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SpringBoot整合ES多个精确值查询 terms功能实现

作者：我一直在流浪

这篇文章主要介绍了SpringBoot整合ES多个精确值查询 terms功能实现,本文给大家介绍的非常详细,感兴趣的朋友跟随小编一起看看吧

ElasticSearch - SpringBoot整合ES：多个精确值查询 terms

01. ElasticSearch terms 查询支持的数据类型

在Elasticsearch中，terms查询支持多种数据类型，包括：

字符串类型：可以将多个字符串值作为数组传递给terms查询，以匹配包含任何一个指定字符串值的文档。

数值类型：可以将多个数值作为数组传递给terms查询，以匹配包含任何一个指定数值的文档。

日期类型：可以将多个日期值作为数组传递给terms查询，以匹配包含任何一个指定日期值的文档。

布尔类型：可以将多个布尔值作为数组传递给terms查询，以匹配包含任何一个指定布尔值的文档。

复杂数据类型如数组类型，对象类型也可以支持，具体可以参考term查询，term查询支持的数据类型，terms查询就会支持。区别在于 term查询用于匹配一个字段中包含指定值的文档，terms查询用于匹配一个字段中包含指定值之一的文档。

02. ElasticSearch term和 terms 查询的区别

在Elasticsearch中，term和terms查询都用于匹配一个字段中包含指定值的文档，但它们之间有一些区别。

term查询用于匹配包含完全相同值的文档，而无法匹配包含部分匹配值的文档。例如，以下查询将返回包含"red"颜色的文档：

{
  "query": {
    "term": {
      "color": "red"
    }
  }
}

但是，如果要查询包含"red"或"blue"颜色的文档，应该使用terms查询，而不是term查询。例如，以下查询将返回包含"red"或"blue"颜色中任何一个的文档：

{
  "query": {
    "terms": {
      "color": ["red", "blue"]
    }
  }
}

terms查询可以将多个值作为数组传递，以匹配包含任何一个指定值的文档，而term查询只能匹配包含单个指定值的文档。因此，如果要匹配包含多个值的文档，应该使用terms查询，而如果要匹配包含单个值的文档，应该使用term查询。

03. ElasticSearch terms 查询数值类型数据

一定要了解 term 和 terms 是包含操作，而非等值操作。 如何理解这句话呢？

在Elasticsearch中，term查询用于匹配一个字段中包含指定值的文档，terms查询用于匹配一个字段中包含指定值之一的文档。可以将多个值作为数组传递给terms查询，以匹配包含任何一个指定值的文档。

① 索引文档，构造数据：

PUT /my_index
{
  "mappings": {
    "properties": {
      "price":{
        "type": "integer"
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "price":10
}
PUT /my_index/_doc/2
{
  "price":20
}
PUT /my_index/_doc/3
{
  "price":30
}

② 查询 price 包含 "10"或"20"的文档，可以使用以下查询：

GET /my_index/_search
{
  "query": {
    "terms": {
      "price": [
        "10",
        "20"
      ]
    }
  }
}
{
  "took" : 11,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "price" : 10
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "price" : 20
        }
      }
    ]
  }
}

04. ElasticSearch terms 查询字符串型数据

terms查询用于匹配一个字段中包含指定值之一的文档。

① 索引文档，数据构造：

PUT /my_index
{
  "mappings": {
    "properties": {
      "tag":{
        "type": "keyword"
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "tag":"tag1"
}
PUT /my_index/_doc/2
{
  "tag":"tag2"
}
PUT /my_index/_doc/3
{
  "tag":"tag3"
}

② 查询 tag 字段包含 tag1 和 tag2 的文档：

GET /my_index/_search
{
  "query": {
    "terms": {
      "tag": [
        "tag1",
        "tag2"
      ]
    }
  }
}
{
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "tag" : "tag1"
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "tag" : "tag2"
        }
      }
    ]
  }
}

不要使用term 和terms 查询文本类型的数据。因为会分词，查询可能会出现意想不到的结果。

05. ElasticSearch terms 查询日期性数据

① 索引文档，构造数据：

PUT /my_index
{
  "mappings": {
    "properties": {
      "createTime":{
        "type": "date",
        "format": "yyyy-MM-dd HH:mm:ss"
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "createTime":"2023-03-29 10:30:11"
}
PUT /my_index/_doc/2
{
   "createTime":"2023-03-29 10:35:11"
}
PUT /my_index/_doc/3
{
   "createTime":"2023-03-29 10:38:11"
}

② 查询 createTime 字段包含 “2023-03-29 10:30:11” 或 “2023-03-29 10:38:11” 的文档：

{
  "took" : 672,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "createTime" : "2023-03-29 10:30:11"
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "createTime" : "2023-03-29 10:38:11"
        }
      }
    ]
  }
}

06. ElasticSearch terms 查询布尔型数据

① 索引文档，构造数据：

PUT /my_index
{
  "mappings": {
    "properties": {
      "flag":{
        "type": "boolean"
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "flag":true
}
PUT /my_index/_doc/2
{
  "flag":true
}
PUT /my_index/_doc/3
{
  "flag":false
}

② 查询 flag 字段包含 true 或 false 的文档：

GET /my_index/_search
{
  "query": {
    "terms": {
      "flag": [
        "true",
        "false"
      ]
    }
  }
}
{
  "took" : 30,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "flag" : true
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "flag" : true
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "flag" : false
        }
      }
    ]
  }
}

07. ElasticSearch terms 查询数组类型数据

terms查询可以用于匹配一个字段中包含指定值之一的文档。对于数组类型的字段，可以将多个值作为数组传递给terms查询，以匹配包含任何一个指定值的文档。

① 索引文档，构造数据：

PUT /my_index
{
  "mappings": {
    "properties": {
      "tags":{
        "type": "keyword"
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "tags":["tag1"]
}
PUT /my_index/_doc/2
{
  "tags":["tag2"]
}
PUT /my_index/_doc/3
{
  "tags":["tag1","tag2"]
}
PUT /my_index/_doc/4
{
  "tags":["tag1","tag2","tag3"]
}

② 要查询 tags 字段包含"tag1"或"tag2"的文档，可以使用以下查询：

GET /my_index/_search
{
  "query": {
    "terms": {
      "tags": [
        "tag1",
        "tag2"
      ]
    }
  }
}
{
  "took" : 4,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 4,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "tags" : [
            "tag1"
          ]
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "tags" : [
            "tag2"
          ]
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "tags" : [
            "tag1",
            "tag2"
          ]
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "4",
        "_score" : 1.0,
        "_source" : {
          "tags" : [
            "tag1",
            "tag2",
            "tag3"
          ]
        }
      }
    ]
  }
}

08. ElasticSearch terms 查询对象型数据

① 索引文档，构造数据：

PUT /my_index
{
  "mappings": {
    "properties": {
      "person": {
        "type": "object",
        "properties": {
          "name": {
            "type": "keyword"
          },
          "age": {
            "type": "integer"
          },
          "address": {
            "type": "keyword"
          }
        }
      }
    }
  }
}
PUT /my_index/_doc/1
{
  "person": {
    "name": "John",
    "age": 30,
    "address": "123 Main St"
  }
}
PUT /my_index/_doc/2
{
  "person": {
    "name": "Alex",
    "age": 20,
    "address": "123 Main St"
  }
}
PUT /my_index/_doc/3
{
  "person": {
    "name": "Smith",
    "age": 10,
    "address": "123 Main St"
  }
}

② 查询 person.name 字段包含 Alex 或者 Smith 的文档：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "person" : {
            "name" : "Alex",
            "age" : 20,
            "address" : "123 Main St"
          }
        }
      },
      {
        "_index" : "my_index",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "person" : {
            "name" : "Smith",
            "age" : 10,
            "address" : "123 Main St"
          }
        }
      }
    ]
  }
}

09. SpringBoot 整合ES实现terms查询

GET /my_index/_search
{
  "query": {
    "terms": {
      "price": [
        "10",
        "20"
      ]
    }
  }
}
@Slf4j
@Service
public class ElasticSearchImpl {
    @Autowired
    private RestHighLevelClient restHighLevelClient;
    public void searchUser() throws IOException {
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        // terms查询
        List<Integer> prices = Arrays.asList(10,20);
        // 查询所有price字段包含10或者20的文档
        TermsQueryBuilder termsQueryBuilder = new TermsQueryBuilder("price",prices);
        searchSourceBuilder.query(termsQueryBuilder);
        SearchRequest searchRequest = new SearchRequest(new String[]{"my_index"},searchSourceBuilder);
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        System.out.println(searchResponse);
    }
}

10. SpringBoot 整合ES实现terms查询

GET /my_index/_search
{
  "query": {
    "terms": {
      "tags": ["tag1","tag2"]
    }
  }
}
@Slf4j
@Service
public class ElasticSearchImpl {
    @Autowired
    private RestHighLevelClient restHighLevelClient;
    public void searchUser() throws IOException {
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        // terms查询
        List<String> tags = Arrays.asList("tag1","tag2");
        // 查询所有tags字段包含tag1或者tag2的文档
        TermsQueryBuilder termsQueryBuilder = new TermsQueryBuilder("tags",tags);
        searchSourceBuilder.query(termsQueryBuilder);
        SearchRequest searchRequest = new SearchRequest(new String[]{"my_index"},searchSourceBuilder);
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        System.out.println(searchResponse);
    }
}

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