ElasticSearch 复合搜索与过滤API

约定不等于承诺〃 2023-06-27 03:17 37阅读 0赞

> 本文基于Elasticsearch7.x

全文搜索在搜索时, 会对输入的搜索文本进行分词, 然后去倒排索引中进行匹配, 只要能匹配上任意一个关键词(词项), 就可以作为结果返回.

在学习本篇博客前先了解下[Elasticsearch全文搜索之基础语法API][Elasticsearch_API]

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2xpdGlhbnhpYW5nX2thb2xh_size_16_color_FFFFFF_t_70]

### Rest API ###

**添加搜索实例数据**

POST /blogs/_bulk
    {"index": {}}
    {"post_date": "2020-01-01", "title": "Quick brown rabbits", "content": "Brown rabbits are commonly seen.", "author_id": 11401}
    {"index": {}}
    {"post_date": "2020-01-02", "title": "Keeping pets healthy", "content": "My quick brown fox eats rabbits on a regular basis.", "author_id": 11402}
    {"index": {}}
    {"post_date": "2020-01-03", "title": "My dog barks", "content": "I see a lot of barking dogs on the road.", "author_id": 11403}

**bool**

基础匹配API的实例都是对一个搜索文本进行匹配, 即单条件搜索. 下面我们来学习下bool多条件搜索, 即由多个搜索文本构成的复合搜索.

(1) bool语法

*  must  
    必须匹配, 贡献算分.
 *  must\_not  
    必须不能匹配, 贡献算分.
 *  should  
    选择性匹配, 贡献算分.
 *  filter  
    必须匹配, 不贡献算分.

must, must\_not, should这三个条件是会用于相关度分数计算的, 而filter不会, 从而filter的性能会更好. 由以上四种搜索子句合并为一条复合搜索语句, 这就是bool搜索.

基础匹配API中讲述的match, match\_phrase, dis\_max, multi\_match, term是基础的搜索语法, bool搜索是基于它们来实现的.

(2) 实例

a. 基础使用

GET /blogs/_search
    {
      "query": {
        "bool": {
          "must": [
            {
              "term": {
                "author_id": {
                  "value": "11403"
                }
              }
            }
          ],
          "must_not": [
            {
              "range": {
                "post_date": {
                  "lte": "2020-01-02"
                }
              }
            }
          ],
          "should": [
            {
              "term": {
                "title.keyword": {
                  "value": "My dog barks"
                }
              }
            },
            {
              "term": {
                "content.keyword": {
                  "value": "barking dogs"
                }
              }
            }
          ],
          "minimum_should_match": 1
        }
      }
    }

b. 嵌套bool搜索

GET /blogs/_search
    {
      "query": {
        "bool": {
          "must": [
            {
              "term": {
                "author_id": {
                  "value": "11403"
                }
              }
            }
          ],
          "should": [
            {
              "bool": {
                "must_not": [
                  {
                    "term": {
                      "post_date": {
                        "value": "2020-01-02"
                      }
                    }
                  }
                ]
              }
            }
          ],
          "minimum_should_match": 1
        }
      }
    }

c. 排序与分页

GET /blogs/_search
    {
      "query": {
        "bool": {
          "must": [
            {
              "range": {
                "post_date": {
                  "gte": "2020-01-01",
                  "lte": "2020-01-03"
                }
              }
            }
          ]
        }
      },
      "sort": [
        {
          "author_id": {
            "order": "desc"
          }
        }
      ],
      "from": 0,
      "size": 2
    }

**filter**

基础匹配API中讲述的match, match\_phrase, dis\_max, multi\_match, term是基础的搜索语法, filter过滤是基于它们来实现的. filter不计算相关度分数, 可以有效的利用缓存, 效率会更高.

(1) 语法

*  constant\_score
 *  bool

(2) 实例

a. constant\_score语法

constant\_score以固定的评分来执行搜索, 默认为1.

GET /blogs/_search
    {
      "query": {
        "constant_score": {
          "filter": {
            "range": {
              "post_date": {
                "gte": "2020-01-01",
                "lte": "2020-01-03"
              }
            }
          }
        }
      },
      "sort": [
        {
          "author_id": {
            "order": "desc"
          }
        }
      ],
      "from": 0,
      "size": 2
    }

b. bool语法

GET /blogs/_search
    {
      "query": {
        "bool": {
          "filter": {
            "term": {
              "post_date": "2020-01-03"
            }
          },
          "should": [
            {
              "term": {
                "title.keyword": {
                  "value": "My dog barks"
                }
              }
            },
            {
              "term": {
                "content.keyword": {
                  "value": "barking dogs"
                }
              }
            }
          ],
          "minimum_should_match": 1
        }
      }
    }

### Java API ###

下面介绍Elasticsearch Java Client 的使用, 我们来将上文的实例转化为 Java Client.

(1) main方法

public static void main(String[] args) throws IOException {
        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(
                        new HttpHost("localhost", 9200, "http")));
    
        bulkIndex(client);
    
        baseApi(client);
    
        boolNestApi(client);
    
        boolPaginationApi(client);
    
        constantScoreApi(client);
    
        boolFilterApi(client);
    
        client.close();
    }

新增文档和查询文档请求不要一起执行, 这样会查不到文档, 因为新增文档后需要1s时间进行倒排索引创建, 这也是ES被称为近实时的原因.

(2) 添加搜索数据

private static void bulkIndex(RestHighLevelClient client) throws IOException {
        BulkRequest bulkRequest = new BulkRequest();
    
        bulkRequest.add(new IndexRequest("blogs").id("1")
                .source(XContentType.JSON, "post_date", "2020-01-01", "title", "Quick brown rabbits", "content", "Brown rabbits are commonly seen.", "author_id", 11401));
        bulkRequest.add(new IndexRequest("blogs").id("2")
                .source(XContentType.JSON, "post_date", "2020-01-02", "title", "Keeping pets healthy", "content", "My quick brown fox eats rabbits on a regular basis.", "author_id", 11402));
        bulkRequest.add(new IndexRequest("blogs").id("3")
                .source(XContentType.JSON, "post_date", "2020-01-03", "title", "My dog barks", "content", "I see a lot of barking dogs on the road.", "author_id", 11403));
    
        client.bulk(bulkRequest, RequestOptions.DEFAULT);
    }

(3) bool搜索基础使用

private static void baseApi(RestHighLevelClient client) throws IOException {
        SearchRequest searchRequest = new SearchRequest("blogs");
    
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
        boolQueryBuilder.must(new TermQueryBuilder("author_id", "11403"));
        boolQueryBuilder.mustNot(new RangeQueryBuilder("post_date").lte("2020-01-02"));
    
        boolQueryBuilder.should(new TermQueryBuilder("title.keyword", "My dog barks"));
        boolQueryBuilder.should(new TermQueryBuilder("content.keyword", "barking dogs"));
        boolQueryBuilder.minimumShouldMatch(1);
        searchSourceBuilder.query(boolQueryBuilder);
        searchRequest.source(searchSourceBuilder);
    
        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (SearchHit hit : hits) {
            System.out.println(hit.getSourceAsString());
        }
    }

(4) 嵌套bool搜索

private static void boolNestApi(RestHighLevelClient client) throws IOException {
        SearchRequest searchRequest = new SearchRequest("blogs");
    
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
        boolQueryBuilder.must(new TermQueryBuilder("author_id", "11403"));
    
        BoolQueryBuilder boolQueryBuilder2 = new BoolQueryBuilder();
        boolQueryBuilder2.mustNot(new TermQueryBuilder("post_date", "2020-01-02"));
        boolQueryBuilder.should(boolQueryBuilder2);
    
        boolQueryBuilder.minimumShouldMatch(1);
        searchSourceBuilder.query(boolQueryBuilder);
        searchRequest.source(searchSourceBuilder);
    
        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (SearchHit hit : hits) {
            System.out.println(hit.getSourceAsString());
        }
    }

(5) 排序与分页

private static void boolPaginationApi(RestHighLevelClient client) throws IOException {
        SearchRequest searchRequest = new SearchRequest("blogs");
    
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
        boolQueryBuilder.must(new RangeQueryBuilder("post_date").gte("2020-01-01").lte("2020-01-03"));
        searchSourceBuilder.query(boolQueryBuilder);
        searchSourceBuilder.sort("author_id", SortOrder.DESC);
        searchSourceBuilder.from(0);
        searchSourceBuilder.size(2);
        searchRequest.source(searchSourceBuilder);
    
        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (SearchHit hit : hits) {
            System.out.println(hit.getSourceAsString());
        }
    }

(6) constant\_score

private static void constantScoreApi(RestHighLevelClient client) throws IOException {
        SearchRequest searchRequest = new SearchRequest("blogs");
    
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    
        RangeQueryBuilder rangeQueryBuilder = new RangeQueryBuilder("post_date").gte("2020-01-01").lte("2020-01-03");
        ConstantScoreQueryBuilder constantScoreQueryBuilder = new ConstantScoreQueryBuilder(rangeQueryBuilder);
        searchSourceBuilder.postFilter(constantScoreQueryBuilder);
        searchSourceBuilder.sort("author_id", SortOrder.DESC);
        searchSourceBuilder.from(0);
        searchSourceBuilder.size(2);
    
        searchRequest.source(searchSourceBuilder);
    
        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (SearchHit hit : hits) {
            System.out.println(hit.getSourceAsString());
        }
    }

(7) filter

private static void boolFilterApi(RestHighLevelClient client) throws IOException {
        SearchRequest searchRequest = new SearchRequest("blogs");
    
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    
        BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
        RangeQueryBuilder rangeQueryBuilder = new RangeQueryBuilder("post_date").gte("2020-01-01").lte("2020-01-03");
        boolQueryBuilder.filter(rangeQueryBuilder);
    
        TermsQueryBuilder termsQueryBuilder1 = new TermsQueryBuilder("title.keyword", "My dog barks");
        TermsQueryBuilder termsQueryBuilder2 = new TermsQueryBuilder("content.keyword", "barking dogs");
        boolQueryBuilder.should(termsQueryBuilder1);
        boolQueryBuilder.should(termsQueryBuilder2);
        boolQueryBuilder.minimumShouldMatch(1);
    
        searchSourceBuilder.query(boolQueryBuilder);
        searchRequest.source(searchSourceBuilder);
    
        SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (SearchHit hit : hits) {
            System.out.println(hit.getSourceAsString());
        }
    }

[Elasticsearch_API]: https://blog.csdn.net/litianxiang_kaola/article/details/103804382
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2xpdGlhbnhpYW5nX2thb2xh_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200102145725993.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2xpdGlhbnhpYW5nX2thb2xh,size_16,color_FFFFFF,t_70