Character filters in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a character filter that replaces '&' with 'and'.

Elasticsearch

{
  "settings": {
    "analysis": {
      "char_filter": {
        "ampersand_filter": {
          "type": "[1]",
          "mappings": ["&=>and"]
        }
      }
    }
  }
}

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

Ahtml_strip

Breplace

Cpattern_replace

Dmapping

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'replace' or 'pattern_replace' which are not valid character filter types.

Confusing character filters with token filters.

The mapping type is used to replace characters or strings with others in character filters.

2fill in blank

medium

Complete the code to define a character filter that removes HTML tags.

Elasticsearch

{
  "settings": {
    "analysis": {
      "char_filter": {
        "html_remover": {
          "type": "[1]"
        }
      }
    }
  }
}

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

Amapping

Bhtml_strip

Cpattern_replace

Dkeyword_marker

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'mapping' type which requires explicit mappings.

Confusing with token filters like 'keyword_marker'.

The html_strip character filter removes HTML tags from text.

3fill in blank

hard

Fix the error in the character filter definition to replace '#' with 'number'.

Elasticsearch

{
  "settings": {
    "analysis": {
      "char_filter": {
        "hash_filter": {
          "type": "[1]",
          "mappings": ["#=>number"]
        }
      }
    }
  }
}

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

Apattern_replace

Bhtml_strip

Cmapping

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'pattern_replace' which requires a regex pattern.

Using 'html_strip' which removes HTML tags.

The correct type for character replacement using mappings is mapping.

4fill in blank

hard

Fill both blanks to create a character filter that replaces '@' with 'at' and removes HTML tags.

Elasticsearch

{
  "settings": {
    "analysis": {
      "char_filter": {
        "email_filter": {
          "type": "[1]",
          "mappings": ["@=>at"]
        },
        "clean_html": {
          "type": "[2]"
        }
      }
    }
  }
}

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

Amapping

Bhtml_strip

Cpattern_replace

Dkeyword_marker

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up the types for each filter.

Using 'pattern_replace' instead of 'mapping' for simple replacements.

The mapping type is used for character replacements with mappings, and html_strip removes HTML tags.

5fill in blank

hard

Fill all three blanks to define a character filter that replaces '$' with 'dollar', removes HTML tags, and replaces '%' with 'percent'.

Elasticsearch

{
  "settings": {
    "analysis": {
      "char_filter": {
        "dollar_filter": {
          "type": "[1]",
          "mappings": ["$=>dollar"]
        },
        "html_cleaner": {
          "type": "[2]"
        },
        "percent_filter": {
          "type": "[3]",
          "mappings": ["%=>percent"]
        }
      }
    }
  }
}

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

Amapping

Bhtml_strip

Cpattern_replace

Dkeyword_marker

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'pattern_replace' instead of 'mapping' for simple character replacements.

Confusing the types for each filter.

The mapping type is used for character replacements with mappings, and html_strip removes HTML tags.

Practice

1. What is the main purpose of a character_filter in Elasticsearch analyzers?

easy

A. To split text into tokens after analysis

B. To modify text before tokenizing by replacing or removing characters

C. To store documents in the index

D. To sort search results by relevance

Solution

1. Step 1: Understand character_filter role

   Character filters act on raw text before tokenization to clean or replace characters.

2. Step 2: Differentiate from other components

   Tokenizers split text into tokens, and other parts handle indexing or sorting, not character filters.

3. Final Answer:

   To modify text before tokenizing by replacing or removing characters -> Option B

4. Quick Check:

   Character filters = modify text pre-tokenizing [OK]

Hint: Character filters act before tokenizing text [OK]

Common Mistakes:

• Confusing character filters with tokenizers
• Thinking character filters sort or store data
• Assuming character filters work after tokenizing

2. Which of the following is the correct syntax to define a mapping character filter in Elasticsearch?

easy

A. "char_filter": {"my_mapping": {"type": "mapping", "mappings": ["ph=>f", "qu=>kw"]}}

B. "char_filter": {"my_mapping": {"type": "pattern_replace", "pattern": "ph", "replacement": "f"}}

C. "char_filter": {"my_mapping": {"type": "mapping", "pattern": "ph", "replacement": "f"}}

D. "char_filter": {"my_mapping": {"type": "replace", "mappings": ["ph=>f"]}}

Solution

1. Step 1: Identify correct type and keys for mapping filter

   The mapping filter uses "type": "mapping" and a "mappings" array with string replacements.

2. Step 2: Check syntax correctness

   "char_filter": {"my_mapping": {"type": "mapping", "mappings": ["ph=>f", "qu=>kw"]}} correctly uses "type": "mapping" and "mappings" with array of strings like "ph=>f".

3. Final Answer:

   "char_filter": {"my_mapping": {"type": "mapping", "mappings": ["ph=>f", "qu=>kw"]}} -> Option A

4. Quick Check:

   Mapping filter syntax = type mapping + mappings array [OK]

Hint: Mapping filters use type 'mapping' and 'mappings' array [OK]

Common Mistakes:

• Using pattern_replace keys for mapping filter
• Wrong type name like 'replace' instead of 'mapping'
• Using 'pattern' and 'replacement' keys in mapping filter

3. Given this character filter configuration:

{
  "char_filter": {
    "my_filter": {
      "type": "pattern_replace",
      "pattern": "\\d",
      "replacement": "#"
    }
  }
}

What will be the output text after applying my_filter to the input "abc123def"?

medium

A. "abc1#3def"

B. "abc123def"

C. "abc###def"

D. "abc#23def"

Solution

1. Step 1: Understand pattern_replace with pattern '\\d'

   The pattern '\\d' matches any digit character (0-9). The replacement is '#'.

2. Step 2: Apply replacement to input text

   All digits '1', '2', '3' in "abc123def" are replaced by '#', resulting in "abc###def".

3. Final Answer:

   "abc###def" -> Option C

4. Quick Check:

   Digits replaced by '#' = "abc###def" [OK]

Hint: Pattern '\d' matches all digits, replaced by '#' [OK]

Common Mistakes:

• Replacing only first digit instead of all
• Not escaping backslash in pattern
• Confusing pattern_replace with mapping filter

4. Identify the error in this character filter definition:

{
  "char_filter": {
    "bad_filter": {
      "type": "mapping",
      "mapping": ["ph=>f"]
    }
  }
}

medium

A. Character filters cannot use arrays

B. The type 'mapping' is invalid

C. The replacement string 'ph=>f' is incorrect format

D. The key should be 'mappings' not 'mapping'

Solution

1. Step 1: Check correct key for mapping filter

   The mapping filter requires the key 'mappings' (plural) for the array of replacements.

2. Step 2: Verify other parts

   Type 'mapping' is valid, and the replacement string format "ph=>f" is correct.

3. Final Answer:

   The key should be 'mappings' not 'mapping' -> Option D

4. Quick Check:

   Key name must be 'mappings' for mapping filter [OK]

Hint: Use 'mappings' key (plural) for mapping filters [OK]

Common Mistakes:

• Using 'mapping' instead of 'mappings'
• Mistaking type name
• Wrong replacement string format

5. You want to create a character filter that replaces all occurrences of 'cat' with 'dog' and removes digits from the text before tokenizing. Which configuration correctly combines these requirements?

hard

A. {
"char_filter": {
"replace_cat": {
"type": "mapping",
"mappings": ["cat=>dog"]
},
"remove_digits": {
"type": "pattern_replace",
"pattern": "[0-9]",
"replacement": ""
}
}
}

B. {
"char_filter": {
"replace_cat": {
"type": "pattern_replace",
"pattern": "cat",
"replacement": "dog"
},
"remove_digits": {
"type": "mapping",
"mapping": ["0=>", "1=>", "2=>", "3=>", "4=>", "5=>", "6=>", "7=>", "8=>", "9=>"]
}
}
}

C. {
"char_filter": {
"replace_cat": {
"type": "mapping",
"mapping": ["cat=>dog"]
},
"remove_digits": {
"type": "pattern_replace",
"pattern": "\\d",
"replacement": ""
}
}
}

D. {
"char_filter": {
"replace_cat": {
"type": "pattern_replace",
"pattern": "cat",
"replacement": "dog"
},
"remove_digits": {
"type": "pattern_replace",
"pattern": "d",
"replacement": ""
}
}
}

Solution

1. Step 1: Check replacement of 'cat' with 'dog'

   Using a mapping filter with "cat=>dog" is correct and simpler for exact string replacement.

2. Step 2: Check digit removal filter

   Removing digits with pattern_replace using pattern "[0-9]" and empty replacement is valid and concise.

3. Step 3: Verify combined configuration

   { "char_filter": { "replace_cat": { "type": "mapping", "mappings": ["cat=>dog"] }, "remove_digits": { "type": "pattern_replace", "pattern": "[0-9]", "replacement": "" } } } correctly combines a mapping filter for 'cat' and a pattern_replace filter for digits removal.

4. Final Answer:

   { "char_filter": { "replace_cat": { "type": "mapping", "mappings": ["cat=>dog"] }, "remove_digits": { "type": "pattern_replace", "pattern": "[0-9]", "replacement": "" } } } -> Option A

5. Quick Check:

   Mapping for 'cat', pattern_replace for digits removal [OK]

Hint: Use mapping for exact words, pattern_replace for patterns [OK]

Common Mistakes:

• Using pattern_replace for simple word mapping unnecessarily
• Using mapping filter to remove digits (inefficient)
• Incorrect regex patterns for digits