ELK-全文检索技术-使用总结

 

 

一.概念

1.1 基础概念

ELK: 是ElasticSearch,LogStash以及Kibana三个产品的首字母缩写

 

lucene : apache 的全文搜索引擎工具包

 

elasticsearch : ElasticSearch是一个基于全文检索引擎lucene实现的一个面向文档的schema free的数据库。所有对数据库的配置、监控及操作都通过Restful接口完成。数据格式为json。默认支持节点自动发现,数据自动复制,自动分布扩展,自动负载均衡。适合处理最大千万级别的数据的检索。处理效率非常高。可以理解为elasticSearch是一个在lucene基础上增加了restful接口及分布式技术的整合。

 

elasticsearch : http协议访问默认使用9200端口

elasticsearch : tcp协议访问默认使用9300端口

 

操作elasticsearch的四种方式:

Kibana:使用http

原始的api:使用tcp

RestAPI:使用http

Sde(SpringDataElasticsearch): 使用tcp

 

tcp传输效率比http高

1.2 elasticsearch概念

Index:存储数据的逻辑区域,类似关系型数据库中的database,是文档的命名空间。如下图的湖蓝色部分所示,Index为twitter。

         Type:类似关系型数据库中的Table,是包含一系列field的json数据。储存一系列类似的field。如下图的黄色部分所示,Type为tweet。不同document里面同名的field一定要是相同类型的。

        Document:存储的实体数据,类似关系型数据库中的Row,是具体的包含一组filed的资料。如下图橙色部分所示,包含user,post_data,message三个field。

         Field:即关系型数据库中Column, Document的一个组成部分,有两个部分组成,name和value。如下图紫色部分所示 post_date及其具体的值就是一个field。

        Mapping:存储field的相关映射信息,不同document type会有不同的mapping。

        Term:不可分割的单词,搜索最小单元。不同的分析器对同样的内容的分析结果是不同的。也就得到不同的term。

        Token:一个Term呈现方式,包含这个Term的内容,在文档中的起始位置,以及类型。

        Node:对应这关系型数据库中的数据库实例。

        Cluster:由多个node组成的一组服务实例。

        Shard:关系型数据库中无此概念,是Lucene搜索的最小单元。一个index可能会存在于多个shards,不同shards可能在不同nodes。一个lucene index在es中我们称为一个shard,而es中的index则是一系列shard。当es执行search操作,会将请求发送到这个index包含的所有shard上去,然后将没一个shard上的执行结果搜集起来作为最终的结果。shard的个数在创建索引之后不能改变!

        Replica:shard的备份,有一个primary shard,其余的叫做replica shards。Elasticsearch采用的是Push Replication模式,当你往 master主分片上面索引一个文档,该分片会复制该文档(document)到剩下的所有 replica副本分片中,这些分片也会索引这个文档 

文档的录入时,Elasticsearch通过对docid进行hash来确定其放在哪个shard上面,然后在shard上面进行索引存储。

 

和数据库的对应:

mysql数据库

ES

Database

Indices   index的复数

Table

Type  一般一个索引库中只有一个type

数据

Document

约束 列存储什么数据类型之类的

Mapping 规定字段什么数据类型、什么分词器

Column

Field

 

 

二.Kibana操作索引库

1.     连接

 ELK-全文检索技术-使用总结_第1张图片

 

 

 

2.     操作

 

创建类型并且制定每个字段的属性(数据类型、是否存储、是否索引、哪种分词器

 

put ahd/_mapping/goods

{

  "properties":{

    "goodsName":{

      "type":"text",

      "analyzer":"ik_max_word",

      "index":"true",

      "store":"true"

    },

    "price":{

      "type":"double",

      "index":"true",

      "store":"false"

    },

    "brand":{

      "type":"keyword",

      "index":"true",

      "store":"true"

    }

  }

}

 

 

查询创建的索引/映射

get ahd/_mapping[/goods]

 

 

分片5,副本1

put /heima

{

  "settings":{

    "number_of_shards":5,

    "number_of_replicas":1

  }

}

创建索影库2

put ahd2

 

 

创建索引库及其字段

put ahd2

{

  "mappings":{

    "goods":{

      "properties":{

        "goodsname":{

        "analyzer":"ik_max_word",

        "type":"text",

        "store":"true",

        "index":"true"

      },

      "price":{

        "type":"double",

        "index":"true",

        "store":"true"

      },

      "brand":{

        "type":"text",

        "index":"true",

        "store":"true"

      }

      }

     

    }

  }

}

 

添加一条数据:指定id的新增

 

post ahd/goods/1

{

  "goodsname":"华为p20手机",

  "brand":"华为",

  "price":2299

}

 

 

根据id查询记录

get ahd/goods/1

 

修改,

 

post ahd/goods/1

{

  "goodsname":"华为p20手机",

  "brand":"华为",

  "price":2599

}

 

不指定id插入一条数据

 

post ahd/goods

{

  "goodsname":"小米手机6",

  "brand":"小米",

  "price":"2500"

}

 

插入数据最好还是使用post,修改数据使用put

 

使用put和使用post是一样的效果

 

 

指定id删除一条数据

delete ahd/goods/IkXNN2wBr0WPOOKNJpRg

 

 

自定义模板

1. 首先先添加一个索引库,

put ahd3

{

  "mappings":{

    "goods":{

       "properties":{

          "image":{

            "type":"text",

            "index":"false",

            "store":"true"

          },

          "goodsname":{

        "analyzer":"ik_max_word",

        "type":"text",

        "store":"true",

        "index":"true"

      },

      "price":{

        "type":"double",

        "index":"true",

        "store":"true"

      },

      "brand":{

        "type":"text",

        "index":"true",

        "store":"true"

      }

        }

    }

  }

}

 

 

在添加的这个索引库基础上添加模板(改动添加语句)

 

put ahd3

{

  "mappings":{

    "goods":{

       "properties":{

          "image":{

            "type":"text",

            "index":"false",

            "store":"true"

          },

          "goodsname":{

        "analyzer":"ik_max_word",

        "type":"text",

        "store":"true",

        "index":"true"

      },

      "price":{

        "type":"double",

        "index":"true",

        "store":"true"

      },

      "brand":{

        "type":"text",

        "index":"true",

        "store":"true"

      }

        } ,

        "dynamic_templates":[

          {

            "mystring":{

              "match_mapping_type":"string",

              "mapping":{

                "type":"keyword"

              }

            }

          }

          ]

       

    }

  }

}

 

 

新增数据还就只能使用post

 

 

在ahd3中新添加一条数据

post ahd3/goods

{

  "goodsname":"小米6X手机",

  "price":1199,

  "image":"http://image.im.com/123.jpg",

  "brand":"小米"

}

 

 

查询goods document 

get ahd3/_mapping/goods

 

 

=====================================================================

=====================================================================

=========================查询(重点)==================================

=====================================================================

=====================================================================

 

1.查询所有

get ahd3/_search

{

  "query":{

    "match_all": {

     

    }

  }

}

 

 

2.term查询:精确查询

 

get ahd3/_search

{

  "query":{

    "term":{

      "goodsname":"小米"

    }

  }

}

 

 

注意,第一行不能有大括号{

 

*.在添加一条数据,进行测试,

post ahd3/goods

{

  "goodsname":"大米",

  "brand":"吊牌",

  "price":200,

  "image":"http://localhost:8080/a.jpg"

}

 

 

进行查询测试

get ahd3/_search

{

  "query":{

    "term":{

      "goodsname": "小米"

    }

  }

}

 

 

 

插入一条新的记录

post ahd3/goods

{

  "goodsname":"大米手机",

  "price":20000,

  "brand":"大米",

  "image":"http://baidu.com/a.jpg"

}

 

 

3.分词查询match测试

get ahd3/_search

{

  "query":{

    "match": {

      "brand":"米"

    }

  }

}

 

 

 

2.4    Range范围查询

get ahd3/_search

{

  "query":{

      "range":{

      "price":{

        "lte":1000,

        "gte":100

      }

        }

  }

 

}

 

 

新添加一条数据

post ahd3/goods

{

  "goodsname":"appla",

  "brand":"apple",

  "price":5000,

  "image":"http://www.baidu.com/sadf.jpg"

}

 

2.5    Fuzzy容错

 

get ahd3/goods/_search

{

  "query":{

    "fuzzy":{

      "goodsname":{

        "value": "apple",

        "fuzziness": 1

      }

    }

  }

}

 

2.6    Bool组合查询

 

get ahd3/goods/_search

{

  "query":{

    "bool": {

      "must":{

        "match":{

          "goodsname":"大米"

        }

       

      }

      }

  }

}

 

测试json书写是否正确

 

get ahd3/goods/_search

{

  "query":{

    "bool": {

      "must":[{

                "match":{

          "goodsname":"大米"

        }

      },{

                "term":{

          "brand":"大米"

        }

      }

 

      ]

      }

  }

}

 

 

显示字段的过滤

 

只显示goodsname

 

get ahd3/_search

{

  "_source":{

    "includes":["goodsname"]

  }

}

 

排除goodsname

 

get ahd3/_search

{

  "_source":{

    "excludes":["goodsname"]

  }

}

 

 

3.2    、查询结果的过滤

 

查询结果的过滤

 

get ahd3/_search

{

  "query":{

    "bool": {

      "must": {

          "term":{

            "goodsname":"小米"

          }

        },

        "filter":{

            "range": {

              "price": {

                "gte": 10,

                "lte": 20000

              }

            }

          }

     

    }

  }

}

 

 

分页:

get ahd3/_search

{

  "query":{

    "match_all": {

     

    }

  },

  "from":2,

  "size":2

}

 

排序倒序

get ahd3/_search

{

  "query":{

    "match_all": {

     

    }

  },

  "sort":{

    "price":"desc"

  }

 

}

 

 

 

高亮

 

get ahd3/_search

{

  "query":{

    "term": {

      "goodsname": {

        "value": "小米"

      }

    }

  },

  "highlight":{

    "pre_tags":"",

    "post_tags":"",

    "fields":{

      "goodsname":{}

    }

  }

}

 

聚合:

get /ahd3/goods/_search

{

   "size":0,

   "aggs":{

     "populor_color":{

       "terms": {

         "field": "price",

         "size": 10

       }

      

     }

   }

}

 

 

三.原始的api操作索引库(tcp:9300)

2.1导入依赖

<dependencies>
    <dependency>
        <groupId>org.elasticsearch.clientgroupId>
        <artifactId>transportartifactId>
        <version>6.2.4version>
    dependency>

    <dependency>
        <groupId>junitgroupId>
        <artifactId>junitartifactId>
        <version>4.12version>
    dependency>

            com.alibaba

            fastjson

            1.2.35

       
dependencies>

 

 

 

2.2原始api操作索引库

TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)


public class EsManager {

    private TransportClient client = null;

    @Before
    public void  init() throws Exception{
        client = new PreBuiltTransportClient(Settings.EMPTY)
                .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), 9300));
    }

    @After
    public void end(){
        client.close();
    }

}

 

 

第三步:各种查询

 

   @Test
    public void queryTest() throws Exception{
//        QueryBuilder queryBuilder = QueryBuilders.matchAllQuery();

//        QueryBuilder queryBuilder = QueryBuilders.matchQuery("goodsName","小米手机");

//        QueryBuilder queryBuilder = QueryBuilders.termQuery("goodsName","小米");

//        FuzzyQueryBuilder queryBuilder = QueryBuilders.fuzzyQuery("goodsName", "大米");
//        queryBuilder.fuzziness(Fuzziness.ONE);

//        QueryBuilder queryBuilder = QueryBuilders.rangeQuery("price").gte(1000).lte(2000);

        BoolQueryBuilder queryBuilder = QueryBuilders.boolQuery();
        queryBuilder.must(QueryBuilders.rangeQuery("price").gte(1000).lte(8000));
        queryBuilder.mustNot(QueryBuilders.termQuery("goodsName", "华为"));

        SearchResponse searchResponse = client.prepareSearch("heima").setQuery(queryBuilder).get();

        SearchHits searchHits = searchResponse.getHits();
        long totalHits = searchHits.getTotalHits();
        System.out.println("总记录数:"+totalHits);
        SearchHit[] hits = searchHits.getHits();
        for (SearchHit hit : hits) {
            String sourceAsString = hit.getSourceAsString();
            Goods goods = JSON.parseObject(sourceAsString, Goods.class);
            System.out.println(goods);
        }
    }

 

 

四.RestAPI操作索引库(http:9200)

3.1 坐标

        org.springframework.boot

        spring-boot-starter-parent

        2.1.3.RELEASE

   

   

       

            org.springframework.boot

            spring-boot-starter-test

       

       

            org.springframework.boot

            spring-boot-starter-logging

       

       

            com.google.code.gson

            gson

            2.8.5

       

       

            org.apache.commons

            commons-lang3

            3.8.1

       

       

            org.elasticsearch.client

            elasticsearch-rest-high-level-client

            6.4.3

       

   

   

       

           

                org.springframework.boot

                spring-boot-maven-plugin

           

       

   

 

 

3.2 RestAPI操作索引库

1.初始化client 

private   RestHighLevelClient client = null;
private Gson gson = new Gson();
@Before
public void init(){
    client = new RestHighLevelClient(
            RestClient.builder(
                    new HttpHost("localhost", 9201, "http"),
                    new HttpHost("localhost", 9202, "http"),
                    new HttpHost("localhost", 9203, "http")));

}

 

2.准备pojo对象(使用lombok)

@Data
@AllArgsConstructor  //全参构造方法
@NoArgsConstructor  //无参构造方法
public class Item implements Serializable{
    private Long id;
    private String title; //标题
   
private String category;// 分类
   
private String brand; // 品牌
   
private Double price; // 价格
   
private String images; // 图片地址
}

 

 

 

//        新增或修改  IndexRequest
       
Item item = new Item(1L,"大米6X手机","手机","小米",1199.0,"http.jpg");
        String jsonStr = gson.toJson(item);
        IndexRequest request = new IndexRequest("item","docs",item.getId().toString());
        request.source(jsonStr, XContentType.JSON);
        client.index(request, RequestOptions.DEFAULT);

 

 

修改文档数据

就是使用上面的新增方法,它既是新增也是修改

 

根据id获取文档数据

GetRequest request = new GetRequest("item","docs","1");
GetResponse getResponse = client.get(request, RequestOptions.DEFAULT);
String sourceAsString = getResponse.getSourceAsString();
Item item = gson.fromJson(sourceAsString, Item.class);
System.out.println(item);

 

 

删除文档数据

DeleteRequest deleteRequest = new DeleteRequest("item","docs","1");
  client.delete(deleteRequest,RequestOptions.DEFAULT);

 

批量新增文档数据

 

// 准备文档数据:
List list = new ArrayList<>();
list.add(new Item(1L, "小米手机7", "手机", "小米", 3299.00,"http://image.leyou.com/13123.jpg"));
list.add(new Item(2L, "坚果手机R1", "手机", "锤子", 3699.00,"http://image.leyou.com/13123.jpg"));
list.add(new Item(3L, "华为META10", "手机", "华为", 4499.00,"http://image.leyou.com/13123.jpg"));
list.add(new Item(4L, "小米Mix2S", "手机", "小米", 4299.00,"http://image.leyou.com/13123.jpg"));
list.add(new Item(5L, "荣耀V10", "手机", "华为", 2799.00,"http://image.leyou.com/13123.jpg"));

BulkRequest bulkRequest = new BulkRequest();
for (Item item : list) {
    bulkRequest.add(new IndexRequest("item","docs",item.getId().toString()).source(JSON.toJSONString(item),XContentType.JSON)) ;
}
client.bulk(bulkRequest,RequestOptions.DEFAULT);

 

 

各种查询

 

@Test
public void testQuery() throws Exception{
    SearchRequest searchRequest = new SearchRequest("item");
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();

    searchSourceBuilder.query(QueryBuilders.matchAllQuery());
    searchSourceBuilder.query(QueryBuilders.termQuery("title","小米"));
    searchSourceBuilder.query(QueryBuilders.matchQuery("title","小米手机"));
    searchSourceBuilder.query(QueryBuilders.fuzzyQuery("title","大米").fuzziness(Fuzziness.ONE));
    searchSourceBuilder.query(QueryBuilders.rangeQuery("price").gte(3000).lte(4000));
    searchSourceBuilder.query(QueryBuilders.boolQuery().must(QueryBuilders.termQuery("title","手机"))
                                                        .must(QueryBuilders.rangeQuery("price").gte(3000).lte(3500)));
    searchRequest.source(searchSourceBuilder);
    SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
    SearchHits searchHits = searchResponse.getHits();
    long total = searchHits.getTotalHits();
    System.out.println("总记录数:"+total);
    SearchHit[] hits = searchHits.getHits();
    for (SearchHit hit : hits) {
        String sourceAsString = hit.getSourceAsString();
        Item item = JSON.parseObject(sourceAsString, Item.class);
        System.out.println(item);
    }
}

 

过滤

1、属性字段显示的过滤

searchSourceBuilder.fetchSource(new String[]{"title","category"},null);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());

 

2、查询结果的过滤

 

searchSourceBuilder.query(QueryBuilders.termQuery("title","手机"));
searchSourceBuilder.postFilter(QueryBuilders.termQuery("brand","小米"));

 

分页

searchSourceBuilder.query(QueryBuilders.matchAllQuery());
searchSourceBuilder.from(0);  //起始位置
searchSourceBuilder.size(3);  //每页显示条数

 

排序

searchSourceBuilder.sort("id", SortOrder.ASC);  // 参数1:排序的域名  参数2:顺序

 

高亮

 

构建高亮的条件

searchSourceBuilder.query(QueryBuilders.termQuery("title","小米"));
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("");
highlightBuilder.postTags("
");
highlightBuilder.field("title");

searchSourceBuilder.highlighter(highlightBuilder);

 

解析高亮的结果

 

for (SearchHit hit : hits) {

    Map highlightFields = hit.getHighlightFields();
    HighlightField highlightField = highlightFields.get("title");
   String title = highlightField.getFragments()[0].toString();

   String sourceAsString = hit.getSourceAsString();
    Item item = JSON.parseObject(sourceAsString, Item.class);
    item.setTitle(title);
    System.out.println(item);
}

 

聚合

需求:根据品牌统计数量

 

 

构建的条件代码

searchSourceBuilder.query(QueryBuilders.matchAllQuery());

searchSourceBuilder.aggregation(AggregationBuilders.terms("brandAvg").field("brand"));

 

解析结果:

 

Aggregations aggregations = searchResponse.getAggregations();
Terms terms = aggregations.get("brandAvg");
Listextends Terms.Bucket> buckets = terms.getBuckets();
for (Terms.Bucket bucket : buckets) {
    System.out.println(bucket.getKeyAsString()+":"+bucket.getDocCount());
}

 

 

 

五.SpringDataElasticsearch操作索引库

 

1.    准备环境

 

1、添加依赖

<dependency>
    <groupId>org.springframework.bootgroupId>
    <artifactId>spring-boot-starter-data-elasticsearchartifactId>
dependency>

 

2、创建引导类

 

@SpringBootApplication
public class EsApplication {
    public static void main(String[] args) {
        SpringApplication.run(EsApplication.class,args);
    }
}

 

3、添加配置文件 application.yml

 

spring:
  data:
    elasticsearch:
      cluster-name: leyou-elastic
      cluster-nodes: 127.0.0.1:9301,127.0.0.1:9302,127.0.0.1:9303

 

 

 

4、创建一个测试类,注入SDE提供的一个模板

 

@RunWith(SpringRunner.class)
@SpringBootTest
public class SpringDataEsManager {

    @Autowired
    private ElasticsearchTemplate elasticsearchTemplate;
}

 

Kibana:http

原始的api:tcp

RestAPI:http

Sde: tcp

 

2.    操作索引库和映射

第一步:准备一个pojo,并且构建和索引的映射关系

 

@Data
@AllArgsConstructor
@NoArgsConstructor
@Document(indexName="leyou",type = "goods",shards = 3,replicas = 1)
public class Goods implements Serializable{
    @Field(type = FieldType.Long)
    private Long id;
    @Field(type = FieldType.Text,analyzer = "ik_max_word",store = true)
    private String title; //标题
   
@Field(type = FieldType.Keyword,index = true,store = true)
    private String category;// 分类
   
@Field(type = FieldType.Keyword,index = true,store = true)
    private String brand; // 品牌
   
@Field(type = FieldType.Double,index = true,store = true)
    private Double price; // 价格
   
@Field(type = FieldType.Keyword,index = false,store = true)
    private String images; // 图片地址
}

 

第二步:创建索引库和映射

  @Test
    public void addIndexAndMapping(){
//        elasticsearchTemplate.createIndex(Goods.class); //根据pojo中的注解创建索引库

        elasticsearchTemplate.putMapping(Goods.class); //根据pojo中的注解创建映射
    }

 

3.    操作文档

//        新增或修改
//        Goods goods = new Goods(1L,"大米6X手机","手机","小米",1199.0,"http.jpg");
//        goodsRespository.save(goods); //save or update

//        根据id查询
//        Optional optional = goodsRespository.findById(1L);
//        Goods goods = optional.get();
//        System.out.println(goods);

//        删除
//        goodsRespository.deleteById(1L);

//        批量新增
       /* List list = new ArrayList<>();
        list.add(new Goods(1L, "小米手机7", "手机", "小米", 3299.00,"http://image.leyou.com/13123.jpg"));
        list.add(new Goods(2L, "坚果手机R1", "手机", "锤子", 3699.00,"http://image.leyou.com/13123.jpg"));
        list.add(new Goods(3L, "华为META10", "手机", "华为", 4499.00,"http://image.leyou.com/13123.jpg"));
        list.add(new Goods(4L, "小米Mix2S", "手机", "小米", 4299.00,"http://image.leyou.com/13123.jpg"));
        list.add(new Goods(5L, "荣耀V10", "手机", "华为", 2799.00,"http://image.leyou.com/13123.jpg"));

        goodsRespository.saveAll(list);*/

 

 

 

4.    查询

 

4.1 goodsRespository自带的查询

//        Iterable goodsList = goodsRespository.findAll();  //查询所有
//        Iterable goodsList = goodsRespository.findAll(Sort.by(Sort.Direction.ASC,"price")); //排序
        Iterable goodsList = goodsRespository.findAll(PageRequest.of(0,3));  //分页 page页码是从0开始代表第一页 size  5
        for (Goods goods : goodsList) {
            System.out.println(goods);
        }

 

4.2 自定义查询方法

 

可以在接口中根据规定定义一些方法就可以直接使用

 

 

public interface GoodsRespository  extends ElasticsearchRepository{

    public List findByTitle(String title);

    public List findByBrand(String brand);

    public List findByTitleOrBrand(String title,String brand);

    public List findByPriceBetween(Double low,Double high);

    public List findByBrandAndCategoryAndPriceBetween(String title,String categoty,Double low,Double high);

}

 

 

 

使用:

 

//        List goodsList = goodsRespository.findByTitle("手机");
       
List goodsList = goodsRespository.findByBrandAndCategoryAndPriceBetween("小米","手机",4000.0,5000.0);
        for (Goods goods : goodsList) {
            System.out.println(goods);
        }

 

 

5.    SpringDataElasticSearch结合原生api查询

 

1、结合native查询

 

 

@Test
    public void testQuery(){

        NativeSearchQueryBuilder nativeSearchQueryBuilder = new NativeSearchQueryBuilder();
        nativeSearchQueryBuilder.withQuery(QueryBuilders.termQuery("title", "小米"));
//        nativeSearchQueryBuilder.withQuery(QueryBuilders.matchAllQuery());
//        nativeSearchQueryBuilder.withPageable(PageRequest.of(0,3,Sort.by(Sort.Direction.DESC,"price")));

       
nativeSearchQueryBuilder.addAggregation(AggregationBuilders.terms("brandAvg").field("brand"));




AggregatedPage aggregatedPage = elasticsearchTemplate.queryForPage(nativeSearchQueryBuilder.build(), Goods.class,new GoodsHighLightResultMapper());

        Aggregations aggregations = aggregatedPage.getAggregations();
        Terms terms = aggregations.get("brandAvg");
        Listextends Terms.Bucket> buckets = terms.getBuckets();
        for (Terms.Bucket bucket : buckets) {
            System.out.println(bucket.getKeyAsString()+bucket.getDocCount());
        }


        List content = aggregatedPage.getContent();
        for (Goods goods : content) {
            System.out.println(goods);
        }


    }

 

2、自己处理高亮

 

需要自定一个用来处理高亮的实现类

 

class GoodsHighLightResultMapper implements SearchResultMapper{
        @Override
        public AggregatedPage mapResults(SearchResponse searchResponse, Class aClass, Pageable pageable) {
            List content = new ArrayList<>();
            Aggregations aggregations = searchResponse.getAggregations();
            String scrollId = searchResponse.getScrollId();
            SearchHits searchHits = searchResponse.getHits();
            long total = searchHits.getTotalHits();
            float maxScore = searchHits.getMaxScore();
            for (SearchHit searchHit : searchHits) {
                String sourceAsString = searchHit.getSourceAsString();
                T t = JSON.parseObject(sourceAsString, aClass);

                Map highlightFields = searchHit.getHighlightFields();
                HighlightField highlightField = highlightFields.get("title");
                String title = highlightField.getFragments()[0].toString();
                try {
                    BeanUtils.setProperty(t,"title",title);
                } catch (Exception e) {
                    e.printStackTrace();
                }

                content.add(t);
            }


            return new AggregatedPageImpl(content,pageable,total,aggregations,scrollId,maxScore);
//            List content, Pageable pageable, long total, Aggregations aggregations, String scrollId, float maxScore
       
}
    }

 

 

3、使用

 ELK-全文检索技术-使用总结_第2张图片

 

你可能感兴趣的:(ELK-全文检索技术-使用总结)