Constant score query in Elasticsearch - Time & Space Complexity

Time Complexity: Constant score query

O(n)

Understanding Time Complexity

We want to understand how the time to run a constant score query changes as the data grows.

Specifically, how does the query's work increase when there are more documents?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

{
  "constant_score": {
    "filter": {
      "term": { "status": "active" }
    },
    "boost": 1.2
  }
}
    

This query finds documents where the status is "active" and assigns a fixed score to each match.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Scanning the index to find documents matching the filter.
• How many times: Once per document or per matching term in the index.

How Execution Grows With Input

As the number of documents grows, the query checks more entries to find matches.

Input Size (n)	Approx. Operations
10	About 10 checks
100	About 100 checks
1000	About 1000 checks

Pattern observation: The work grows roughly in direct proportion to the number of documents.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the query grows linearly as the number of documents increases.

Common Mistake

[X] Wrong: "The constant score query runs instantly no matter how big the data is."

[OK] Correct: Even though the score is fixed, the query still needs to check documents to find matches, so time grows with data size.

Interview Connect

Understanding how queries scale helps you write efficient searches and explain your choices clearly in real projects.

Self-Check

"What if we replaced the term filter with a match_all filter? How would the time complexity change?"

Practice

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

easy

A. To filter documents and assign the same score to all matched documents

B. To sort documents by their relevance score

C. To perform a full-text search with varying scores

D. To aggregate documents by a field value

Solution

1. Step 1: Understand the role of constant_score query

   The constant_score query filters documents and assigns the same score to all matches, ignoring relevance scoring.

2. Step 2: Compare with other query types

   Unlike full-text queries that score by relevance, constant_score keeps scores equal for filtered documents.

3. Final Answer:

   To filter documents and assign the same score to all matched documents -> Option A

4. Quick Check:

   constant_score = equal scoring for filtered docs [OK]

Hint: Constant score means all matched docs get the same score [OK]

Common Mistakes:

• Thinking it sorts by relevance
• Confusing with full-text scoring
• Assuming it aggregates data

2. Which of the following is the correct syntax to create a constant score query with a filter on field status equal to active?

easy

A. {"constant_score": {"filter": {"match": {"status": "active"}}}}

B. {"constant_score": {"query": {"term": {"status": "active"}}}}

C. {"constant_score": {"term": {"status": "active"}}}

D. {"constant_score": {"filter": {"term": {"status": "active"}}}}

Solution

1. Step 1: Identify correct key for filtering

   The constant_score query uses the key "filter" to specify the filter clause, not "query" or direct term.

2. Step 2: Check filter syntax

   The filter should be a term query inside the filter object, correctly written as {"term": {"status": "active"}}.

3. Final Answer:

   {"constant_score": {"filter": {"term": {"status": "active"}}}} -> Option D

4. Quick Check:

   Use "filter" with term inside constant_score [OK]

Hint: Use "filter" key with term query inside constant_score [OK]

Common Mistakes:

• Using "query" instead of "filter"
• Placing term query directly under constant_score
• Using match instead of term for exact filter

3. Given this Elasticsearch query snippet, what will be the score of each matched document?

{
  "constant_score": {
    "filter": { "term": { "category": "books" } },
    "boost": 3
  }
}

medium

A. The score will vary based on relevance

B. The score will be 3 for all matched documents

C. The score will be 1 for all matched documents

D. The score will be 0 because boost is ignored

Solution

1. Step 1: Understand constant_score with boost

   The constant_score query assigns the same score to all matched documents, and the boost multiplies that score.

2. Step 2: Calculate the score

   By default, constant_score gives score 1, multiplied by boost 3, resulting in score 3 for all matches.

3. Final Answer:

   The score will be 3 for all matched documents -> Option B

4. Quick Check:

   constant_score x boost = 3 [OK]

Hint: Boost multiplies constant score, so score = boost value [OK]

Common Mistakes:

• Assuming scores vary by relevance
• Ignoring the boost value
• Thinking boost is ignored in constant_score

4. Identify the error in this constant score query:

{
  "constant_score": {
    "filter": {
      "terms": {
        "tags": ["tech", "science"]
      }
    },
    "boost": "2"
  }
}

medium

A. The boost value should be a number, not a string

B. The filter key should be replaced with query

C. The terms query cannot be used inside constant_score

D. The tags field should be inside a match query

Solution

1. Step 1: Check boost data type

   The boost parameter must be a numeric value, not a string. Here, "2" is a string, which is invalid.

2. Step 2: Validate filter and terms usage

   Using "filter" with a "terms" query is valid syntax, so no error there.

3. Final Answer:

   The boost value should be a number, not a string -> Option A

4. Quick Check:

   boost must be numeric, not string [OK]

Hint: Boost must be a number, not quoted string [OK]

Common Mistakes:

• Using string for boost instead of number
• Replacing filter with query incorrectly
• Misunderstanding terms query usage

5. You want to find all documents where status is published and boost their score by 5, but keep all matched documents scored equally. Which query correctly achieves this?

hard

A. { "match": { "status": "published", "boost": 5 } }

B. { "bool": { "must": { "term": { "status": "published" } }, "boost": 5 } }

C. { "constant_score": { "filter": { "term": { "status": "published" } }, "boost": 5 } }

D. { "constant_score": { "query": { "term": { "status": "published" } }, "boost": 5 } }

Solution

1. Step 1: Use constant_score with filter and boost

   To keep scores equal and apply a boost, use constant_score with a filter clause and boost parameter.

2. Step 2: Validate correct syntax

   { "constant_score": { "filter": { "term": { "status": "published" } }, "boost": 5 } } uses "filter" with a term query and numeric boost, which is the correct syntax.

3. Step 3: Check other options

   { "bool": { "must": { "term": { "status": "published" } }, "boost": 5 } } uses bool query which scores by relevance, not constant. { "match": { "status": "published", "boost": 5 } } is a match query with boost but scores vary. { "constant_score": { "query": { "term": { "status": "published" } }, "boost": 5 } } incorrectly uses "query" instead of "filter" inside constant_score.

4. Final Answer:

   { "constant_score": { "filter": { "term": { "status": "published" } }, "boost": 5 } } -> Option C

5. Quick Check:

   constant_score + filter + boost = equal boosted scores [OK]

Hint: Use constant_score with filter and numeric boost for equal boosted scores [OK]

Common Mistakes:

• Using query instead of filter inside constant_score
• Using bool or match queries that score variably
• Setting boost as string instead of number