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ElasticSearch Blueprints

You're reading from   ElasticSearch Blueprints A practical project-based guide to generating compelling search solutions using the dynamic and powerful features of Elasticsearch

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Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781783984923
Length 192 pages
Edition 1st Edition
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Toc

Table of Contents (10) Chapters Close

Preface 1. Google-like Web Search 2. Building Your Own E-Commerce Solution FREE CHAPTER 3. Relevancy and Scoring 4. Managing Relational Content 5. Analytics Using Elasticsearch 6. Improving the Search Experience 7. Spicing Up a Search Using Geo 8. Handling Time-based Data Index

Substring matching


By now, you would have noticed that only exact word matches are taken as result qualifiers. What if I want an incomplete token or word to be matched?

For example, when I search for titani, it should match against titanium because titani is an incomplete form of titanium.

For this kind of purpose, it would be best to use the EdgeNGram-based analyzer.

First let's create the analyzer:

curl -X PUT "http://localhost:9200/my-index" -d '{
  "index": {
    "number_of_shards": 1,
    "number_of_replicas": 1
  },
  "analysis": {
    "filter": {
      "ngram": {
        "type": "edgeNgram",
        "min_gram": 1,
  "max_gram" : 50
      }
    },
    "analyzer": {
      "NGramAnalyzer": {
        "type": "custom",
        "tokenizer" : "standard", 
        "filter": "ngram"
      }
    }
  } 
}'  

Here, we are creating an edge NGram filter, which creates substrings of all the tokens from one end of the token with the minimum length of two and the maximum length of 50.

Let's see what its...

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