ElasticSearch中实现模糊查询效果（类似数据库中like功能）

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ElasticSearch中实现模糊查询效果（类似数据库中like功能）

文章目录

    • ElasticSearch中实现模糊查询效果（类似数据库中like功能）
      • 场景：
      • 实现方式：
        • pom依赖：
        • 代码：
        • 测试：
        • 造数据：
        • 调用接口：

场景：

业务要求提供一个es查询功能，实现类似模糊查询效果，并且命中字段显示红色。举例说明：

es中字段内容 输入（即关键字） 是否输出
你好，中国，强大的祖国 中国 是（则‘中国’两个字飘红）
你好，中国，强大的祖国 俄国 否
你好，中国，强大的祖国 最大 否

实现方式：

这种实现方式主要是用es的query_string查询方式，不过需要对输入条件做区分处理才能实现模糊查询效果。

首先，先复习一下query_string查询方式的特点：

{
	"query": {
		"query_string": {
			"query": "中国"
		}
	},
	"size": 10,
	"from": 0,
	"sort": []
}
pom依赖：

我用的elasticsearch版本是6.8.1，springboot版本是2.3.5.RELEASE，因此pom依赖的版本不对，需要先排除再引入正确的包。

    
        org.springframework.boot
        spring-boot-starter-data-elasticsearch
        
            
                spring-data-elasticsearch
                org.springframework.data
            
        
    
    
        org.springframework.data
        spring-data-elasticsearch
        3.2.6.RELEASE
代码：
import org.apache.commons.lang3.StringUtils;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.core.CountRequest;
import org.elasticsearch.client.core.CountResponse;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightField;
import org.springframework.stereotype.Service;

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

/**
 * 弹性搜索核心服务
 *
 * @author lukou
 * @date 2023/05/15
 */
@Service
public class ElasticSearchCoreService {

    /**
     * 常量和
     */
    private static final String CONSTANT_AND = " AND ";
    /**
     * 常量不
     */
    private static final String CONSTANT_NOT = " NOT ";
    /**
     * 常量或
     */
    private static final String CONSTANT_OR = " OR ";

    @Resource
    private RestHighLevelClient restHighLevelClient;

    /**
     * 通过query_string方法查询统计
     *
     * @param index   指数
     * @param keyword 关键字
     * @return {@link CountResponse}
     * @throws IOException ioexception
     */
    public CountResponse queryCount(String index, String keyword) throws IOException {
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(this.queryString(keyword));
        CountRequest request = new CountRequest(index);
        request.source(searchSourceBuilder);
        return restHighLevelClient.count(request, RequestOptions.DEFAULT);
    }

    /**
     * 通过query_string方法查询搜索
     *
     * @param index   指数
     * @param keyword 关键字
     * @param from    起始位置
     * @param size    大小
     * @return {@link SearchResponse}
     * @throws IOException ioexception
     */
    public SearchResponse querySearch(String index, String keyword, int from, int size) throws IOException {
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(this.queryString(keyword)).highlighter(redHighlightBuilder())
                .from(from)
                .size(size);
        SearchRequest request = new SearchRequest(index);
        // preference解决分页数据不准确的问题(和分片有关系)
        request.source(searchSourceBuilder).preference(String.valueOf(keyword.hashCode()));
        return restHighLevelClient.search(request, RequestOptions.DEFAULT);
    }

    /**
     * 通过query_string方法查询字符串
     * 按照逻辑表达式切割（AND OR NOT）
     *
     * 
     * "123 AND abc"
     * "123 OR abc"
     * "123 NOT abc"
     * "NOT 123 NOT abc"
     * 


     *
     * @param key 关键
     * @return {@link QueryBuilder}
     */
    public QueryBuilder queryString(String key) {
        //Bool查找
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        if (StringUtils.contains(key, CONSTANT_AND)) {
            // 包含AND
            String[] keys = key.split(CONSTANT_AND);
            for (String s : keys) {
                boolQueryBuilder.must(QueryBuilders.queryStringQuery(convert(s)));
            }
            return boolQueryBuilder;
        } else if (StringUtils.contains(key, CONSTANT_OR)) {
            String[] keys = key.split(CONSTANT_OR);
            for (String s : keys) {
                boolQueryBuilder.should(QueryBuilders.queryStringQuery(convert(s)));
            }
            return boolQueryBuilder;
        } else if (StringUtils.contains(key, CONSTANT_NOT)) {
            List keys = new ArrayList(Arrays.asList(key.split(CONSTANT_NOT)));
            if (keys.get(0).startsWith("NOT ")) {
                keys.set(0, keys.get(0).replaceAll("Not ", ""));
                for (String s : keys) {
                    boolQueryBuilder.mustNot(QueryBuilders.queryStringQuery(convert(s)));
                }
                return boolQueryBuilder;
            }
            String keyword = keys.remove(0);
            boolQueryBuilder.must(QueryBuilders.queryStringQuery(convert(keyword)));
            for (String s : keys) {
                boolQueryBuilder.mustNot(QueryBuilders.queryStringQuery(convert(s)));
            }
            return boolQueryBuilder;
        }
        boolQueryBuilder.must(QueryBuilders.queryStringQuery(convert(key)));
        return boolQueryBuilder;
    }


    /**
     * 转换
     * 判断是不是字母、数字、汉字
     *
     * @param key 关键
     * @return {@link String}
     */
    public String convert(String key) {
        //在执行查询时，搜索的词不会被分词器分词，而是直接以一个短语的形式查询
        String res = "\"" + key + "\"";
        if (key.matches("^[A-Za-z0-9]*$")) {
            res = "*" + key + "*";
        }
        if (key.matches("^[\u4e00-\u9fa5][A-Za-z0-9]*$")) {
            res = key + "*";
        }
        return res;
    }


    /**
     * 红色突出显示生成器
     *
     * @return {@link HighlightBuilder}
     */
    public HighlightBuilder redHighlightBuilder() {
        HighlightBuilder highlightBuilder = new HighlightBuilder();
        //高亮的字段
        highlightBuilder.field("*");
        //是否多个字段都高亮
        highlightBuilder.requireFieldMatch(true);
        //前缀后缀
        highlightBuilder.preTags("");
        highlightBuilder.postTags("");
        return highlightBuilder;
    }


    /**
     * 构建突出标记
     *
     * @param hits 支安打
     * @return {@link List}<{@link Map}>
     */
    public List<Map> buildHighlightTags(SearchHit[] hits) {
        //解析结果
        List<Map> result = new LinkedList();
        for (SearchHit hit : hits) {
            //解析高亮的字段
            //获取高亮字段
            Map highlightFields = hit.getHighlightFields();
            Map sourceAsMap = hit.getSourceAsMap();
            for (String s : highlightFields.keySet()) {
                if (s != null) {
                    sourceAsMap.put(s, highlightFields.get(s).getFragments()[0].toString());//替换掉原来的内容
                }
            }
            result.add(sourceAsMap);
        }
        return result;
    }
}


测试：


import org.elasticsearch.action.search.SearchResponse;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

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

@RestController
public class TestController {

    @Resource
    private ElasticSearchCoreService elasticSearchCoreService;

    @GetMapping("/test")
    public Map test(String index, String keyword) throws IOException {
        SearchResponse searchResponse = elasticSearchCoreService.querySearch(index, keyword, 0, 10);
        long total = searchResponse.getHits().getTotalHits();
        List<Map> mapList = elasticSearchCoreService.buildHighlightTags(searchResponse.getHits().getHits());
        Map result = new HashMap();
        result.put("total", total);
        result.put("data", mapList);
        return result;
    }
}



造数据：


新建索引tmp_1以及插入5条数据


PUT http://localhost:9200/tmp_1

{
	"settings": {
		"number_of_shards": 1,
		"number_of_replicas": 0
	},
	"mappings": {
		"_doc": {
			"properties": {
				"@timestamp": {
					"type": "date"
				},
				"@version": {
					"type": "text",
					"fields": {
						"keyword": {
							"type": "keyword",
							"ignore_above": 256
						}
					}
				},
				"name": {
					"type": "keyword"
				},
				"sfz": {
					"type": "text"
				},
				"content": {
					"type": "text"
				},
				"address": {
					"type": "text"
				}
			}
		}
	}
}



POST http://localhost:9200/tmp_1/_doc

{
	"@version": "1",
	"@timestamp": "2020-06-19T09:06:26.446Z",
	"name": "唐伯虎",
	"sfz": "3212111990018989",
	"content": "当你无话可说的时候就别说话，在你不知如何回答别人的话的时候就保持沉默，这就是生活中一个很好的策略",
	"address": "江苏省南京市"
}



POST http://localhost:9200/tmp_1/_doc

{
	"@version": "1",
	"@timestamp": "2020-06-19T09:06:26.446Z",
	"name": "唐伯龙",
	"sfz": "3212111990018989",
	"content": "凡事都有偶然的凑巧，结果却又如宿命的必然",
	"address": "江苏省无锡市"
}



POST http://localhost:9200/tmp_1/_doc

{
	"@version": "1",
	"@timestamp": "2020-06-19T09:06:26.446Z",
	"name": "唐小虎",
	"sfz": "321211199709227654",
	"content": "一个人如果刻意逃避他所惧怕的东西，到头来会发现自己只是抄了近路去见它",
	"address": "江苏省苏州市"
}



POST http://localhost:9200/tmp_1/_doc

{
	"@version": "1",
	"@timestamp": "2020-06-19T09:06:26.446Z",
	"name": "李小龙",
	"sfz": "1234211186709222348",
	"content": "虫子被踩后缩起来，这是明智的，它借此减少重新被踩的概率。用道德的语言就叫:谦恭",
	"address": "江苏省常州市"
}



POST http://localhost:9200/tmp_1/_doc

{
	"@version": "1",
	"@timestamp": "2020-06-19T09:06:26.446Z",
	"name": "李四",
	"sfz": "436754187709087623",
	"content": "你好，1234，你好5678",
	"address": "上海市"
}



调用接口：


http://localhost:8081/test?index=tmp_1&keyword=你好
# 响应
{
    "total": 1,
    "data": [
        {
            "@timestamp": "2020-06-19T09:06:26.446Z",
            "address": "上海市",
            "sfz": "436754187709087623",
            "@version": "1",
            "name": "李四",
            "content": "你好，1234，你好5678"
        }
    ]
}



http://localhost:8081/test?index=tmp_1&keyword=唐小虎
# 响应
{
    "total": 1,
    "data": [
        {
            "@timestamp": "2020-06-19T09:06:26.446Z",
            "address": "江苏省苏州市",
            "sfz": "321211199709227654",
            "@version": "1",
            "name": "唐小虎",
            "content": "一个人如果刻意逃避他所惧怕的东西，到头来会发现自己只是抄了近路去见它"
        }
    ]
}



测试场景没有全面覆盖，如有错误，欢迎指正。

                                                        
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