Rescore

The rescore parameter improves search precision by reordering only the highest-ranked documents returned from your initial query. Rather than applying an expensive algorithm to all documents in the index, rescoring focuses computational resources on reranking a smaller window of top results using a secondary scoring method.

When you include a rescore parameter in your search request, OpenSearch processes the results in the following sequence:

1. Initial search: The primary query and any post-filters execute across all relevant documents.
2. Shard-level rescoring: Each shard applies the rescoring algorithm to its top results.
3. Final coordination: The coordinating node combines rescored results from all shards.

This approach provides better relevance while maintaining acceptable performance.

When using the rescore parameter, note the following important considerations:

• You cannot use explicit sorting (other than _score in descending order) with rescoring. OpenSearch returns an error if you attempt to combine custom sorting with a rescore query.

• When implementing pagination, maintain the same window_size across all pages. Changing the window size between pages can cause result inconsistencies as users navigate through search results.

Query rescoring

Query rescoring applies a secondary query to refine the scores of top-ranked documents. You can control how many documents each shard examines using the window_size parameter (default is 10).

Basic rescoring syntax

POST /_search
{
  "query": {
    "match": {
      "content": {
        "query": "OpenSearch query optimization",
        "operator": "or"
      }
    }
  },
  "rescore": {
    "window_size": 100,
    "query": {
      "rescore_query": {
        "match_phrase": {
          "content": {
            "query": "OpenSearch query optimization",
            "slop": 1
          }
        }
      },
      "query_weight": 0.8,
      "rescore_query_weight": 1.3
    }
  }
}

Rescore parameters

The rescore object supports the following parameters.

Score combination modes

The score_mode parameter determines how OpenSearch combines the original score with the rescore query score. This parameter accepts the following values.

Multiple rescoring stages

You can chain multiple rescoring operations to apply increasingly sophisticated ranking algorithms:

POST /_search
{
  "query": {
    "match": {
      "title": {
        "query": "search engine technology",
        "operator": "or"
      }
    }
  },
  "rescore": [
    {
      "window_size": 200,
      "query": {
        "rescore_query": {
          "match_phrase": {
            "title": {
              "query": "search engine technology",
              "slop": 2
            }
          }
        },
        "query_weight": 0.6,
        "rescore_query_weight": 1.4
      }
    },
    {
      "window_size": 50,
      "query": {
        "score_mode": "multiply",
        "rescore_query": {
          "function_score": {
            "script_score": {
              "script": {
                "source": "Math.log10(doc['popularity'].value + 2)"
              }
            }
          }
        }
      }
    }
  ]
}

In this multi-stage example:

1. The first rescoring stage examines 200 documents per shard, applying phrase matching to improve relevance.
2. The second rescoring stage takes the top 50 results from the first stage and applies popularity-based scoring using a logarithmic function.

Each stage processes the results from the previous stage, creating a refinement pipeline where computationally expensive operations only operate on the most promising candidates.