Installing and Configuring Elasticsearch for Site Search with IK Analyzer and Node.js Client

Installation Elasticsearch

The simplest deployment uses the Elasticsearch Dockerfile, but the author installs it manually on Ubuntu 14.04.3 LTS, version 2.1.1. First ensure Java is present:

sudo apt-get install openjdk-7-jre-headless

Download and unzip the package, rename the directory to ~/es_root , make the binary executable, and start the service:

cd ~/es_root/bin/
chmod a+x elasticsearch
./elasticsearch

Verify with:

curl -XGET http://127.0.0.1:9200/?pretty

Adjust ~/es_root/config/elasticsearch.yml to bind to all interfaces for debugging (not recommended in production):

network.bind_host: "0.0.0.0"
network.publish_host: _non_loopback:ipv4_

Install IK Analysis

Elasticsearch’s default tokenizer splits Chinese characters individually, so the IK analyzer plugin is required. Download the matching version, compile with Maven, and copy the built zip into the plugins directory:

wget -c https://github.com/medcl/elasticsearch-analysis-ik/archive/master.zip
unzip master.zip
sudo apt-get install maven
cd elasticsearch-analysis-ik-master/
mvn package
mkdir -p ~/es_root/plugins/ik/
unzip target/releases/elasticsearch-analysis-ik-1.6.2.zip -d ~/es_root/plugins/ik/

Copy the configuration files to ~/es_root/config/ik . After restarting Elasticsearch you should see:

[plugins] [Libra] loaded [elasticsearch-analysis-ik]

Configure Synonyms

Add a custom analyzer that combines the IK tokenizer with a synonym filter by editing ~/es_root/config/elasticsearch.yml :

index:
  analysis:
    analyzer:
      ik_syno:
        type: custom
        tokenizer: ik_max_word
        filter: [my_synonym_filter]
      ik_syno_smart:
        type: custom
        tokenizer: ik_smart
        filter: [my_synonym_filter]
    filter:
      my_synonym_filter:
        type: synonym
        synonyms_path: analysis/synonym.txt

Create ~/es_root/config/analysis/synonym.txt with entries such as:

ua,user-agent,userAgent
js,javascript
internet explore=>ie

Use JavaScript API

Install the official Node.js client:

npm install elasticsearch --save

Instantiate the client:

var elasticsearch = require('elasticsearch');
var client = new elasticsearch.Client({
  host: '10.211.55.23:9200',
  log: 'trace'
});

Both callback and promise styles are supported; the article uses promises for brevity.

Full‑Text Search

Create an index and mapping that uses the custom ik_syno analyzer for title , content , and tags fields:

client.indices.create({index : 'test'});
client.indices.putMapping({
  index : 'test',
  type : 'article',
  body : {
    article: {
      properties: {
        title: {type: 'string', term_vector: 'with_positions_offsets', analyzer: 'ik_syno', search_analyzer: 'ik_syno'},
        content: {type: 'string', term_vector: 'with_positions_offsets', analyzer: 'ik_syno', search_analyzer: 'ik_syno'},
        tags: {type: 'string', index: 'not_analyzed'},
        slug: {type: 'string'},
        update_date: {type: 'date', index: 'not_analyzed'}
      }
    }
  }
});

Index a sample document:

client.index({
  index : 'test',
  type : 'article',
  id : '100',
  body : {
    title : '什么是 JS？',
    slug :'what-is-js',
    tags : ['JS', 'JavaScript', 'TEST'],
    content : 'JS 是 JavaScript 的缩写！',
    update_date : '2015-12-15T13:05:55Z'
  }
});

Search with a simple query:

client.search({index : 'test', type : 'article', q : 'JS'});

For more advanced queries, the article provides a complex Query DSL that combines match clauses on title , content , tags , and slug with boosting, minimum‑should‑match thresholds, and result highlighting.

The author notes that the setup is a minimal example; production use should include more data, additional synonym files, and careful security configuration.