How does a dismax query work in Elasticsearch?

When a dismax query is executed in Elasticsearch, it constructs a query that searches for all the specified search terms across multiple fields, but gives more weight to documents that contain more of the terms. The dismax query also uses a disjunction operator to combine the scores from each field into a single score for each document.

Here’s an example of a dismax query in Elasticsearch:

GET /my_index/_search
{
  "query": {
    "dis_max": {
      "queries": [
        { "match": { "title": "elasticsearch" }},
        { "match": { "description": "search" }}
      ],
      "tie_breaker": 0.3
    }
  }
}

In this example, we are searching the `title` and `description` fields in the `my_index` index for documents that contain the terms “elasticsearch” and “search”. The dismax query constructs a query that searches for both terms across both fields, but gives more weight to documents that contain both terms and uses a tie breaker of 0.3 to balance the scores from each field.

The dismax query also supports a variety of other features, such as specifying different levels of importance or weighting for different fields, using fuzzy matching or wildcard matching, and specifying minimum and maximum should match parameters.

The dismax query can also be used in combination with other query types, such as the bool query, to construct more complex search queries. By giving more weight to documents that contain more of the search terms and combining scores from multiple fields into a single score, the dismax query provides a powerful and flexible way to search for text in Elasticsearch.

However, it’s important to note that dismax queries can be computationally expensive and may not be suitable for large datasets or high-traffic applications. Additionally, dismax queries can be less precise than other query types, such as the term or match query, because they match a broader range of terms. Therefore, it’s important to carefully consider the use case and performance implications before using dismax queries in Elasticsearch.