Query: Adds support for weighted RRF in Hybrid Search

[aayush3011]

Weighted RRF support

This change adds support for weighted RRF in hybrid search.

We allow weights to be negative but the negative sign is used to signal that we should sort scores in ascending order for the corresponding component. The final WRRF score is then computed using the absolute value of the weight.

In this approach, the sign of the weight indicates the interpretation of the ranking itself rather than directly affecting the calculated score:
WRRF(d) = ∑ |w_i| × 1/(k + r_i'(d))

Where:

|w_i| is the absolute value of the weight for the i-th component
r_i'(d) is the rank of document d in the i-th component, with a crucial difference:

• If w_i > 0: r_i'(d) is the original rank (descending order, where 1 is best)
• If w_i < 0: r_i'(d) is the inverted rank (ascending order, where higher number is better)

k = 60

Intuition Behind This Modification

This modification addresses a key scenario in information retrieval and ranking fusion: sometimes "lower is better" rather than "higher is better."

• Handling Different Ranking Interpretations: Some systems naturally produce rankings where lower values are better (like error rates, distances, or pricing). The sign becomes a semantic indicator of how to interpret the ranking.
• Unifying Disparate Metrics: This allows you to combine rankings based on completely different metrics (relevance scores, error rates, freshness, etc.) without having to pre-process them into a common format.
• Integration of Minimization Metrics: You can directly incorporate metrics that should be minimized (like latency or error) alongside metrics that should be maximized (like relevance or user engagement).

All SDK Contribution checklist:

• The pull request does not introduce [breaking changes]
• CHANGELOG is updated for new features, bug fixes or other significant changes.
• I have read the contribution guidelines.

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Testing Guidelines

• Pull request includes test coverage for the included changes.

[Copilot]

Pull Request Overview

This PR adds support for weighted RRF in hybrid search by introducing a new component weight property and updating the ranking calculations accordingly. Key changes include:

• Adding a new property “componentWeights” and its getter in HybridSearchQueryInfo.
• Updating query feature lists and ranking computation in HybridSearchDocumentQueryExecutionContext to incorporate weight values.
• Adjusting tests to cover various weighted RRF scenarios.

Reviewed Changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
HybridSearchQueryInfo.java	Introduces a new componentWeights field and getter supporting weighted queries.
QueryPlanRetriever.java	Updates the supported query features list to include WeightedRankFusion.
QueryFeature.java	Adds the WeightedRankFusion enum value.
HybridSearchDocumentQueryExecutionContext.java	Modifies methods to retrieve component weights, sort component scores using the provided comparator, and use weights in RRF score calculations.
Constants.java	Updates JSON property mapping constants for hybrid search, though the key names appear to be swapped.
HybridSearchQueryTest.java	Adds new tests covering weighted RRF scenarios.

[github-actions]

API Change Check

APIView identified API level changes in this PR and created the following API reviews

com.azure:azure-cosmos

[kushagraThapar]

Thanks @aayush3011 , looks good to me, can you please get approval from @simorenoh and @bambriz on this, thanks!

[aayush3011]

/azp run java - cosmos - tests

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[kushagraThapar]

Requesting changes since we don't want to merge this to main

[simorenoh]

One small comment but not blocking on it since it doesn't affect the code, thanks!