Token filters (lowercase, stemmer, synonym) in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this Elasticsearch analyzer test?

Given the following analyzer configuration and input text, what tokens will be produced after applying the lowercase and stemmer filters?

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "standard",
          "filter": ["lowercase", "english_stemmer"]
        }
      },
      "filter": {
        "english_stemmer": {
          "type": "stemmer",
          "language": "english"
        }
      }
    }
  }
}

Input text: "Running runners run quickly"

A ["run", "run", "run", "quickli"]

B ["run", "runner", "run", "quickli"]

C ["running", "runners", "run", "quickly"]

D ["running", "runner", "run", "quick"]

💡 Hint

Remember that the lowercase filter converts all tokens to lowercase before stemming. The stemmer reduces words to their root form.

The lowercase filter converts all tokens to lowercase: 'Running' -> 'running', 'runners' -> 'runners', etc. The English stemmer then reduces 'running' and 'runners' to 'run', and 'quickly' to 'quickli'. So the final tokens are ['run', 'run', 'run', 'quickli'].

🧠 Conceptual

intermediate

Which token filter is responsible for replacing words with their synonyms?

In Elasticsearch, which token filter should you use to replace tokens with their synonyms during analysis?

A synonym

B stop

C stemmer

D lowercase

💡 Hint

Think about the filter that changes words to other words with similar meaning.

The synonym token filter replaces tokens with their synonyms based on a defined synonym list. Lowercase converts tokens to lowercase, stemmer reduces words to their root form, and stop removes common words.

🔧 Debug

advanced

Why does this synonym filter configuration cause an error?

Examine the following synonym filter configuration. Why does Elasticsearch reject it with a syntax error?

Elasticsearch

{
  "filter": {
    "my_synonym": {
      "type": "synonym",
      "synonyms": [
        "quick, fast",
        "jumps, leap"
      ]
    }
  }
}

A The synonyms list must be a file path, not an inline array.

B The filter type 'synonym' is deprecated and must be 'synonym_graph'.

C The synonym filter requires a 'synonyms_path' property instead of 'synonyms'.

D The synonyms must be separated by '=>' instead of commas.

💡 Hint

Check the latest Elasticsearch documentation for synonym filter types.

In recent Elasticsearch versions, the 'synonym' filter type is deprecated and replaced by 'synonym_graph' for better support in multi-term synonyms. Using 'synonym' causes a syntax error.

📝 Syntax

advanced

Which option correctly defines a lowercase token filter in Elasticsearch?

Select the correct JSON snippet that defines a lowercase token filter named 'my_lowercase'.

A { "filter": { "my_lowercase": { "type": "LowerCase" } } }

B { "filter": { "my_lowercase": { "type": "lower_case" } } }

C { "filters": { "my_lowercase": { "type": "lowercase" } } }

D { "filter": { "my_lowercase": { "type": "lowercase" } } }

💡 Hint

Check the exact spelling and case sensitivity of the 'type' property.

The correct key is 'filter' (not 'filters'), and the type must be exactly 'lowercase' in lowercase letters without underscores. Option D matches this exactly.

🚀 Application

expert

How many tokens are produced by this analyzer with synonym and lowercase filters?

Given this analyzer configuration and input, how many tokens will be produced?

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "syn_lower_analyzer": {
          "tokenizer": "standard",
          "filter": ["lowercase", "my_synonym"]
        }
      },
      "filter": {
        "my_synonym": {
          "type": "synonym_graph",
          "synonyms": [
            "quick, fast",
            "jumps, leaps"
          ]
        }
      }
    }
  }
}

Input text: "The quick fox jumps"

A 4

B 5

C 6

D 7

💡 Hint

Remember that synonym_graph can produce multiple tokens for synonyms, increasing token count.

The input tokens after standard tokenizer and lowercase are: ['the', 'quick', 'fox', 'jumps']. The synonym_graph filter expands 'quick' to ['quick', 'fast'] and 'jumps' to ['jumps', 'leaps'], so tokens become: ['the', 'quick', 'fast', 'fox', 'jumps', 'leaps'], total 6 tokens.