.

progress: {Array} During index retrieval, raw inverted index are dispatched.


var schema = {
  fullTextCatalogs: [{
    name: 'name',
    lang: 'en',
      sources: [
          storeName: 'contact',
          keyPath: 'first'
    stores: [
        name: 'contact',
        autoIncrement: true
var db = new ydn.db.Storage('db name', schema);
db.put('contact', [{first: 'Jhon'}, {first: 'Collin'}]);
db.search('name', 'jon').done(function(x) {
  db.get(x[0].storeName, x[0].primaryKey).done(function(top) {

Full text catalog

Full text catalog is a logical grouping of one or more full-text indexes. It is defined in database initialization in database schema.


  • {string} name Full text catalog name.
  • {string=} lang Language. Stemming, word segmentation and phonetic normalization are language dependent. lang must be defined to index properly. Currently only en is well supported. For more languages, check out on natural project repo.
  • {Array} sources Full text indexes. Each index has source reference to original document by storeName and keyPath. The value of keyPath is the text to be indexed. weight factor is applied when ranking search result. This value is not stored in the database can be changed after indexing as well.

The following full text catalog index author name on first and last field of record value with weighting more on first.

var catalog = {
  name: 'author-name',
  lang: 'en',
  sources: [{
    storeName: 'author',
    keyPath: 'first',
    weight: 1.0
  }, {
    storeName: 'author',
    keyPath: 'last',
    weight: 0.8

Native full-text search on WebSQL

WebSQL support full text search via FTS3 extension on Chrome and Safari. The follow example illustrate full text search usage. Use virtual table to create full text index using porter tokenizer. Here is example from Nolan Lawson,

var db = openDatabase('fts_demo', 1, 'fts_demo', 5000000);

db.transaction(function (tx){
  function onReady() {
    var content = 'WebSQL has full-text search!';
    tx.executeSql('insert into doc values (?)', [content], function () {
      var terms = ['websql', 'text', 'search', 'searches', 'searching', 'indexeddb']
      terms.forEach(function (term) {
        tx.executeSql('select count(*) as count from doc where content match ?',
            [term], function (tx, res) {
          var count = res.rows.item(0).count;
          console.log(term, !!count);
  tx.executeSql('create virtual table doc using fts3(content text, tokenize=porter);', [], onReady, onReady);

Demo applications


  1. Closure library: http://closure-library.googlecode.com/svn/trunk/
  2. YDN-BASE: https://github.com/yathit/ydn-base.git
  3. YDN-DB: https://github.com/yathit/ydn-db.git
  4. fullproof: https://github.com/yathit/fullproof.git
  5. natural: https://github.com/yathit/natural.git

Build process

See detail build procedure in YDN-DB.

Collect all dependency using git or svn. Generate closure dependency using ant deps. Then you should able to run HTML test files in the source code folders. You should able to run example using raw js files. Use ant build for minification.


Kyaw Tun