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.

Practice

1. What is the main purpose of phrase suggestions (did you mean) in Elasticsearch?

easy

A. To help fix typos and suggest correct phrases in search queries

B. To sort search results by relevance

C. To filter documents based on date ranges

D. To aggregate numeric data for analytics

Solution

1. Step 1: Understand phrase suggestions purpose

   Phrase suggestions are designed to detect and correct typos or mistakes in user search queries.

2. Step 2: Compare with other features

   Sorting, filtering, and aggregations serve different purposes unrelated to typo correction.

3. Final Answer:

   To help fix typos and suggest correct phrases in search queries -> Option A

4. Quick Check:

   Phrase suggestions = typo correction [OK]

Hint: Phrase suggestions fix typos in queries [OK]

Common Mistakes:

• Confusing phrase suggestions with sorting or filtering
• Thinking phrase suggestions aggregate data
• Assuming phrase suggestions change document content

2. Which of the following is the correct way to specify a phrase suggestion in an Elasticsearch query?

easy

A. "suggest": {"my-suggestion": {"completion": {"field": "content"}}}

B. "suggest": {"my-suggestion": {"term": {"field": "content"}}}

C. "suggest": {"my-suggestion": {"text": "exampl", "phrase": {"field": "content"}}}

D. "suggest": {"my-suggestion": {"match": {"field": "content"}}}

Solution

1. Step 1: Identify phrase suggestion syntax

   Phrase suggestions use the "phrase" type inside the suggest block with a specified field.

2. Step 2: Check other options

   Options A, B, and D use other suggestion types like completion, term, or match, which are not phrase suggestions.

3. Final Answer:

   "suggest": {"my-suggestion": {"text": "exampl", "phrase": {"field": "content"}}} -> Option C

4. Quick Check:

   Phrase suggestion uses "phrase" type [OK]

Hint: Phrase suggestions use "phrase" type in suggest [OK]

Common Mistakes:

• Using term or completion instead of phrase
• Omitting the "field" inside phrase
• Misplacing the "text" parameter

3. Given this Elasticsearch phrase suggestion snippet, what will be the size of suggestions returned?

{
  "suggest": {
    "text": "quik brown",
    "phrase": {
      "field": "body",
      "size": 3
    }
  }
}

medium

A. 1 suggestion

B. Unlimited suggestions

C. 5 suggestions

D. 3 suggestions

Solution

1. Step 1: Identify the size parameter

   The "size" parameter inside the phrase suggestion controls how many suggestions are returned.

2. Step 2: Check the value of size

   Here, "size" is set to 3, so Elasticsearch will return up to 3 suggestions.

3. Final Answer:

   3 suggestions -> Option D

4. Quick Check:

   Size = 3 means 3 suggestions [OK]

Hint: Check "size" to know number of suggestions [OK]

Common Mistakes:

• Assuming default size without checking parameter
• Confusing size with gram_size
• Thinking size limits characters, not suggestions

4. Identify the error in this phrase suggestion query:

{
  "suggest": {
    "my-suggest": {
      "text": "helo world",
      "phrase": {
        "field": "content",
        "gram_size": "two"
      }
    }
  }
}

medium

A. "gram_size" should be an integer, not a string

B. "text" parameter is missing

C. "field" should be an array, not a string

D. Phrase suggestions don't support 'gram_size' parameter

Solution

1. Step 1: Check the "gram_size" parameter type

   "gram_size" expects an integer value, but here it is given as a string "two".

2. Step 2: Verify other parameters

   "text" and "field" are correctly specified; phrase suggestions do support "gram_size".

3. Final Answer:

   "gram_size" should be an integer, not a string -> Option A

4. Quick Check:

   gram_size = integer, not string [OK]

Hint: Use numbers, not words, for gram_size [OK]

Common Mistakes:

• Passing gram_size as a string
• Removing the text parameter
• Changing field to an array unnecessarily

5. You want to suggest corrections for a user query with multiple words and control the phrase suggestion to consider 2-gram phrases. Which of the following is the correct way to configure the phrase suggestion in Elasticsearch?

hard

A. { "suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": 2, "size": 2 } } }

B. { "suggest": { "my-suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": 2, "size": 2 } } } }

C. { "suggest": { "my-suggest": { "text": "spel cheker", "term": { "field": "text", "gram_size": 2 } } } }

D. { "suggest": { "my-suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": "2", "size": 2 } } } }

Solution

1. Step 1: Check the suggest block structure

   The suggest block must have a named suggestion (e.g., "my-suggest") containing "text" and "phrase" parameters.

2. Step 2: Verify phrase suggestion parameters

   "gram_size" should be an integer (2), and "size" controls number of suggestions. { "suggest": { "my-suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": 2, "size": 2 } } } } correctly uses these.

3. Step 3: Eliminate incorrect options

   { "suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": 2, "size": 2 } } } misses the named suggestion key. { "suggest": { "my-suggest": { "text": "spel cheker", "term": { "field": "text", "gram_size": 2 } } } } uses "term" instead of "phrase". { "suggest": { "my-suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": "2", "size": 2 } } } } passes "gram_size" as a string, which is invalid.

4. Final Answer:

   { "suggest": { "my-suggest": { "text": "spel cheker", "phrase": { "field": "text", "gram_size": 2, "size": 2 } } } } -> Option B

5. Quick Check:

   Named suggest + phrase + integer gram_size = correct [OK]

Hint: Use named suggest with phrase and integer gram_size [OK]

Common Mistakes:

• Omitting the named suggestion key
• Using term instead of phrase
• Passing gram_size as a string