Custom analyzers in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a custom analyzer with lowercase and stop filters

Given the following Elasticsearch analyzer configuration and input text, what is the output tokens after analysis?

Elasticsearch

{
  "analysis": {
    "analyzer": {
      "my_custom_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filter": ["lowercase", "stop"]
      }
    },
    "filter": {
      "stop": {
        "type": "stop",
        "stopwords": ["the", "is"]
      }
    }
  }
}

Input text: "The Quick Brown Fox is Jumping"

A ["quick", "brown", "fox", "jumping"]

B ["the", "quick", "brown", "fox", "jumping"]

C ["quick", "brown", "fox", "is", "jumping"]

D ["The", "Quick", "Brown", "Fox", "Jumping"]

💡 Hint

Remember that the lowercase filter converts all tokens to lowercase and the stop filter removes specified stopwords.

The tokenizer splits the text into tokens. The lowercase filter converts all tokens to lowercase. The stop filter removes the words "the" and "is". So the output tokens are ["quick", "brown", "fox", "jumping"].

🧠 Conceptual

intermediate

Purpose of a custom analyzer in Elasticsearch

What is the main purpose of creating a custom analyzer in Elasticsearch?

A To store data in a custom format in Elasticsearch

B To create custom visualizations in Kibana

C To define a specific way to tokenize and filter text for indexing and searching

D To manage user access and permissions

💡 Hint

Think about how Elasticsearch processes text for search.

Custom analyzers let you control how text is broken into tokens and how those tokens are filtered before indexing and searching, improving search relevance.

🔧 Debug

advanced

Identify the error in this custom analyzer configuration

What error will occur when trying to create this analyzer in Elasticsearch?

Elasticsearch

{
  "analysis": {
    "analyzer": {
      "my_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filter": ["lowercase", "nonexistent_filter"]
      }
    }
  }
}

A Elasticsearch will raise an error because 'nonexistent_filter' is not defined

B The analyzer will work but ignore 'nonexistent_filter'

C The analyzer will use the default filter instead

D The analyzer will create a new filter named 'nonexistent_filter' automatically

💡 Hint

Check if all filters used in the analyzer are defined in the analysis settings.

Elasticsearch requires all filters used in an analyzer to be defined. Using an undefined filter causes an error.

📝 Syntax

advanced

Correct syntax for defining a custom analyzer with a synonym filter

Which option correctly defines a custom analyzer that uses a synonym filter named 'my_synonyms'?

A

{
  "analysis": {
    "analyzer": {
      "synonym_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filters": ["lowercase", "my_synonyms"]
      }
    },
    "filter": {
      "my_synonyms": {
        "type": "synonym",
        "synonyms": ["quick,fast", "jumps,leaps"]
      }
    }
  }
}

B

{
  "analysis": {
    "analyzer": {
      "synonym_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filter": ["lowercase", "my_synonyms"]
      }
    },
    "filter": {
      "my_synonyms": {
        "type": "synonym",
        "synonyms": ["quick,fast", "jumps,leaps"]
      }
    }
  }
}

C

{
  "analysis": {
    "analyzer": {
      "synonym_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filter": ["lowercase", "my_synonyms"]
      }
    },
    "filters": {
      "my_synonyms": {
        "type": "synonym",
        "synonyms": ["quick,fast", "jumps,leaps"]
      }
    }
  }
}

D

{
  "analysis": {
    "analyzer": {
      "synonym_analyzer": {
        "type": "custom",
        "tokenizer": "standard",
        "filter": ["lowercase", "my_synonyms"]
      }
    },
    "filter": {
      "my_synonyms": {
        "type": "synonym",
        "synonym": ["quick,fast", "jumps,leaps"]
      }
    }
  }
}

💡 Hint

Check the spelling of keys: 'filter' vs 'filters' and 'synonyms' vs 'synonym'.

The correct key for filters is 'filter' (singular) inside the analyzer. The filter definitions must be under 'filter' (not 'filters'). The synonym filter requires the key 'synonyms' (plural) for the list of synonyms.

🚀 Application

expert

Number of tokens produced by a custom analyzer with pattern tokenizer and lowercase filter

Given this custom analyzer configuration, how many tokens will be produced when analyzing the text "Hello, World! Welcome to Elasticsearch."?

Elasticsearch

{
  "analysis": {
    "analyzer": {
      "pattern_analyzer": {
        "type": "custom",
        "tokenizer": "pattern",
        "filter": ["lowercase"]
      }
    },
    "tokenizer": {
      "pattern": {
        "type": "pattern",
        "pattern": "\\W+"
      }
    }
  }
}

A 7

B 6

C 4

D 5

💡 Hint

The pattern tokenizer splits text by non-word characters (\W+). Count the resulting tokens after splitting.

The pattern '\\W+' splits on any sequence of non-word characters. The text splits into: ['Hello', 'World', 'Welcome', 'to', 'Elasticsearch']. After lowercase filter, tokens remain the same count. So total tokens = 5.