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。

<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-elasticsearch</artifactId><exclusions><exclusion><artifactId>spring-data-elasticsearch</artifactId><groupId>org.springframework.data</groupId></exclusion></exclusions></dependency><dependency><groupId>org.springframework.data</groupId><artifactId>spring-data-elasticsearch</artifactId><version>3.2.6.RELEASE</version></dependency>
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 */@Servicepublic 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 ";@Resourceprivate 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ANDString[] 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<String> 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<String, Object>> buildHighlightTags(SearchHit[] hits) {//解析结果List<Map<String, Object>> result = new LinkedList<>();for (SearchHit hit : hits) {//解析高亮的字段//获取高亮字段Map<String, HighlightField> highlightFields = hit.getHighlightFields();Map<String, Object> 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;@RestControllerpublic class TestController {@Resourceprivate ElasticSearchCoreService elasticSearchCoreService;@GetMapping("/test")public Map<String, Object> test(String index, String keyword) throws IOException {SearchResponse searchResponse = elasticSearchCoreService.querySearch(index, keyword, 0, 10);long total = searchResponse.getHits().getTotalHits();List<Map<String, Object>> mapList = elasticSearchCoreService.buildHighlightTags(searchResponse.getHits().getHits());Map<String, Object> 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。