Phrase suggestions (did you mean) in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Phrase Suggestion Output for Misspelled Query

Given the following Elasticsearch phrase suggestion query, what is the expected output suggestion for the misspelled word "appl"?

Elasticsearch

{
  "suggest": {
    "text": "appl",
    "simple_phrase": {
      "phrase": {
        "field": "title.trigram",
        "size": 1,
        "gram_size": 3,
        "direct_generator": [{
          "field": "title.trigram",
          "suggest_mode": "always"
        }],
        "highlight": {
          "pre_tag": "<em>",
          "post_tag": "</em>"
        }
      }
    }
  }
}

A {"simple_phrase":[{"text":"appl","highlighted":"<em>appl</em>"}]}

B {"simple_phrase":[{"text":"apply","highlighted":"<em>apply</em>"}]}

C {"simple_phrase":[{"text":"apple","highlighted":"<em>apple</em>"}]}

D {"simple_phrase":[]}

💡 Hint

Think about how phrase suggestions correct common misspellings using trigram analysis.

The phrase suggester uses trigram analysis to suggest the closest correct word. "appl" is corrected to "apple" with highlighting.

🧠 Conceptual

intermediate

Understanding the Purpose of Direct Generator in Phrase Suggestions

What is the main role of the "direct_generator" in an Elasticsearch phrase suggestion query?

A It highlights the matched terms in the search results.

B It generates candidate corrections based on the specified field and suggest mode.

C It controls the number of suggestions returned by the query.

D It filters out suggestions that do not match the original query exactly.

💡 Hint

Consider how Elasticsearch finds possible corrections for misspelled words.

The direct_generator creates candidate terms for correction based on the field and suggest_mode, which are then scored and returned.

❓ Predict Output

advanced

Output of Phrase Suggestion with Multiple Candidates

What is the output of the following phrase suggestion query when the input text is "recieve" and the index contains "receive" and "recipe"?

Elasticsearch

{
  "suggest": {
    "text": "recieve",
    "phrase_suggester": {
      "phrase": {
        "field": "content.trigram",
        "size": 2,
        "gram_size": 3,
        "direct_generator": [{
          "field": "content.trigram",
          "suggest_mode": "always"
        }],
        "highlight": {
          "pre_tag": "<b>",
          "post_tag": "</b>"
        }
      }
    }
  }
}

A {"phrase_suggester":[{"text":"receive","highlighted":"<b>receive</b>"},{"text":"recipe","highlighted":"<b>recipe</b>"}]}

B {"phrase_suggester":[{"text":"recieve","highlighted":"<b>recieve</b>"}]}

C {"phrase_suggester":[{"text":"receipt","highlighted":"<b>receipt</b>"}]}

D {"phrase_suggester":[]}

💡 Hint

The suggester returns the top 2 candidates based on trigram similarity.

The phrase suggester returns the two closest matches "receive" and "recipe" with highlighting tags.

🔧 Debug

advanced

Identify the Error in Phrase Suggestion Query

What error will this Elasticsearch phrase suggestion query produce?

Elasticsearch

{
  "suggest": {
    "text": "exampel",
    "phrase": {
      "field": "body.trigram",
      "gram_size": 3,
      "direct_generator": {
        "field": "body.trigram",
        "suggest_mode": "missing"
      }
    }
  }
}

A RuntimeError: suggest_mode 'missing' is invalid

B No error, query runs successfully

C TypeError: field parameter missing in direct_generator

D SyntaxError: direct_generator must be an array, not an object

💡 Hint

Check the data type of direct_generator in the phrase suggestion syntax.

The direct_generator must be an array of objects, but here it is given as a single object, causing a syntax error.

🧠 Conceptual

expert

Why Use Phrase Suggestions Instead of Term Suggestions?

Why would you choose to use phrase suggestions (did you mean) over term suggestions in Elasticsearch?

A Phrase suggestions consider the context of multiple words to correct phrases, reducing nonsensical corrections.

B Phrase suggestions are faster to compute than term suggestions.

C Term suggestions do not support highlighting of corrections.

D Phrase suggestions only work on numeric fields, while term suggestions work on text.

💡 Hint

Think about how phrase suggestions handle multiple words compared to single words.

Phrase suggestions analyze the context of entire phrases, which helps avoid incorrect or irrelevant corrections that term suggestions might produce when correcting words individually.