Boosting query in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this boosting query?

Given the following Elasticsearch boosting query, what documents will be boosted and how?

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": {
        "match": {"title": "apple"}
      },
      "negative": {
        "match": {"title": "banana"}
      },
      "negative_boost": 0.2
    }
  }
}

A Documents containing both "apple" and "banana" are boosted equally.

B Documents containing "apple" in title are boosted; documents containing "banana" have their score reduced by 80%.

C Documents containing "banana" are boosted; documents containing "apple" have their score reduced by 80%.

D Documents containing "apple" or "banana" are excluded from results.

💡 Hint

Remember that the positive query boosts scores, and the negative query reduces scores by the negative_boost factor.

The boosting query increases the score of documents matching the positive query ("apple") and reduces the score of documents matching the negative query ("banana") by multiplying their score by 0.2 (reducing by 80%).

🧠 Conceptual

intermediate

Which statement best describes the purpose of the negative_boost parameter?

In an Elasticsearch boosting query, what does the negative_boost parameter do?

A It decreases the score of documents matching the negative query by a factor.

B It increases the score of documents matching the negative query.

C It excludes documents matching the negative query from the results.

D It sets the minimum score for documents to be included.

💡 Hint

Think about how the negative query affects scoring.

The negative_boost parameter multiplies the score of documents matching the negative query by a factor less than 1, effectively lowering their relevance.

🔧 Debug

advanced

Why does this boosting query cause a syntax error?

Identify the error in this boosting query and its cause: { "query": { "boosting": { "positive": { "match": {"content": "python"} }, "negative": { "match": {"content": "java"} }, "negative_boost": "0.5" } } }

A The negative query is missing a closing bracket.

B The positive query must be a term query, not match.

C negative_boost should be a number, not a string.

D The boosting query requires a minimum_should_match parameter.

💡 Hint

Check the data type of negative_boost.

The negative_boost parameter must be a numeric value, not a string. Using quotes causes a syntax error.

❓ Predict Output

advanced

What is the effect of this boosting query on document scores?

Consider this boosting query: { "query": { "boosting": { "positive": { "term": {"category": "electronics"} }, "negative": { "term": {"brand": "generic"} }, "negative_boost": 0.1 } } } What happens to documents in the "electronics" category with brand "generic"?

A Their score is multiplied by 0.1, reducing it significantly.

B Their score is boosted twice, increasing it.

C They are excluded from the results.

D Their score remains unchanged.

💡 Hint

Both positive and negative queries can match the same document.

Documents matching both positive and negative queries get their score boosted by the positive query but then multiplied by negative_boost (0.1), resulting in a significant reduction.

🚀 Application

expert

How many documents will have their scores reduced by this boosting query?

Given an index with 1000 documents, 300 contain "python" in the "tags" field, 150 contain "beginner" in the "tags" field, and 50 contain both. Using this boosting query: { "query": { "boosting": { "positive": { "match": {"tags": "python"} }, "negative": { "match": {"tags": "beginner"} }, "negative_boost": 0.3 } } } How many documents will have their scores reduced by the negative_boost?

A 200 documents

B 350 documents

C 50 documents

D 150 documents

💡 Hint

Only documents matching the negative query have their scores reduced.

The negative query matches 150 documents with "beginner" tag, so those 150 documents have their scores multiplied by 0.3, reducing their scores.