Synonym handling in Elasticsearch - Mini Project: Build & Apply

Synonym Handling in Elasticsearch

📖 Scenario: You are building a search feature for an online bookstore. You want users to find books even if they use different words that mean the same thing. For example, searching for "sci-fi" should also find books tagged with "science fiction".

🎯 Goal: Create an Elasticsearch index with a synonym filter so that searches recognize synonyms. You will define synonyms, apply them in an analyzer, and then create the index using that analyzer.

📋 What You'll Learn

Create a synonym filter named book_synonym_filter with these synonyms: "sci-fi, science fiction" and "ya, young adult"

Create a custom analyzer named book_synonym_analyzer that uses the standard tokenizer and the book_synonym_filter

Create an index named books that uses the book_synonym_analyzer for the title field

💡 Why This Matters

🌍 Real World

Synonym handling improves search results by matching different words with the same meaning, making search more user-friendly and effective.

💼 Career

Understanding how to configure analyzers and filters in Elasticsearch is essential for roles involving search engine development, data indexing, and improving user search experience.

1

Define the synonym filter

Create a filter called book_synonym_filter with type synonym and include these synonyms exactly: "sci-fi, science fiction" and "ya, young adult".

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        // Define the synonym filter here
      }
    }
  }
}

Need a hint?

Use the filter section inside analysis to define book_synonym_filter with the synonym type and list the synonyms as an array.

2

Create the synonym analyzer

Add an analyzer named book_synonym_analyzer that uses the standard tokenizer and applies the book_synonym_filter filter.

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        "book_synonym_filter": {
          "type": "synonym",
          "synonyms": [
            "sci-fi, science fiction",
            "ya, young adult"
          ]
        }
      },
      "analyzer": {
        // Add book_synonym_analyzer here
      }
    }
  }
}

Need a hint?

Inside analysis, add an analyzer section. Define book_synonym_analyzer with the standard tokenizer and apply the book_synonym_filter in the filter list.

3

Create the books index with the analyzer

Create an index named books with the book_synonym_analyzer applied to the title field in the mappings.

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        "book_synonym_filter": {
          "type": "synonym",
          "synonyms": [
            "sci-fi, science fiction",
            "ya, young adult"
          ]
        }
      },
      "analyzer": {
        "book_synonym_analyzer": {
          "tokenizer": "standard",
          "filter": ["book_synonym_filter"]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "title": {
        // Apply the book_synonym_analyzer here
      }
    }
  }
}

Need a hint?

In the mappings section, set the title field to type text and assign the book_synonym_analyzer as its analyzer.

4

Complete the index creation JSON

Ensure the JSON includes the settings with analysis filters and analyzers, and the mappings with the title field using the book_synonym_analyzer. This completes the Elasticsearch index setup for synonym handling.

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        "book_synonym_filter": {
          "type": "synonym",
          "synonyms": [
            "sci-fi, science fiction",
            "ya, young adult"
          ]
        }
      },
      "analyzer": {
        "book_synonym_analyzer": {
          "tokenizer": "standard",
          "filter": ["book_synonym_filter"]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "title": {
        "type": "text",
        "analyzer": "book_synonym_analyzer"
      }
    }
  }
}
# This is the complete JSON for the index creation

Need a hint?

Review the entire JSON to confirm it has all parts: settings with filters and analyzers, and mappings with the title field using the synonym analyzer.