Boosting query in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a boosting query that lowers the score of documents matching the negative query.

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": { "match_all": {} },
      "negative": { "term": { "status": "archived" } },
      "[1]": 0.2
    }
  }
}

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

Ascore

Bnegative_boost

Cboost

Dweight

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'boost' instead of 'negative_boost' causes an error.

Using 'score' or 'weight' are not valid parameters here.

The negative_boost parameter sets the factor by which the score of documents matching the negative query is reduced.

2fill in blank

medium

Complete the code to boost documents matching the positive query with a higher score.

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": { "match": { "title": "[1]" } },
      "negative": { "term": { "status": "draft" } },
      "boost": 1.5
    }
  }
}

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

Aelasticsearch

Bpython

Cjavascript

Djava

Attempts:

3 left

💡 Hint

Common Mistakes

Using unrelated programming languages as the match term.

Leaving the match term empty causes no boost.

The positive query matches documents with the word elasticsearch in the title, boosting their score.

3fill in blank

hard

Fix the error in the boosting query by completing the missing field name.

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": { "match": { "content": "search" } },
      "negative": { "term": { "status": "deprecated" } },
      "[1]": 0.1
    }
  }
}

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

Aweight

Bscore

Cnegative_boost

Dboost

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'boost' instead of 'negative_boost' causes errors.

Using 'score' or 'weight' are invalid here.

The correct field to reduce the score of negative matches is negative_boost.

4fill in blank

hard

Fill both blanks to create a boosting query that boosts documents with 'python' in the title and lowers score for status 'obsolete'.

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": { "match": { "title": "[1]" } },
      "negative": { "term": { "status": "[2]" } },
      "boost": 2.0
    }
  }
}

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

Apython

Bjava

Cobsolete

Ddraft

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up positive and negative query terms.

Using unrelated status values.

The positive query matches 'python' in the title, and the negative query matches documents with status 'obsolete' to lower their score.

5fill in blank

hard

Fill all three blanks to create a boosting query that boosts documents with 'cloud' in description, lowers score for status 'inactive', and sets boost factor to 0.3.

Elasticsearch

{
  "query": {
    "boosting": {
      "positive": { "match": { "description": "[1]" } },
      "negative": { "term": { "status": "[2]" } },
      "[3]": 0.3
    }
  }
}

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

Acloud

Binactive

Cnegative_boost

Dactive

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'active' instead of 'inactive' for negative query.

Using wrong field name instead of 'negative_boost'.

The positive query matches 'cloud' in description, the negative query matches status 'inactive', and the boost factor is set with negative_boost.

Practice

1. What is the main purpose of a boosting query in Elasticsearch?

easy

A. To filter out documents without a specific field

B. To sort results alphabetically

C. To increase the relevance score of some results and decrease others

D. To aggregate data by terms

Solution

1. Step 1: Understand boosting query purpose

   A boosting query is designed to adjust the relevance scores of search results by raising some and lowering others.

2. Step 2: Compare with other query types

   Sorting alphabetically, filtering, and aggregating are different Elasticsearch features unrelated to boosting.

3. Final Answer:

   To increase the relevance score of some results and decrease others -> Option C

4. Quick Check:

   Boosting query = Adjust relevance scores [OK]

Hint: Boosting changes scores, not sorting or filtering [OK]

Common Mistakes:

• Confusing boosting with sorting
• Thinking boosting filters documents
• Mixing boosting with aggregation

2. Which of the following is the correct syntax snippet for a boosting query in Elasticsearch?

easy

A. { "boosting": { "positive": { "term": { "field": "value" } }, "negative": { "term": { "field": "other" } } } }

B. { "boost": { "match": { "field": "value" }, "boost_factor": 2 } }

C. { "boosting_query": { "positive": { "term": { "field": "value" } }, "negative": { "term": { "field": "other" } } } }

D. { "boosting": { "positive": { "match": { "field": "value" } }, "negative": { "match": { "field": "other" } }, "negative_boost": 0.5 } }

Solution

1. Step 1: Identify correct boosting query structure

   The correct syntax uses the "boosting" key with "positive", "negative", and "negative_boost" fields.

2. Step 2: Check each option

   The snippet using "boosting" with "positive" match query, "negative" match query, and "negative_boost": 0.5 matches the correct structure. Others miss "negative_boost" or use incorrect keys like "boost" or "boosting_query".

3. Final Answer:

   { "boosting": { "positive": { "match": { "field": "value" } }, "negative": { "match": { "field": "other" } }, "negative_boost": 0.5 } } -> Option D

4. Quick Check:

   Boosting query syntax = { "boosting": { "positive": { "match": { "field": "value" } }, "negative": { "match": { "field": "other" } }, "negative_boost": 0.5 } } [OK]

Hint: Look for "boosting" with positive, negative, and negative_boost keys [OK]

Common Mistakes:

• Using wrong key names like "boost" or "boosting_query"
• Omitting "negative_boost"
• Using incorrect query types inside positive/negative

3. Given this boosting query, what will happen to documents matching the negative query?

{
  "boosting": {
    "positive": { "match": { "title": "apple" } },
    "negative": { "match": { "title": "banana" } },
    "negative_boost": 0.3
  }
}

medium

A. Their relevance scores will be increased by 0.3

B. Their relevance scores will be decreased by multiplying by 0.3

C. They will be excluded from results

D. They will have the same score as positive matches

Solution

1. Step 1: Understand negative_boost effect

   The negative_boost value multiplies the score of documents matching the negative query, lowering their relevance.

2. Step 2: Apply to given query

   Documents matching "banana" will have their scores multiplied by 0.3, reducing their rank but not excluding them.

3. Final Answer:

   Their relevance scores will be decreased by multiplying by 0.3 -> Option B

4. Quick Check:

   negative_boost multiplies score down [OK]

Hint: Negative matches get score multiplied by negative_boost < 1 [OK]

Common Mistakes:

• Thinking negative_boost adds to score
• Assuming negative matches are filtered out
• Confusing negative_boost with positive boost

4. Identify the error in this boosting query:

{
  "boosting": {
    "positive": { "match": { "content": "dog" } },
    "negative": { "match": { "content": "cat" } }
  }
}

medium

A. Missing "negative_boost" field

B. Incorrect query type inside positive

C. Wrong key name "boosting" should be "boost"

D. Positive and negative queries cannot use the same field

Solution

1. Step 1: Check required fields in boosting query

   A boosting query requires "positive", "negative", and "negative_boost" fields to work correctly.

2. Step 2: Identify missing element

   The provided query lacks the "negative_boost" field, which defines how much to reduce negative matches.

3. Final Answer:

   Missing "negative_boost" field -> Option A

4. Quick Check:

   Boosting query needs negative_boost [OK]

Hint: Always include negative_boost in boosting queries [OK]

Common Mistakes:

• Omitting negative_boost
• Using wrong key names
• Assuming same field usage is invalid

5. You want to boost documents containing "premium" in the category field and reduce scores of documents containing "basic" in the same field by half. Which boosting query correctly achieves this?

hard

A. { "boosting": { "positive": { "term": { "category": "premium" } }, "negative": { "term": { "category": "basic" } }, "negative_boost": 0.5 } }

B. { "boosting": { "positive": { "match": { "category": "premium" } }, "negative": { "match": { "category": "basic" } }, "negative_boost": 2 } }

C. { "boost": { "term": { "category": "premium" }, "boost_factor": 2 } }

D. { "boosting": { "positive": { "term": { "category": "basic" } }, "negative": { "term": { "category": "premium" } }, "negative_boost": 0.5 } }

Solution

1. Step 1: Identify positive and negative queries

   Positive query should match "premium" category to boost, negative query should match "basic" to reduce score.

2. Step 2: Check negative_boost value

   Negative boost of 0.5 reduces scores of negative matches by half, which matches the requirement.

3. Step 3: Verify options

   { "boosting": { "positive": { "term": { "category": "premium" } }, "negative": { "term": { "category": "basic" } }, "negative_boost": 0.5 } } correctly uses term queries and negative_boost 0.5. Other options either use negative_boost greater than 1, are not boosting queries, or reverse positive and negative.

4. Final Answer:

   { "boosting": { "positive": { "term": { "category": "premium" } }, "negative": { "term": { "category": "basic" } }, "negative_boost": 0.5 } } -> Option A

5. Quick Check:

   Positive = premium, negative = basic, negative_boost = 0.5 [OK]

Hint: Positive boosts, negative reduces with negative_boost < 1 [OK]

Common Mistakes:

• Swapping positive and negative queries
• Using negative_boost greater than 1
• Using boost instead of boosting query