我正在使用以下内容进行搜索。它工作正常。但是当找到完整的单词匹配时它会返回结果。但我想要部分查询的结果(至少 3 个字符匹配不完整的单词)。另一个检查应该是，我有一个字段campus在我的文档中。其中具有类似 campus: "Bradford" 的值, campus:"Oxford" , campus:"Harvard"等等。我希望我的查询应该返回其 campus 的文档。应该是 Bradford or Oxford和 Nel将在整个文档的其余部分提供。
RestHighLevelClient client;
QueryBuilder matchQueryBuilder = QueryBuilders.queryStringQuery("Nel");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(matchQueryBuilder);
SearchRequest searchRequest = new SearchRequest("index_name");
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
where campus='Bradford' OR campus='Oxford' .在文件中，我有“纳尔逊曼德拉二世”
目前，如果我写
Nelson，它正在工作作为查询，但我需要它来处理查询 Nel .
最佳答案
基本上有两种可能的方法来实现您正在寻找的用例。
解决方案 1:使用通配符查询
假设你有两个字段
name类型 text campus类型 text 下面是你的java代码的样子:
private static void wildcardQuery(RestHighLevelClient client, SearchSourceBuilder sourceBuilder)
throws IOException {
System.out.println("-----------------------------------------------------");
System.out.println("Wildcard Query");
MatchQueryBuilder campusClause_1 = QueryBuilders.matchQuery("campus", "oxford");
MatchQueryBuilder campusClause_2 = QueryBuilders.matchQuery("campus", "bradford");
//Using wildcard query
WildcardQueryBuilder nameClause = QueryBuilders.wildcardQuery("name", "nel*");
//Main Query
BoolQueryBuilder query = QueryBuilders.boolQuery()
.must(nameClause)
.should(campusClause_1)
.should(campusClause_2)
.minimumShouldMatch(1);
sourceBuilder.query(query);
SearchRequest searchRequest = new SearchRequest();
//specify your index name in the below parameter
searchRequest.indices("my_wildcard_index");
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(searchResponse.getHits().getTotalHits());
System.out.println("-----------------------------------------------------");
}
keyword类型并且您需要完全匹配区分大小写，您需要以下代码:TermQueryBuilder campusClause_2 = QueryBuilders.termQuery("campus", "Bradford");
为此，您需要使用 Edge Ngram标记器。
以下是您的映射方式:
映射:
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"filter": "lowercase",
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "edge_ngram",
"min_gram": 2,
"max_gram": 10,
"token_chars": [
"letter",
"digit"
]
}
}
}
},
"mappings": {
"properties": {
"name":{
"type": "text",
"analyzer": "my_analyzer"
},
"campus": {
"type": "text"
}
}
}
}
PUT my_index/_doc/1
{
"name": "Nelson Mandela",
"campus": "Bradford"
}
PUT my_index/_doc/2
{
"name": "Nel Chaz",
"campus": "Oxford"
}
POST my_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "nel"
}
}
],
"should": [
{
"match": {
"campus": "bradford"
}
},
{
"match": {
"campus": "oxford"
}
}
],
"minimum_should_match": 1
}
}
}
private static void boolMatchQuery(RestHighLevelClient client, SearchSourceBuilder sourceBuilder)
throws IOException {
System.out.println("-----------------------------------------------------");
System.out.println("Bool Query");
MatchQueryBuilder campusClause_1 = QueryBuilders.matchQuery("campus", "oxford");
MatchQueryBuilder campusClause_2 = QueryBuilders.matchQuery("campus", "bradford");
//Plain old match query would suffice here
MatchQueryBuilder nameClause = QueryBuilders.matchQuery("name", "nel");
BoolQueryBuilder query = QueryBuilders.boolQuery()
.must(nameClause)
.should(campusClause_1)
.should(campusClause_2)
.minimumShouldMatch(1);
sourceBuilder.query(query);
SearchRequest searchRequest = new SearchRequest();
searchRequest.indices("my_index");
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(searchResponse.getHits().getTotalHits());
}
在控制台中，您应该能够看到文档的总点击量。
同样，您也可以使用其他查询类型，例如
Term query在上述解决方案中，如果您正在寻找 keyword 的完全匹配项场等更新答案:
个人不推荐
Solution 1因为单个字段本身会浪费大量的计算能力，更不用说多个字段了。为了进行多字段子字符串匹配，最好的方法是利用名为
copy-to 的概念。然后对该字段使用 Edge N-Gram 分词器。那么这个 Edge N-Gram 分词器到底有什么作用呢？简单来说，基于
min-gram和 max-gram它只会分解您的 token ，例如齐柏林飞艇进
Zep, Zepp, Zeppe, Zeppel, Zeppeli, Zeppelin从而将这些值插入到该字段的倒排索引中。如果你只是执行一个非常简单的 match查询，它将返回该文档，因为您的倒排索引将具有该子字符串。关于 copy_to field :
The
copy_toparameter allows you to copy the values of multiple fields into a group field, which can then be queried as a single field.
使用 copy_to 字段，我们有以下两个字段的映射
campus和 name .映射:
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"filter": "lowercase",
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "edge_ngram",
"min_gram": 3,
"max_gram": 10,
"token_chars": [
"letter",
"digit"
]
}
}
}
},
"mappings": {
"properties": {
"name":{
"type": "text",
"copy_to": "search_string" <---- Note this
},
"campus": {
"type": "text",
"copy_to": "search_string" <---- Note this
},
"search_string": {
"type": "text",
"analyzer": "my_analyzer" <---- Note this
}
}
}
}
search_string .请注意，这会消耗磁盘空间，因此您可能需要退后一步并确保您不将此分析器用于所有字段，但这同样取决于您拥有的用例。示例文档:
POST my_index/_doc/1
{
"campus": "Cambridge University",
"name": "Ramanujan"
}
POST my_index/_search
{
"query": {
"match": {
"search_string": "ram"
}
}
}
private static void boolMatchQuery(RestHighLevelClient client, SearchSourceBuilder sourceBuilder)
throws IOException {
System.out.println("-----------------------------------------------------");
System.out.println("Bool Query");
MatchQueryBuilder searchClause = QueryBuilders.matchQuery("search_string", "ram");
//Feel free to add multiple clauses
BoolQueryBuilder query = QueryBuilders.boolQuery()
.must(searchClause);
sourceBuilder.query(query);
SearchRequest searchRequest = new SearchRequest();
searchRequest.indices("my_index");
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
System.out.println(searchResponse.getHits().getTotalHits());
}
关于java - 使用 Elasticsearch 7 java api 使用 Where 语句进行部分查询，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/62573908/