In the preceding section, we discussed using proximity queries just for relevance purposes, not to include or exclude results from the result set. A query may match millions of results, but chances are that our users are interested in only the first few pages of results.

A simple match query will already have ranked documents that contain all search terms near the top of the list. Really, we just want to rerank the top results to give an extra relevance bump to those documents that also match the phrase query.

The search API supports exactly this functionality via rescoring. The rescore phase allows you to apply a more expensive scoring algorithm—​like a phrase query—​to just the top K results from each shard. These top results are then resorted according to their new scores.

The request looks like this:

GET /my_index/my_type/_search
{
    "query": {
        "match": {  
            "title": {
                "query":                "quick brown fox",
                "minimum_should_match": "30%"
            }
        }
    },
    "rescore": {
        "window_size": 50, 
        "query": {         
            "rescore_query": {
                "match_phrase": {
                    "title": {
                        "query": "quick brown fox",
                        "slop":  50
                    }
                }
            }
        }
    }
}