Advanced Multi-Match Queries in Elasticsearch

Elasticsearch has revolutionized how we handle full-text search and data analytics, offering a wealth of tools for fine-tuned search experiences. Among its powerful query options is the multi-match query, which allows you to search across multiple fields simultaneously. This advanced query type is invaluable when creating sophisticated search features for applications ranging from e-commerce to document management systems.

In this blog post, we’ll explore multi-match queries in Elasticsearch, their advanced options, and how to tailor them to achieve precise results.

What is a Multi-Match Query?

The multi-match query in Elasticsearch is an extension of the match query, designed to search multiple fields with a single query. Instead of writing multiple match clauses for each field, the multi-match query lets you specify multiple fields to be searched simultaneously.

For example, if you’re building a job search engine, you might want to search across fields like job_title, description, and skills_required. A multi-match query can achieve this efficiently.

Basic Syntax of a Multi-Match Query

Here’s a simple example of a multi-match query:

POST /jobs/_search
{
  "query": {
    "multi_match": {
      "query": "data scientist",
      "fields": ["job_title", "description", "skills_required"]
    }
  }
}

In this example:

The query parameter specifies the search term.
The fields array lists the fields to search.

Types of Multi-Match Queries

Elasticsearch provides several type options for multi-match queries, allowing you to fine-tune how the query operates. Here are the most commonly used types:

1. Best Fields (Default)

This mode retrieves results from the single field that matches the query best.

"multi_match": {
  "query": "data scientist",
  "fields": ["job_title", "description", "skills_required"],
  "type": "best_fields"
}

Use Case: Ideal for scenarios where the relevance score from one field is sufficient to determine a match.

2. Most Fields

This mode considers all specified fields and combines their scores to find documents matching the most fields.

"multi_match": {
  "query": "data scientist",
  "fields": ["job_title", "description", "skills_required"],
  "type": "most_fields"
}

Use Case: Useful for cases where the document should have matches across multiple fields.

3. Cross Fields

This mode treats multiple fields as if they were one. It’s particularly effective when different fields represent parts of the same concept.

"multi_match": {
  "query": "data scientist",
  "fields": ["job_title", "description", "skills_required"],
  "type": "cross_fields",
  "operator": "and"
}

Use Case: Ideal for searching names or phrases split across fields (e.g., first name and last name).

4. Phrase

This mode searches for the query as a phrase in each field.

"multi_match": {
  "query": "data scientist",
  "fields": ["job_title", "description"],
  "type": "phrase"
}

Use Case: Useful for exact phrase matches, such as job titles or precise keywords.

5. Phrase Prefix

This mode searches for documents containing terms that match the phrase prefix.

"multi_match": {
  "query": "data sci",
  "fields": ["job_title", "description"],
  "type": "phrase_prefix"
}

Use Case: Great for auto-suggest and search-as-you-type implementations.

Boosting Field Importance

Elasticsearch allows you to assign weights to fields by adding a boost factor, ensuring certain fields are prioritized in the search results.

"multi_match": {
  "query": "data scientist",
  "fields": ["job_title^3", "description^2", "skills_required"]
}

Here:

job_title has the highest importance (boosted by 3).
description has moderate importance (boosted by 2).
skills_required has the default importance.

Boosting is particularly helpful in scenarios like e-commerce, where product titles might carry more weight than descriptions.

Combining Multi-Match with Filters

For more refined queries, combine multi-match queries with filters. For example, search for "data scientist" but only in jobs based in "New York":

POST /jobs/_search
{
  "query": {
    "bool": {
      "must": {
        "multi_match": {
          "query": "data scientist",
          "fields": ["job_title", "description", "skills_required"]
        }
      },
      "filter": {
        "term": {
          "location": "New York"
        }
      }
    }
  }
}

Conclusion

Multi-match queries are a cornerstone of building advanced, user-friendly search experiences in Elasticsearch. By leveraging its versatile types, field boosts, and combinations with other query types, you can create powerful search solutions tailored to your application’s needs. Whether you’re working on a search engine for e-commerce, recruitment, or content discovery, mastering multi-match queries will elevate your Elasticsearch implementation to the next level.

Ready to implement multi-match queries in your project? Let us know if you have questions or need further guidance.