Testing analyzers (_analyze API) in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to analyze the text "Quick Brown Fox" using the standard analyzer.

Elasticsearch

{
  "analyzer": "[1]",
  "text": "Quick Brown Fox"
}

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

Awhitespace

Bstandard

Csimple

Dkeyword

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using 'whitespace' analyzer which only splits on spaces but does not lowercase.

The standard analyzer is the default and breaks text into terms on word boundaries.

2fill in blank

medium

Complete the code to analyze the text "Running runner runs" using the English stemmer analyzer.

Elasticsearch

{
  "tokenizer": "standard",
  "filter": ["[1]"],
  "text": "Running runner runs"
}

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

Alowercase

Benglish_stemmer

Cstop

Dporter_stem

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'english_stemmer' which is not a default filter name.

Using 'stop' filter which removes stop words instead of stemming.

The porter_stem filter applies the Porter stemming algorithm to reduce words to their root form.

3fill in blank

hard

Fix the error in the analyzer definition to correctly lowercase the text "HELLO WORLD".

Elasticsearch

{
  "tokenizer": "standard",
  "filter": ["[1]"],
  "text": "HELLO WORLD"
}

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

Alowercase

Buppercase

Cstop

Dasciifolding

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'uppercase' filter which does the opposite.

Using 'stop' filter which removes common words but does not change case.

The lowercase filter converts all tokens to lowercase, which is needed here.

4fill in blank

hard

Fill both blanks to analyze the text "Cats running" with a custom analyzer that uses the standard tokenizer and the lowercase and porter_stem filters.

Elasticsearch

{
  "tokenizer": "[1]",
  "filter": ["[2]", "porter_stem"],
  "text": "Cats running"
}

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

Astandard

Bkeyword

Clowercase

Dstop

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' tokenizer which does not split text.

Omitting the lowercase filter which causes stemming to fail on uppercase tokens.

The standard tokenizer splits text into words, and the lowercase filter converts tokens to lowercase before stemming.

5fill in blank

hard

Fill all three blanks to create an analyzer that tokenizes text on whitespace, lowercases tokens, and removes English stop words.

Elasticsearch

{
  "tokenizer": "[1]",
  "filter": ["[2]", "[3]"],
  "text": "The quick brown fox jumps over the lazy dog"
}

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

Astandard

Bwhitespace

Clowercase

Dstop

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'standard' tokenizer which splits on punctuation too.

Omitting the stop filter which leaves stop words in tokens.

The whitespace tokenizer splits text on spaces, lowercase filter converts tokens to lowercase, and stop filter removes common English stop words.