﻿---
title: Combined fields
description: The combined_fields query supports searching multiple text fields as if their contents had been indexed into one combined field. The query takes a term-centric...
url: https://www.elastic.co/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-combined-fields-query
products:
  - Elasticsearch
---

# Combined fields
The `combined_fields` query supports searching multiple text fields as if their contents had been indexed into one combined field. The query takes a term-centric view of the input string: first it analyzes the query string into individual terms, then looks for each term in any of the fields. This query is particularly useful when a match could span multiple text fields, for example the `title`, `abstract`, and `body` of an article:
```json

{
  "query": {
    "combined_fields" : {
      "query":      "database systems",
      "fields":     [ "title", "abstract", "body"],
      "operator":   "and"
    }
  }
}
```

The `combined_fields` query takes a principled approach to scoring based on the simple BM25F formula described in [The Probabilistic Relevance Framework: BM25 and Beyond](http://www.staff.city.ac.uk/~sb317/papers/foundations_bm25_review.pdf). When scoring matches, the query combines term and collection statistics across fields to score each match as if the specified fields had been indexed into a single, combined field. This scoring is a best attempt; `combined_fields` makes some approximations and scores will not obey the BM25F model perfectly.
<admonition title="Field number limit">
  By default, there is a limit to the number of clauses a query can contain. This limit is defined by the [`indices.query.bool.max_clause_count`](/elastic/docs-builder/docs/2948/reference/elasticsearch/configuration-reference/search-settings#indices-query-bool-max-clause-count) setting, which defaults to `4096`. For combined fields queries, the number of clauses is calculated as the number of fields multiplied by the number of terms.
</admonition>


## Per-field boosting

Field boosts are interpreted according to the combined field model. For example, if the `title` field has a boost of 2, the score is calculated as if each term in the title appeared twice in the synthetic combined field.
```json

{
  "query": {
    "combined_fields" : {
      "query" : "distributed consensus",
      "fields" : [ "title^2", "body" ] <1>
    }
  }
}
```

<note>
  The `combined_fields` query requires that field boosts are greater than or equal to 1.0. Field boosts are allowed to be fractional.
</note>


## Top-level parameters for `combined_fields`

<definitions>
  <definition term="fields">
    (Required, array of strings) List of fields to search. Field wildcard patterns are allowed. Only [`text`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/mapping-reference/text) fields are supported, and they must all have the same search [`analyzer`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/mapping-reference/analyzer).
  </definition>
  <definition term="query">
    (Required, string) Text to search for in the provided `<fields>`.
  </definition>
</definitions>

The `combined_fields` query [analyzes](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/2948/manage-data/data-store/text-analysis) the provided text before performing a search.
<definitions>
  <definition term="auto_generate_synonyms_phrase_query">
    (Optional, Boolean) If `true`, [match phrase](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-match-query-phrase) queries are automatically created for multi-term synonyms. Defaults to `true`.
  </definition>
</definitions>

See [Use synonyms with match query](/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-match-query#query-dsl-match-query-synonyms) for an example.
<definitions>
  <definition term="operator">
    (Optional, string) Boolean logic used to interpret text in the `query` value. Valid values are:
    - `or` (Default)
      For example, a `query` value of `database systems` is interpreted as `database OR systems`.
    - `and`
      For example, a `query` value of `database systems` is interpreted as `database AND systems`.
  </definition>
  <definition term="minimum_should_match">
    (Optional, string) Minimum number of clauses that must match for a document to be returned. See the [`minimum_should_match` parameter](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-minimum-should-match) for valid values and more information.
  </definition>
  <definition term="zero_terms_query">
    (Optional, string) Indicates whether no documents are returned if the `analyzer` removes all tokens, such as when using a `stop` filter. Valid values are:
    - `none` (Default)
      No documents are returned if the `analyzer` removes all tokens.
    - `all`
      Returns all documents, similar to a [`match_all`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-match-all-query) query.
  </definition>
</definitions>

See [Zero terms query](/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-match-query#query-dsl-match-query-zero) for an example.

### Comparison to `multi_match` query

The `combined_fields` query provides a principled way of matching and scoring across multiple [`text`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/mapping-reference/text) fields. To support this, it requires that all fields have the same search [`analyzer`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/mapping-reference/analyzer).
If you want a single query that handles fields of different types like keywords or numbers, then the [`multi_match`](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/query-languages/query-dsl/query-dsl-multi-match-query) query may be a better fit. It supports both text and non-text fields, and accepts text fields that do not share the same analyzer.
The main `multi_match` modes `best_fields` and `most_fields` take a field-centric view of the query. In contrast, `combined_fields` is term-centric: `operator` and `minimum_should_match` are applied per-term, instead of per-field. Concretely, a query like
```json

{
  "query": {
    "combined_fields" : {
      "query":      "database systems",
      "fields":     [ "title", "abstract"],
      "operator":   "and"
    }
  }
}
```

is executed as:
```txt
+(combined("database", fields:["title" "abstract"]))
+(combined("systems", fields:["title", "abstract"]))
```

In other words, each term must be present in at least one field for a document to match.
The `cross_fields` `multi_match` mode also takes a term-centric approach and applies `operator` and `minimum_should_match per-term`. The main advantage of `combined_fields` over `cross_fields` is its robust and interpretable approach to scoring based on the BM25F algorithm.
<admonition title="Custom similarities">
  The `combined_fields` query currently only supports the BM25 similarity, which is the default unless a [custom similarity](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/index-settings/similarity) is configured. [Per-field similarities](https://www.elastic.co/elastic/docs-builder/docs/2948/reference/elasticsearch/mapping-reference/similarity) are also not allowed. Using `combined_fields` in either of these cases will result in an error.
</admonition>