Standard analyzer in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a standard analyzer in Elasticsearch.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_standard_analyzer": {
          "type": "[1]"
        }
      }
    }
  }
}

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

Astandard

Bkeyword

Csimple

Dwhitespace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' analyzer which does not tokenize the text.

Using 'simple' or 'whitespace' which behave differently.

The standard analyzer is the default and most common analyzer in Elasticsearch. It tokenizes text into terms on word boundaries and removes most punctuation.

2fill in blank

medium

Complete the code to create an index with a standard analyzer applied to a field.

Elasticsearch

{
  "mappings": {
    "properties": {
      "content": {
        "type": "text",
        "analyzer": "[1]"
      }
    }
  }
}

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

Akeyword

Bstandard

Csimple

Denglish

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' analyzer which does not tokenize text.

Using language-specific analyzers like 'english' when standard is needed.

The standard analyzer is specified as the analyzer for the 'content' field to tokenize and analyze text using the default standard analyzer.

3fill in blank

hard

Fix the error in the analyzer definition to use the standard analyzer correctly.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "type": "[1]"
        }
      }
    }
  }
}

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

Astandard

BStandard

CSTANDARD

Dstandards

Attempts:

3 left

💡 Hint

Common Mistakes

Using uppercase or capitalized versions like 'Standard' or 'STANDARD'.

Typo like 'standards' which is invalid.

The analyzer type must be lowercase standard. Elasticsearch is case-sensitive for analyzer types.

4fill in blank

hard

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

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "custom_std_lower": {
          "tokenizer": "[1]",
          "filter": ["[2]"]
        }
      }
    }
  }
}

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

Astandard

Blowercase

Cstop

Dkeyword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' tokenizer which does not split text.

Using 'stop' filter instead of 'lowercase' filter.

The standard tokenizer splits text into terms on word boundaries. The lowercase filter converts all tokens to lowercase.

5fill in blank

hard

Fill all three blanks to create an index with a standard analyzer and a mapping that uses it on the 'title' field.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_std_analyzer": {
          "type": "[1]"
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "title": {
        "type": "text",
        "analyzer": "[2]"
      }
    }
  }
}

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

Akeyword

Bstandard

Cmy_std_analyzer

Dsimple

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' as analyzer type which does not tokenize.

Using 'standard' as analyzer name in mapping instead of custom analyzer name.

The analyzer type is standard. The mapping uses the custom analyzer named my_std_analyzer which is defined as type standard. The analyzer name in the mapping must match the custom analyzer's name.

Practice

1. What does the standard analyzer in Elasticsearch do by default?

easy

A. Keeps punctuation and case intact

B. Breaks text into words, ignores punctuation and case

C. Only analyzes numbers and symbols

D. Removes all spaces and joins words

Solution

1. Step 1: Understand the role of the standard analyzer

   The standard analyzer splits text into simple words by removing punctuation and ignoring case differences.

2. Step 2: Recall default behavior in Elasticsearch

   It is the default analyzer and is designed for general text processing, making text lowercase and splitting on punctuation.

3. Final Answer:

   Breaks text into words, ignores punctuation and case -> Option B

4. Quick Check:

   Standard analyzer = splits words, ignores punctuation and case [OK]

Hint: Standard analyzer splits words and lowercases text [OK]

Common Mistakes:

• Thinking it keeps punctuation
• Assuming it preserves case
• Believing it only analyzes numbers

2. Which of the following is the correct way to specify the standard analyzer in an Elasticsearch index mapping?

easy

A. "analyzer": "whitespace"

B. "analyzer": "simple"

C. "analyzer": "keyword"

D. "analyzer": "standard"

Solution

1. Step 1: Identify the analyzer name for standard analyzer

   The standard analyzer is referenced by the string "standard" in Elasticsearch mappings.

2. Step 2: Compare with other analyzer names

   Other analyzers like "simple", "keyword", and "whitespace" are different and not the standard analyzer.

3. Final Answer:

   "analyzer": "standard" -> Option D

4. Quick Check:

   Standard analyzer name = "standard" [OK]

Hint: Use "analyzer": "standard" to apply standard analyzer [OK]

Common Mistakes:

• Using other analyzer names by mistake
• Forgetting quotes around analyzer name
• Confusing standard with simple analyzer

3. Given the text "Hello, World! Elasticsearch 7.10", what tokens will the standard analyzer produce?

medium

A. ["Hello", "World", "Elasticsearch", "7.10"]

B. ["hello,", "world!", "elasticsearch", "7.10"]

C. ["hello", "world", "elasticsearch", "7", "10"]

D. ["hello world elasticsearch 7 10"]

Solution

1. Step 1: Apply standard analyzer tokenization rules

   The standard analyzer lowercases text and splits on punctuation and whitespace, so "Hello," becomes "hello", "World!" becomes "world".

2. Step 2: Analyze numbers and punctuation

   Numbers separated by punctuation like "7.10" are split into "7" and "10" tokens.

3. Final Answer:

   ["hello", "world", "elasticsearch", "7", "10"] -> Option C

4. Quick Check:

   Standard analyzer tokens = lowercase words split on punctuation [OK]

Hint: Standard analyzer lowercases and splits on punctuation [OK]

Common Mistakes:

• Keeping punctuation attached to words
• Not splitting numbers on dots
• Preserving original case

4. You wrote this mapping snippet but your field is not analyzed as expected:

{
  "mappings": {
    "properties": {
      "title": {
        "type": "text",
        "analyzer": "standard_analyzer"
      }
    }
  }
}

What is the error?

medium

A. Analyzer name should be "standard", not "standard_analyzer"

B. Field type should be "keyword" instead of "text"

C. Analyzer must be defined under "settings", not "mappings"

D. Missing "index": true property

Solution

1. Step 1: Check the analyzer name used in mapping

   The standard analyzer is named "standard". Using "standard_analyzer" is incorrect and causes the analyzer to not be found.

2. Step 2: Verify field type and analyzer placement

   Field type "text" is correct for analyzed fields, and analyzer is correctly placed under "mappings". "index": true is default and not required.

3. Final Answer:

   Analyzer name should be "standard", not "standard_analyzer" -> Option A

4. Quick Check:

   Analyzer name must be exact "standard" [OK]

Hint: Use exact analyzer name "standard" in mappings [OK]

Common Mistakes:

• Adding extra suffix to analyzer name
• Changing field type to keyword for analyzed text
• Misplacing analyzer in settings instead of mappings

5. You want to create a custom analyzer that uses the standard tokenizer but adds a lowercase filter and a stop word filter. Which of the following JSON snippets correctly defines this analyzer in Elasticsearch?

hard

A. {
"settings": {
"analysis": {
"analyzer": {
"custom_std": {
"type": "custom",
"tokenizer": "standard",
"filter": ["lowercase", "stop"]
}
}
}
}
}

B. {
"settings": {
"analysis": {
"analyzer": {
"custom_std": {
"type": "standard",
"filter": ["lowercase", "stop"]
}
}
}
}
}

C. {
"settings": {
"analysis": {
"analyzer": {
"custom_std": {
"type": "custom",
"tokenizer": "simple",
"filter": ["lowercase", "stop"]
}
}
}
}
}

D. {
"settings": {
"analysis": {
"analyzer": {
"custom_std": {
"type": "custom",
"tokenizer": "standard",
"filter": ["stop", "uppercase"]
}
}
}
}
}

Solution

1. Step 1: Define a custom analyzer with standard tokenizer

   The analyzer must have "type": "custom" and use "tokenizer": "standard" to start with the standard tokenizer.

2. Step 2: Add lowercase and stop filters in correct order

   The filters array should include "lowercase" and "stop" filters to lowercase tokens and remove stop words.

3. Step 3: Verify other options

   { "settings": { "analysis": { "analyzer": { "custom_std": { "type": "standard", "filter": ["lowercase", "stop"] } } } } } uses "type": "standard" which does not allow custom filters. { "settings": { "analysis": { "analyzer": { "custom_std": { "type": "custom", "tokenizer": "simple", "filter": ["lowercase", "stop"] } } } } } uses "simple" tokenizer, not standard. { "settings": { "analysis": { "analyzer": { "custom_std": { "type": "custom", "tokenizer": "standard", "filter": ["stop", "uppercase"] } } } } } uses "uppercase" filter which is incorrect here.

4. Final Answer:

   Custom analyzer with type custom, standard tokenizer, and filters lowercase and stop -> Option A

5. Quick Check:

   Custom analyzer = type custom + standard tokenizer + lowercase + stop filters [OK]

Hint: Custom analyzer needs type custom and tokenizer standard [OK]

Common Mistakes:

• Using type standard instead of custom for filters
• Choosing wrong tokenizer like simple
• Wrong filter order or filters like uppercase