How Search Query Works

sangmin7648·2021년 5월 11일

1. Query DSL vs Query String

there are 2 ways of querying
1. using query DSL
2. using query string

1-1. Using query DSL

2 types
1. leaf query : search for values within particular fields
2. compound query : contain multiple leaf queries or compound queries

  • most flexible and common way of writing search query
GET /product/_search
    "query" : {
        "match" : {
            "description" : {
                "value" : "red wine"
  • query object in _search API contains query definition

1-2. Using query string

GET /product/_search?q=name:pasta

name = field name
pasta = value

2. How search query works

  • search query reaches node with shard b, which becomes coordinating node
  • coordinating node then queries nodes with different shards

2-1. Relevance Scoring

full text search results are sorted by their relevance score

  • relevance scoring is what differenciates Elasticsearch from RDB
  • until recently TF/IDF was used, but now BM 25 is used
    • better handling of stop words using nonlinear term frequency saturation
    • improving field-length norm factor by treating each field separately instead of just treating a field in the same way across all docs

⚠️ IDF might be different for relevance scoring as by default, scoring is per shard based

3. Search Contexts

  • query clause can be executed on 2 contexts
  1. Query Context : how well do docs match the query (match + relevance scoring)
  2. Filter Context : do docs match? (only match)

4. Full text vs term search

  • term level : search for exact value, input is not processed by analyzer

  • full text : search query is analyzed before matching. Analyzer specified by the field is used, if none, standard analyzer is used

편하게 읽기 좋은 단위의 포스트를 추구하는 개발자입니다

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