elasticSearch Java Spring Data Api
1.
BoolQueryBuilder qb=QueryBuilders. boolQuery();qb.should(QueryBuilders.matchQuery("keyWord","经济"));
SearchQuery searchQuery = new NativeSearchQueryBuilder()
.withFields("userName","keyWord","userId")
.withHighlightFields(new HighlightBuilder.Field("keyWord").fragmentSize(15))
.build();
AggregatedPage<SearchHistory> sampleEntities = elasticsearchTemplate.queryForPage(searchQuery, SearchHistory.class, new SearchResultMapper() {
@Override
public <T> AggregatedPage<T> mapResults(SearchResponse response, Class<T> clazz, Pageable pageable) {
List<SearchHistory> chunk = new ArrayList<SearchHistory>();
SearchHits hits = response.getHits();
for (SearchHit searchHit : response.getHits()) {
if (response.getHits().getHits().length <= 0) {
return null;
}
SearchHistory user = new SearchHistory();
user.setUserId((Integer)searchHit.getFields().get("userId").getValue());//这么获取
Map<String, HighlightField> highlightFields = searchHit.getHighlightFields();//高亮字段为空
chunk.add(user);
}
if (chunk.size() > 0) {
return new AggregatedPageImpl<T>((List<T>) chunk);
}
return null;
}
});
return sampleEntities;
.withQuery(termQuery("keyWord", "安徽")) //单个可以使用 .withQuery(termQuery("userName", "小经济")) //两个一块写后面会覆盖前面的也就是以“小经济”为高亮
.withFields("userName","keyWord","userId")
.withHighlightFields(new HighlightBuilder.Field("keyWord").fragmentSize(15),new HighlightBuilder.Field("userName").fragmentSize(15))//.preTags("<am>").postTags("</am>").fragmentSize(15)) 1.withQuery(QueryBuilders.queryStringQuery("安徽")) //这样组合可以查出来，但是没有高亮
.withFields("userName","keyWord","userId") //去掉这行，在source中，没有高亮
.withHighlightFields(new HighlightBuilder.Field("keyWord").fragmentSize(15),new HighlightBuilder.Field("userName").fragmentSize(15))//.preTags("<am>").postTags("</am>").fragmentSize(15)) 1.withFilter(boolQuery().should(termQuery("keyWord", "经济")).should(termQuery("keyWord", "安徽"))) //这样组合可以查出来，但是没有高亮
String[] includes = new String[]{"userName","keyWord","userId"};.withHighlightFields(new HighlightBuilder.Field("keyWord").fragmentSize(15),new HighlightBuilder.Field("userName").fragmentSize(15)).withQuery(boolQuery().should(termQuery("keyWord", "安徽")).should(termQuery("userName","小经济")))
.withSourceFilter(new FetchSourceFilter(includes,new String[]{})) //这个是可以
结果 ： {keyWord='<em>安徽</em>商报报道，<em>安徽</em>宣城市泾县一名', userId=1005, userName='<em>小经济</em>'}
String keyWord = searchHit.getHighlightFields().get("keyWord").fragments()[0].toString();
String userName = searchHit.getHighlightFields().get("userName").fragments()[0].toString();
user.setUserId((Integer) searchHit.getSource().get("userId"));
2. 测试ik
/*** 测试ik
* @throws IOException
*/
public void test() throws IOException {
AnalyzeRequestBuilder ikRequest = new AnalyzeRequestBuilder(elasticsearchTemplate.getClient(),
AnalyzeAction.INSTANCE,"test","一个大的安全帽");
ikRequest.setTokenizer("ik");
List<AnalyzeResponse.AnalyzeToken> ikTokenList = ikRequest.execute().actionGet().getTokens();
// 循环赋值
List<String> searchTermList = new ArrayList<>();
ikTokenList.forEach(ikToken -> { searchTermList.add(ikToken.getTerm()); });
System.out.println(JSON.json(searchTermList));
}
3.
termQuery 和 matchQuery 和 multiMatchQuery 和 matchPhraseQuery
4. store属性
5. 将时间加入权重中
(1)最终找到的方案
Map<String, Object> params = new HashMap<>();params.put("pubTimeStamp", 1521632807000L);
String inlineScript = "return (1/(pubTimeStamp-doc['pubTimeStamp'].value.toDouble()+1))/2"; //时间加入权重的公式
Script script = new Script(inlineScript, ScriptService.ScriptType.INLINE, "groovy", params); //设置脚本
QueryBuilder queryBuilder = boolQuery().must(matchQuery("title","中国"));//普通的查询
ScoreFunctionBuilder scoreFunctionBuilder = ScoreFunctionBuilders.scriptFunction(script);//将脚本加入函数中
FunctionScoreQueryBuilder query = QueryBuilders.functionScoreQuery(queryBuilder,scoreFunctionBuilder);//加入普通查询和脚本
SearchQuery searchQuery = new NativeSearchQueryBuilder()
//搜索的type（相当于table）
.withTypes(types)
//高亮字段定义
.withHighlightFields(new HighlightBuilder.Field("title").preTags("<font color=\"#ff55ae\">").postTags("</font>"))
//查询条件
.withQuery(query) //加入查询条件（包含普通和脚本）
//返回字段includes 和不包含的字段 excludes
.withSourceFilter(new FetchSourceFilter(queryFields,new String[]{})) //这个是可以
//分页
.withPageable(pageable)
.build();
上面函数对应的restful
{ "function_score" : {
"query" : {
"bool" : {
"must" : {
"match" : {
"title" : {
"query" : "中国",
"type" : "boolean"
}
}
}
}
},
"functions" : [ {
"script_score" : {
"script" : {
"inline" : "return (1/(pubTimeStamp-doc['pubTimeStamp'].value.toDouble()+1))/2",
"lang" : "groovy",
"params" : {
"pubTimeStamp" : 1521632807000
}
}
}
} ]
}
}
正确的应该是这种样式的
{ "query": {
"function_score": {
"query": {
"match": {
"title": "天安门"
}
},
"script_score": {
"script": "return (1/(pubTimeStamp-doc['pubTimeStamp'].value.toDouble()+1))/2",
"lang": "groovy",
"params": {
"pubTimeStamp": 1521632807000
}
}
}
}
}
(2)走过的错路
Map<String, Object> params = new HashMap<>();params.put("pubTimeStamp", 1521632807000L);
String inlineScript = "return (1/(pubTimeStamp-doc['pubTimeStamp'].value.toDouble()+1))/2";
Script script = new Script(inlineScript, ScriptService.ScriptType.INLINE, "groovy", params);
QueryBuilder queryBuilder = boolQuery().must(matchQuery("title","中国"));
ScoreFunctionBuilder scoreFunctionBuilder = ScoreFunctionBuilders.scriptFunction(script);
SearchQuery searchQuery = new NativeSearchQueryBuilder()
//搜索的type（相当于table）
.withTypes(types)
//高亮字段定义
.withHighlightFields(new HighlightBuilder.Field("title").preTags("<font color=\"#ff55ae\">").postTags("</font>"))
//查询条件
.withQuery(functionScoreQuery().add(queryBuilder,scoreFunctionBuilder))//放入普通的查询和脚本查询
//返回字段includes 和不包含的字段 excludes
.withSourceFilter(new FetchSourceFilter(queryFields,new String[]{})) //这个是可以
//分页
.withPageable(pageable)
.build();
这样出来的restful
{ "function_score" : {
"functions" : [ { //从这里可以看出是不正确的，function不应该包含filter（对照上面正确的可以看出），查出来的结果就是将不包含"中国"的数据也差出来了，还有就是分数总是为1.0
"filter" : {
"bool" : {
"must" : {
"match" : {
"title" : {
"query" : "中国",
"type" : "boolean"
}
}
}
}
},
"script_score" : {
"script" : {
"inline" : "return (1/(pubTimeStamp-doc['pubTimeStamp'].value.toDouble()+1))/2",
"lang" : "groovy",
"params" : {
"pubTimeStamp" : 1521632807000
}
}
}
} ]
}
}
6. 分数公式
（1）totalScore = _socre * doc['id'].value ====》 总分数 = 原始分数 * 二次评分
"script_score": { "script": "doc['id'].value",
"lang": "groovy"
}
（2）跟上面一样
"script_score": { "script": "_score+doc['id'].value",
"lang": "groovy"
}
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