15_Best_field.asciidoc

Best Fields

Imagine that we have a website that allows users to search blog posts, such as these two documents:

PUT /my_index/my_type/1
{
    "title": "Quick brown rabbits",
    "body":  "Brown rabbits are commonly seen."
}

PUT /my_index/my_type/2
{
    "title": "Keeping pets healthy",
    "body":  "My quick brown fox eats rabbits on a regular basis."
}

The user types in the words `Brown fox'' and clicks Search. We don’t know ahead of time if the user’s search terms will be found in the `title or the body field of the post, but it is likely that the user is searching for related words. To our eyes, document 2 appears to be the better match, as it contains both words that we are looking for.

Now we run the following bool query:

{
    "query": {
        "bool": {
            "should": [
                { "match": { "title": "Brown fox" }},
                { "match": { "body":  "Brown fox" }}
            ]
        }
    }
}

And we find that this query gives document 1 the higher score:

{
  "hits": [
     {
        "_id":      "1",
        "_score":   0.14809652,
        "_source": {
           "title": "Quick brown rabbits",
           "body":  "Brown rabbits are commonly seen."
        }
     },
     {
        "_id":      "2",
        "_score":   0.09256032,
        "_source": {
           "title": "Keeping pets healthy",
           "body":  "My quick brown fox eats rabbits on a regular basis."
        }
     }
  ]
}

To understand why, think about how the bool query calculates its score:

1. It runs both of the queries in the should clause.

2. It adds their scores together.

3. It multiplies the total by the number of matching clauses.

4. It divides the result by the total number of clauses (two).

Document 1 contains the word brown in both fields, so both match clauses are successful and have a score. Document 2 contains both brown and fox in the body field but neither word in the title field. The high score from the body query is added to the zero score from the title query, and multiplied by one-half, resulting in a lower overall score than for document 1.

In this example, the title and body fields are competing with each other. We want to find the single best-matching field.

What if, instead of combining the scores from each field, we used the score from the best-matching field as the overall score for the query? This would give preference to a single field that contains both of the words we are looking for, rather than the same word repeated in different fields.

dis_max Query

Instead of the bool query, we can use the dis_max or Disjunction Max Query. Disjunction means or (while conjunction means and) so the Disjunction Max Query simply means return documents that match any of these queries, and return the score of the best matching query:

{
    "query": {
        "dis_max": {
            "queries": [
                { "match": { "title": "Brown fox" }},
                { "match": { "body":  "Brown fox" }}
            ]
        }
    }
}

This produces the results that we want:

{
  "hits": [
     {
        "_id":      "2",
        "_score":   0.21509302,
        "_source": {
           "title": "Keeping pets healthy",
           "body":  "My quick brown fox eats rabbits on a regular basis."
        }
     },
     {
        "_id":      "1",
        "_score":   0.12713557,
        "_source": {
           "title": "Quick brown rabbits",
           "body":  "Brown rabbits are commonly seen."
        }
     }
  ]
}