Tokenizers (standard, whitespace, pattern) in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a standard tokenizer in Elasticsearch.

Elasticsearch

{
  "settings": {
    "analysis": {
      "tokenizer": {
        "my_tokenizer": {
          "type": "[1]"
        }
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Akeyword

Bstandard

Cpattern

Dwhitespace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'whitespace' instead of 'standard' when you want word boundaries.

Confusing 'pattern' tokenizer with 'standard' tokenizer.

The standard tokenizer is the default tokenizer in Elasticsearch that breaks text into terms on word boundaries.

2fill in blank

medium

Complete the code to define a whitespace tokenizer in Elasticsearch.

Elasticsearch

{
  "settings": {
    "analysis": {
      "tokenizer": {
        "my_ws_tokenizer": {
          "type": "[1]"
        }
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Awhitespace

Bpattern

Cstandard

Dkeyword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'standard' tokenizer when whitespace tokenizer is needed.

Confusing 'pattern' tokenizer with 'whitespace' tokenizer.

The whitespace tokenizer splits text only on whitespace characters, keeping punctuation attached to words.

3fill in blank

hard

Fix the error in the pattern tokenizer definition by completing the pattern field.

Elasticsearch

{
  "settings": {
    "analysis": {
      "tokenizer": {
        "my_pattern_tokenizer": {
          "type": "pattern",
          "pattern": "[1]"
        }
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

A\\d+

B\\w+

C\\s+

D\\S+

Attempts:

3 left

💡 Hint

Common Mistakes

Using '\w+' which matches word characters, not spaces.

Using '\d+' which matches digits, not spaces.

The pattern tokenizer uses a regular expression to split text. The pattern \s+ matches one or more whitespace characters, splitting text on spaces.

4fill in blank

hard

Fill both blanks to define a pattern tokenizer that splits on commas and spaces.

Elasticsearch

{
  "settings": {
    "analysis": {
      "tokenizer": {
        "comma_space_tokenizer": {
          "type": "[1]",
          "pattern": "[2]"
        }
      }
    }
  }
}

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Apattern

B\\s*,\\s*

C\\s+

Dwhitespace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'whitespace' type with a pattern field.

Using a pattern that does not match commas.

The tokenizer type must be pattern to use a regex pattern. The pattern \s*,\s* splits text on commas surrounded by optional spaces.

5fill in blank

hard

Fill all three blanks to define a custom analyzer using the standard tokenizer and lowercase filter.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_custom_analyzer": {
          "type": "custom",
          "tokenizer": "[1]",
          "filter": ["[2]", "[3]"]
        }
      }
    }
  }
}

Drag options to blanks, or click blank then click option'

Astandard

Blowercase

Cstop

Dwhitespace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'whitespace' tokenizer instead of 'standard'.

Omitting the 'stop' filter when filtering stop words is needed.

The custom analyzer uses the standard tokenizer. The filters include lowercase to convert tokens to lowercase and stop to remove common stop words.