Synonym handling in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this synonym filter configuration?

Given the following Elasticsearch analyzer configuration with synonyms, what tokens will be produced for the input text "quick fox"?

Elasticsearch

{
  "settings": {
    "analysis": {
      "filter": {
        "synonym_filter": {
          "type": "synonym",
          "synonyms": [
            "quick,fast",
            "fox,red fox"
          ]
        }
      },
      "analyzer": {
        "synonym_analyzer": {
          "tokenizer": "standard",
          "filter": ["lowercase", "synonym_filter"]
        }
      }
    }
  }
}

Input text: "quick fox"

A ["quick", "fast", "fox", "red", "fox"]

B ["quick", "fox"]

C ["fast", "red", "fox"]

D ["quick", "fast", "fox"]

💡 Hint

Think about how synonyms expand tokens during analysis.

The synonym filter expands each token to include its synonyms. "quick" expands to "quick" and "fast". "fox" expands to "fox" and "red fox" which tokenizes as "red" and "fox" separately.

🧠 Conceptual

intermediate

Which synonym type supports multi-word synonyms in Elasticsearch?

Elasticsearch supports different synonym types. Which synonym type allows you to define multi-word synonyms like "red fox" as a synonym for "fox"?

A "synonym_graph" filter

B "synonym" filter with <code>expand: true</code>

C "stop" filter

D "keyword" filter

💡 Hint

Multi-word synonyms require special handling to preserve token positions.

The "synonym_graph" filter supports multi-word synonyms properly by preserving token graph positions, which is necessary for phrase queries.

🔧 Debug

advanced

Why does this synonym filter cause a query parsing error?

Given this synonym filter snippet, why does Elasticsearch return a parsing error when indexing documents? "synonyms": [ "fast, quick", "fox => red fox" ]

Elasticsearch

synonyms: [
  "fast, quick",
  "fox => red fox"
]

A The arrow syntax (=>) is only valid in the "synonym" filter, but the list is missing commas.

B The arrow syntax (=>) is invalid in the "synonym" filter; it requires the "synonym" filter with <code>expand: false</code>.

C The arrow syntax (=>) is valid only if <code>expand</code> is set to false, which is missing here.

D The arrow syntax (=>) is invalid in the "synonym" filter; it requires the "synonym_graph" filter.

💡 Hint

Check the rules for using arrow syntax in synonym filters.

The arrow syntax (=>) is only valid in the "synonym" filter when expand is set to false. Without expand: false, it causes a parsing error.

📝 Syntax

advanced

Which synonym filter configuration is syntactically correct for multi-word synonyms?

Select the correct Elasticsearch synonym filter configuration snippet that supports multi-word synonyms without errors.

A

{
  "type": "synonym",
  "synonyms": ["red fox, fox"]
}

B

{
  "type": "synonym_graph",
  "synonyms": ["red fox, fox"]
}

C

{
  "type": "synonym",
  "synonyms": ["red fox => fox"]
}

D

{
  "type": "synonym_graph",
  "synonyms": ["red fox => fox"]
}

💡 Hint

Multi-word synonyms with arrow syntax require a specific filter type.

The "synonym_graph" filter supports multi-word synonyms and arrow syntax correctly. Option D is the only valid syntax for this case.

🚀 Application

expert

How many tokens are produced by this analyzer with synonyms and stop words?

Given this analyzer configuration and input text, how many tokens are produced? Analyzer config: { "tokenizer": "standard", "filter": ["lowercase", "stop_filter", "synonym_filter"] } Filters: - stop_filter removes: "the", "a" - synonym_filter synonyms: "quick,fast" "fox,red fox" Input text: "The quick brown fox jumps over a lazy dog"

A 11

B 9

C 10

D 12

💡 Hint

Count tokens after stop word removal and synonym expansion.

Stop words "the" and "a" are removed, leaving 7 tokens. "quick" expands to 2 tokens (+1 extra). "fox" expands to "fox", "red", "fox" (3 tokens, +2 extra). Total tokens: 7 + 1 + 2 = 10.