Custom analyzers in Elasticsearch - Mini Project: Build & Apply

Create a Custom Analyzer in Elasticsearch

📖 Scenario: You are setting up a search engine for a small online bookstore. You want to improve search results by creating a custom analyzer that lowercases text and removes common English stopwords.

🎯 Goal: Build an Elasticsearch index with a custom analyzer that uses the standard tokenizer, lowercases all text, and removes English stopwords.

📋 What You'll Learn

Create an index called bookstore with custom analyzer settings

Define a custom analyzer named my_custom_analyzer

Use the standard tokenizer in the analyzer

Add lowercase and stop filters to the analyzer

Set the stop filter to use English stopwords

Print the analyzer settings to verify

💡 Why This Matters

🌍 Real World

Custom analyzers help improve search quality by controlling how text is broken down and filtered before searching.

💼 Career

Knowing how to create and configure custom analyzers is important for roles involving search engine setup, data indexing, and improving user search experience.

1

Create the initial index settings with an empty analyzer

Create an index called bookstore with settings that include an empty analysis object.

Elasticsearch

{
  "settings": {
    "analysis": {
      
    }
  }
}
# Your code here

Need a hint?

Start by creating the settings key with an analysis object inside it.

2

Add a custom analyzer named my_custom_analyzer

Inside settings.analysis, add an analyzer object with a custom analyzer named my_custom_analyzer that uses the standard tokenizer and an empty filter list.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_custom_analyzer": {
          "tokenizer": "standard",
          "filter": []
        }
      }
    }
  }
}
# Your code here

Need a hint?

Define the analyzer key and inside it add my_custom_analyzer with the standard tokenizer and an empty filter list.

3

Add lowercase and stop filters to the analyzer

Modify the my_custom_analyzer to include the lowercase and stop filters in the filter list. Also, add a filter object in analysis defining the stop filter with stopwords set to _english_.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_custom_analyzer": {
          "tokenizer": "standard",
          "filter": ["lowercase", "stop"]
        }
      },
      "filter": {
        "stop": {
          "type": "stop",
          "stopwords": "_english_"
        }
      }
    }
  }
}
# Your code here

Need a hint?

Add the lowercase and stop filters to the analyzer's filter list. Then define the stop filter with English stopwords in the filter object.

4

Print the analyzer settings to verify

Print the complete JSON settings for the bookstore index to verify the custom analyzer configuration.

Elasticsearch

print(settings)
# Your code here

Need a hint?

Use print(settings) to display the full JSON settings object.