Why text analysis enables smart search in Elasticsearch - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a basic analyzer that lowercases text.

Elasticsearch

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

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

Asimple

Bstandard

Ckeyword

Dcustom

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'keyword' analyzer which does not lowercase text.

Using 'standard' analyzer which does more than just lowercase.

The simple analyzer lowercases text, which is essential for case-insensitive search.

2fill in blank

medium

Complete the code to add a stopwords filter to remove common words.

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        "my_stop": {
          "type": "[1]",
          "stopwords": ["the", "is", "at"]
        }
      }
    }
  }
}

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

Astop

Blowercase

Csynonym

Dstemmer

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'lowercase' filter which only changes case.

Using 'stemmer' which reduces words to their root form.

The stop filter removes common words like 'the', 'is', and 'at' to improve search relevance.

3fill in blank

hard

Fix the error in the analyzer definition to include both lowercase and stop filters.

Elasticsearch

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": ["[1]", "stop"]
        }
      }
    }
  }
}

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

Astemmer

Bkeyword

Csynonym

Dlowercase

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'stemmer' which changes word forms instead of case.

Using 'keyword' which does not change tokens.

The lowercase filter ensures tokens are lowercase before stopwords are removed.

4fill in blank

hard

Fill both blanks to create a mapping that uses the custom analyzer and enables full-text search.

Elasticsearch

{
  "mappings": {
    "properties": {
      "content": {
        "type": "[1]",
        "analyzer": "[2]"
      }
    }
  }
}

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

Atext

Bkeyword

Cmy_analyzer

Dstandard

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' type which does not analyze text.

Using 'standard' analyzer instead of the custom one.

The field type should be text to allow analyzed full-text search, and the analyzer should be the custom one my_analyzer.

5fill in blank

hard

Fill all three blanks to define a custom analyzer with a standard tokenizer, lowercase and stop filters.

Elasticsearch

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

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

Acustom

Bstandard

Clowercase

Dkeyword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' tokenizer which does not split text.

Omitting the lowercase filter.

The analyzer type is custom, tokenizer is standard, and filters include lowercase and stop for effective text analysis.