Full-Text Queries: match, multi_match, match_phrase

Queries that understand text

match analyses the query text and finds documents containing the terms; by default any term can match (operator: or), and you can require all with operator: and or a minimum_should_match such as "75%". fuzziness: "AUTO" tolerates small typos. multi_match runs a match over several fields with optional boosts (title^3); its type controls how per-field scores combine: best_fields (default, the best single field wins), most_fields (sum across fields), cross_fields (treat fields as one big field, good for names split across first/last), and phrase/phrase_prefix. match_phrase requires the terms in order and adjacent, with slop allowing some distance between them.

Asking precise questions

Full-text queries score relevance, term-level queries filter exactly, and bool combines them.

Three full-text queries

Kibana Dev Tools console syntax; send the same requests with curl or a client library.

GET /products/_search
{
  "query": {
    "match": {
      "name": { "query": "waterproof jaket", "operator": "and", "fuzziness": "AUTO" }
    }
  }
}

GET /products/_search
{
  "query": {
    "multi_match": {
      "query": "trail running shoe",
      "fields": [ "name^3", "brand^2", "description" ],
      "type": "best_fields"
    }
  }
}

GET /products/_search
{
  "query": {
    "match_phrase": { "description": { "query": "machine washable", "slop": 1 } }
  }
}

Start with multi_match and boosts

For a typical search box, multi_match over a few fields with a higher boost on the title is a solid baseline; tune with real queries rather than guesses.

त्वरित जाँच: Which query requires its terms to appear in order and near each other?

• match_phrase
• match with operator or
• term
• exists