/**
* 查询接口
*
* @param searchReqVO
*/
public EsSearchPageInfoResVO guessYouWantListForClient(EsSearchRequestVO searchReqVO) {
BaseInfo baseInfo = getApp();
List<Long> catalogues = getAccesses();
EsSearchPageInfoResVO result = new EsSearchPageInfoResVO();
SearchRequest request = new SearchRequest();
CountRequest countRequest = new CountRequest();
countRequest.indices(INDEX_NAME);
request.indices(INDEX_NAME);
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("<em style='color: red'>");
highlightBuilder.postTags("</em>");
highlightBuilder.field("question_info");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();
boolQueryBuilder.must(QueryBuilders.matchQuery("base_info_id", baseInfo.getId()));
int shouldCount = 0;
if (!StringUtils.isEmpty(searchReqVO.getSearchText())) {
shouldCount++;
boolQueryBuilder.should(QueryBuilders.matchPhraseQuery("question_info", searchReqVO.getSearchText()));
boolQueryBuilder.should(QueryBuilders.matchPhraseQuery("answer_info", searchReqVO.getSearchText()));
boolQueryBuilder.should(QueryBuilders.matchPhraseQuery("keyword", searchReqVO.getSearchText()));
boolQueryBuilder.should(QueryBuilders.matchQuery("question_info", searchReqVO.getSearchText()));
boolQueryBuilder.should(QueryBuilders.matchQuery("answer_info", searchReqVO.getSearchText()));
boolQueryBuilder.should(QueryBuilders.matchQuery("keyword", searchReqVO.getSearchText()));
}
boolQueryBuilder.minimumShouldMatch(shouldCount);
countRequest.query(boolQueryBuilder);
//设置分页 from:页码，（当前页-1）*每页条数
searchSourceBuilder.from(searchReqVO.getRows() * (searchReqVO.getPage() - 1));
searchSourceBuilder.size(searchReqVO.getRows());
searchSourceBuilder.query(boolQueryBuilder);
searchSourceBuilder.highlighter(highlightBuilder);
//未输入模糊搜索内容时默认按更新时间排序、输入则默认按es相似度分值排序
if (StringUtils.isEmpty(searchReqVO.getSearchText())) {
searchSourceBuilder.sort("update_timestamp", SortOrder.DESC);
}
request.source(searchSourceBuilder);
SearchResponse searchResponse = null;
CountResponse countResponse = null;
List<EsSearchResponseVO> resultList = new ArrayList<>();
try {
countResponse = highLevelClient.count(countRequest, RequestOptions.DEFAULT);
Long totalCount = countResponse.getCount();
result.setTotal(totalCount);
searchResponse = highLevelClient.search(request, RequestOptions.DEFAULT);
SearchHit[] searchHits = searchResponse.getHits().getHits();
for (SearchHit searchHit : searchHits) {
//原理就是用es自动查找出来的hightlight字段值替换正常检索出来的值
Map<String, HighlightField> highlightFields = searchHit.getHighlightFields();
HighlightField highlightTitle = highlightFields.get("question_info");//注意是数组
Map<String, Object> sourceMap = searchHit.getSourceAsMap();
if(highlightTitle != null){
Text[] fragments = highlightTitle.getFragments();
if(fragments != null && fragments.length > 0){
//替换(fargment[0]是Text类型的)
sourceMap.replace("question_info", fragments[0].toString());
}
}
ESQuestionAnswerVersionDTO esResult = JSON.parseObject(JSON.toJSONString(sourceMap), ESQuestionAnswerVersionDTO.class);
EsSearchResponseVO vo = new EsSearchResponseVO();
vo.setQuestionInfo(esResult.getQuestion_info());
vo.setKnowledgeId(esResult.getKnowledge_id());
vo.setId(esResult.getId());
vo.setBaseInfoId(esResult.getBase_info_id());
resultList.add(vo);
}
} catch (Exception e) {
log.info("联想搜索知识失败，搜索条件: ", JSONUtil.toJsonStr(searchReqVO));
Traces.recordException(e);
}
result.setRows(resultList);
return result;
}对比做了高亮前后的结果返回：
高亮前：
高亮后：
可以看到加入高亮的代码之后返回的json串命中的关键字被套了一层<em style=‘color: red’>xxx</em>标签，也就是我们前置设置的preTags与postTags;
当然hightlight本身支持多个字段高亮，java代码实现只要设置多个
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highlightBuilder.field("aaaa”);
highlightBuilder.field(“bbb”);
…后续查询出结果之后挨个全部替换成hightlight的结果即可。
翻译成es的kibana语句如下：
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 22.00881,
"hits" : [
{
"_index" : "knowledge_question_answer",
"_type" : "_doc",
"_id" : "12494",
"_score" : 22.00881,
"_source" : {
"id" : 12494,
"question_info" : "香肠/腊肠/金字火腿常见问题",
"answer_info" : "万有全广式香肠蒸出来口感很粉， 是面粉放多了吗",
"keyword" : "香肠发酸,香肠,腊肠,金字火腿,火腿,金字金华香肠,腊肠发酸,万有全广式香肠"
},
"highlight" : {
"question_info" : [
"<em style='color: red'>香肠</em>/腊肠/金字火腿常见问题"
]
}
}
]
}
}这里只设置了一个字段高亮，只要该字段有匹配到的关键字就会被放到结果集的高亮那一栏中。结果如下：
GET /knowledge_question_answer/_doc/_search
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
//查询条件忽略
...
],
"adjust_pure_negative": true,
"minimum_should_match": "1",
"boost": 1
}
},
"highlight": {
"pre_tags": [
"<em style='color: red'>"
],
"post_tags": [
"</em>"
],
"fields": {
"question_info": {},
"answer_info": {},
"keyword": {}
}
}
}多个高亮查询结果如下：
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 22.00881,
"hits" : [
{
"_index" : "knowledge_question_answer",
"_type" : "_doc",
"_id" : "12494",
"_score" : 22.00881,
"_source" : {
"id" : 12494,
"question_info" : "香肠/腊肠/金字火腿常见问题",
"answer_info" : "万有全广式香肠蒸出来口感很粉， 是面粉放多了吗",
"keyword" : "香肠发酸,香肠,腊肠,金字火腿,火腿,金字金华香肠,腊肠发酸,万有全广式香肠"
},
"highlight" : {
"answer_info" : [
"万有全广式<em style='color: red'>香肠</em>蒸出来口感很粉， 是面粉放多了吗？"
],
"question_info" : [
"<em style='color: red'>香肠</em>/腊肠/金字火腿常见问题"
],
"keyword" : [
"<em style='color: red'>香肠</em>发酸,<em style='color: red'>香肠</em>,腊肠,金字火腿,火腿,金字金华<em style='color: red'>香肠</em>,腊肠发酸,万有全广式<em style='color: red'>香肠</em>"
]
}
}
]
}
}可以看到，多个field只要出现检索词“香肠”的地方 都被套上了前置后置的标签，展示在前端页面也就又了高亮显示的效果。