全文检索ElasticSearch（整合Springboot实战操作）

添加依赖

 
    
        7.4.2
    

    
    
        
            org.elasticsearch.client
            elasticsearch-rest-high-level-client
            7.4.2
        
    

修改配置文件

server:
  port: 83

spring:
  application:
    name: service-util
  cloud:
    nacos:
      discovery:
        server-addr: 外网IP:8848
        username: nacos
        password: kgcqh
  redis:
    host: 外网IP
    port: 6379
    database: 0
    password: kgcqh

management:
  endpoints:
    web:
      exposure:
        include: "*"

es:
  hostname: 外网IP
  port: 9200
  protocol: http

创建RestHighLevelClient对象

@Configuration
@ConfigurationProperties(prefix = "es")
@Setter
public class ElasticSearchConfig {
    private String hostname;
    private int port;
    private String protocol;

    //请求的一些选项
    public static final RequestOptions COMMON_OPTIONS;

    static{
        RequestOptions.Builder builder=RequestOptions.DEFAULT.toBuilder();
        COMMON_OPTIONS=builder.build();
    }

    @Bean
    public RestHighLevelClient restHighLevelClient(){
        RestClientBuilder restClientBuilder=
                RestClient.builder(new HttpHost(hostname,port,protocol));

        RestHighLevelClient restHighLevelClient=
                new RestHighLevelClient(restClientBuilder);

        return restHighLevelClient;
    }

}

package cn.kgc.qh.util;

import cn.kgc.qh.config.ElasticSearchConfig;
import cn.kgc.qh.entity.Company;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.baomidou.mybatisplus.annotation.TableId;
import com.fasterxml.jackson.core.JsonParser;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang.StringUtils;
import org.elasticsearch.action.bulk.BulkRequest;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.action.delete.DeleteResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchScrollRequest;
import org.elasticsearch.action.update.UpdateRequest;
import org.elasticsearch.action.update.UpdateResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.unit.Timevalue;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.Scroll;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.Aggregation;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.aggregations.metrics.Cardinality;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;

import javax.annotation.Resource;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;



@Component
@Slf4j
public class ESUtil {

    @Resource
    private RestHighLevelClient restHighLevelClient;


    
    public  boolean saveBatch(String index,List bachList){
        BulkRequest bulkRequest=new BulkRequest();

        //封装保存的数据
        for(int i=0;i T select(String index,String id, Class targetClass){

        SearchRequest searchRequest=new SearchRequest();
        searchRequest.indices(index);
        //构建查询条件
        SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
        searchSourceBuilder.query(QueryBuilders.termQuery("_id",id));
        searchRequest.source(searchSourceBuilder);

        try {
           SearchResponse searchResponse= restHighLevelClient.search(searchRequest,ElasticSearchConfig.COMMON_OPTIONS);
           SearchHits hits= searchResponse.getHits();
           SearchHit [] searchHits= hits.getHits();  //查询结果
           if(searchHits==null||searchHits.length==0){  //如果数组为空,表示没有查询结果
               return null;
           }
           String jsonString= searchHits[0].getSourceAsString();
           T t= JSON.parseObject(jsonString,targetClass);
           return t;
        } catch (IOException e) {
            e.printStackTrace();
        }
        return null;
    }

    
    public   List select(String index,Class targetClass,
                                            SearchSourceBuilder searchSourceBuilder){
        SearchRequest searchRequest=new SearchRequest(); //查询请求
        searchRequest.indices(index);
        searchRequest.source(searchSourceBuilder); //请求中添加中查询条件
        List list=new ArrayList<>();
        try {
            //执行查询,获得查询结果
            SearchResponse searchResponse=
                    restHighLevelClient.search(searchRequest,ElasticSearchConfig.COMMON_OPTIONS);
            SearchHits hits= searchResponse.getHits();  //封装结果
            SearchHit[] searchHits= hits.getHits();
            for(SearchHit searchHit:searchHits){
               String jsonString= searchHit.getSourceAsString();
               T t=JSON.parseObject(jsonString,targetClass);
               list.add(t);
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
        return list;
    }

    
    public  Map page(String index,
                                        SearchSourceBuilder searchSourceBuilder,
                                        Class targetClass,int from,int size){
        SearchRequest searchRequest=new SearchRequest();
        searchRequest.indices(index);
        searchSourceBuilder.from(from);
        searchSourceBuilder.size(size);
        searchRequest.source(searchSourceBuilder);
        Map result=new HashMap<>();
        List resultList=new ArrayList<>();
        int page=0;
        try {
          SearchResponse searchResponse=
                  restHighLevelClient.search(searchRequest,ElasticSearchConfig.COMMON_OPTIONS);
          SearchHits hits=  searchResponse.getHits();
          long totalValue=hits.getTotalHits().value; //获得总记录数    3.0/2=1.5    Math.ceil(1.5)   2.0;
          page  = (int) Math.ceil((double)totalValue/size); //总页数
          SearchHit [] searchHits=  hits.getHits();
          for(SearchHit searchHit:searchHits){
             String jsonString= searchHit.getSourceAsString();
             T t= JSON.parseObject(jsonString,targetClass);
             resultList.add(t);
          }
        } catch (IOException e) {
            e.printStackTrace();
        }
        result.put("page",page);
        result.put("list",resultList);
        return result;
    }


    
    public  Map page(String index,
                                SearchSourceBuilder searchSourceBuilder,
                                Class targetClass,int size,String scrollId){
        SearchRequest searchRequest=new SearchRequest();
        searchRequest.indices(index);

        Scroll scroll=new Scroll(Timevalue.timevalueMinutes(1)); //指定scroll镜像的时间为1分钟
        searchSourceBuilder.size(size); //每页显示多少条记录
        Map map=new HashMap<>();
        SearchResponse searchResponse=null;
        try {
            if(StringUtils.isBlank(scrollId)){ //scroll方式的第一次查询
               searchRequest.scroll(scroll); //查询是scroll查询 镜像的时间为1分钟
               searchRequest.source(searchSourceBuilder);  //查询请求中添加查询条件
               searchResponse=restHighLevelClient.search(searchRequest,ElasticSearchConfig.COMMON_OPTIONS);
            }else{   //scroll方式的后面查询   请求:GET /_search/scroll
                SearchScrollRequest searchScrollRequest=new SearchScrollRequest();
                searchScrollRequest.scroll(scroll);
                searchScrollRequest.scrollId(scrollId);
                searchResponse=restHighLevelClient.scroll(searchScrollRequest,ElasticSearchConfig.COMMON_OPTIONS);
            }
            //封装查询结果
            map= searchResponseToMap(searchResponse,size,targetClass);
        } catch (IOException e) {
            e.printStackTrace();
        }
        return map;
    }

    //当前页的数据    scrollId    总页数
    private  Map
                      searchResponseToMap(SearchResponse searchResponse,int size,Class targetClass){
        SearchHits hits= searchResponse.getHits(); //查询的结果

        double count=hits.getTotalHits().value; //获得总记录数
        int page=  (int)Math.ceil(count/size);  //算出总页数
        Map map=new HashMap<>();  //返回的结果
        List list=new ArrayList<>();   //当前页的数据
        SearchHit [] searchHits=  hits.getHits(); //获得hits中的数据


        for(SearchHit temp:searchHits){
           String jsonString= temp.getSourceAsString();
           T t=JSON.parseObject(jsonString,targetClass);
           list.add(t);
        }
        map.put("page",page);
        map.put("scrollId",searchResponse.getScrollId());
        map.put("list",list);
        return map;
    }
}

下面解释一下分页(我这里有两种)

from:从第几条开始 size:显示多少条记录

GET /students/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "name": "scott"
          }
        }
      ]
    }
  },
  "from": 0,
  "size": 10
}

深度查询问题(使用from+size分页查询, 限制下分页的页数)

分页查询数据,每页显示10条记录
我们可以假设在一个有5个主分片的索引中搜索。 当我们请求结果的第一页,每一个分片产生前 10 的结果，并且返回给 协调节点。协调节点对50个结果排序得到全部结果的前10个。

现在假设我们请求第1000页，从 10001 到 10010 。所有都以相同的方式工作除了每个分片不得不产生前10010个结果。然后协调节点对全部50050个结果排序最后丢弃掉这些结果中的 50040 个结果。

可以看到，在分布式系统中，对结果排序的成本随分页的深度成指数上升。

缺点:有深度查询问题, 在数据量比较少时,或者限制分页的页数时可以使用

第一次请求传入size条数, 按照_doc排序。请求地址上scroll=1m 表示此次查询的会话是一分钟,并且在这一分钟内不会查询到向ES中添加的新的数据。

GET /company-index/_search?scroll=1m
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "_doc": {
        "order": "desc"
      }
    }
  ],
  "size": 2
}

后面的查询指定第一次插入获得的scroll_id,后面不需要在传入size参数

GET /_search/scroll
{
  "scroll_id" : "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAEGAUWMlRKYnQzcW1RMDJBeVhnODF6ekxTQQ==",
  "scroll": "1m"
}

scroll每个批次查询的条数是: size * number_of_primary_shards

缺点: 数据并不是实时的。

PUT my-index-000001/_doc/1
{
  "group" : "fans",
  "user" : [ 
    {
      "first" : "John",
      "last" :  "Smith"
    },
    {
      "first" : "Alice",
      "last" :  "White"
    }
  ]
}

实际在ES中存储时会将存储的数据扁平化处理

{
  "group" :        "fans",
  "user.first" : [ "Alice", "John" ],
  "user.last" :  [ "Smith", "White" ]
}

执行以下查询语句

GET my-index-000001/_search
{
  "query": {
    "bool": {
      "must": [
        { "match": { "user.first": "Alice" }},
        { "match": { "user.last":  "Smith" }}
      ]
    }
  }
}

应该查不到数据,但实际会查询到数据。

我们可以使用Nested类型 修改映射

DELETE my-index-000001

PUT my-index-000001
{
  "mappings": {
    "properties": {
      "user": {
        "type": "nested" 
      }
    }
  }
}

在执行保存操作

PUT my-index-000001/_doc/1
{
  "group" : "fans",
  "user" : [
    {
      "first" : "John",
      "last" :  "Smith"
    },
    {
      "first" : "Alice",
      "last" :  "White"
    }
  ]
}

使用以下语句在次查询

GET my-index-000001/_search
{
  "query": {
    "nested": {
      "path": "user",
      "query": {
        "bool": {
          "must": [
            { "match": { "user.first": "Alice" }},
            { "match": { "user.last":  "Smith" }} 
          ]
        }
      }
    }
  }
}

总结:

ES如果有一个属性是一个对象数组,在创建映射的时候,要指定该属性的类型是nested类型。否则ES对该属性进行扁平化处理。

发现符合我们的预期,没有查询到结果