Advanced Elasticsearch Queries: Bool, Range, Fuzzy, Filter, and Sorting

In this tutorial we extend basic Elasticsearch usage by demonstrating several advanced query types and how to combine them for more precise search results.

1. Boolean query (bool) combines other queries using must (AND), must_not (NOT) and should (OR) clauses.

GET /yoshop/_search
{
  "query": {
    "bool": {
      "must": { "match": { "title": "大米" }},
      "must_not": { "match": { "title": "电视" }},
      "should": { "match": { "title": "手机" }}
    }
  }
}

2. Range query (range) selects documents whose numeric or date fields fall within a specified interval.

GET /heima/_search
{
  "query": {
    "range": {
      "price": {
        "gte": 1000.0,
        "lt": 2800.00
      }
    }
  }
}

3. Fuzzy query (fuzzy) is a tolerant version of a term query that allows a limited edit distance (default up to 2) between the searched term and the indexed term.

GET /youshop/_search
{
  "query": {
    "fuzzy": {
      "title": "applo"
    }
  }
}

To control the allowed edit distance explicitly, use the fuzziness parameter:

GET /youshop/_search
{
  "query": {
    "fuzzy": {
      "title": {
        "value": "appla",
        "fuzziness": 1
      }
    }
  }
}

4. Filter applies criteria that restrict the result set without influencing the relevance score.

GET /youshop/_search
{
  "query": {
    "bool": {
      "must": { "match": { "title": "小米手机" }},
      "filter": {
        "range": { "price": { "gt": 3000, "lt": 3800.00 } }
      }
    }
  }
}

Filters can also be combined with additional bool conditions.

5. Sorting

Single‑field sorting orders results by a specific field using the order parameter.

GET /youshop/_search
{
  "query": { "match": { "title": "小米手机" } },
  "sort": [
    { "price": { "order": "desc" } }
  ]
}

Multi‑field sorting combines several fields, for example sorting first by price and then by _id :

GET /goods/_search
{
  "query": {
    "bool": {
      "must": { "match": { "title": "小米手机" }},
      "filter": { "range": { "price": { "gt": 2000, "lt": 3000 } } }
    }
  },
  "sort": [
    { "price": { "order": "desc" } },
    { "_id": { "order": "desc" } }
  ]
}

These examples illustrate how to build more powerful Elasticsearch queries by combining boolean logic, range constraints, fuzzy matching, filters, and sorting.