将ngrams与elasticsearch一起使用时带回所有相关结果 [英] Bring back all relevant results when using ngrams with elasticsearch
问题描述
我用ngram索引了我的elasticsearch索引,从而可以进行模糊匹配和快速前缀搜索.我注意到,如果我在名称字段中搜索包含"Bob"的文档,则仅结果名称= Bob返回.我希望响应包含名称为Bob的文档,但还要包含名称为Bobbi,Bobbette等的 文档.Bob的结果应该有一个相对较高的分数.其他不完全匹配的结果仍应出现在结果集中,但得分较低.如何使用ngrams实现此目的?
I indexed my elasticsearch index with ngrams to make it possible to do fuzzy matching and prefix searches quickly. I notice that if I search for documents containing "Bob" in the name field, only results name = Bob return. I would like the response to include documents with name=Bob, but also documents with name = Bobbi, Bobbette, etcetera. The Bob results should have a relatively high score. The other results that don't match exactly, should still appear in the results set, but with lower scores. How can I achieve this with ngrams?
我正在使用一个非常小的简单索引进行测试.索引包含两个文档.
I am using a very small simple index to test. The index contains two documents.
{
"_index": "contacts_4",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"full_name": "Bob Smith"
}
},
{
"_index": "contacts_4",
"_type": "_doc",
"_id": "2",
"_score": 1.0,
"_source": {
"full_name": "Bobby Smith"
}
}
推荐答案
这是一个可行的示例(使用n-gram标记器):
Here is a working example (using n-gram tokenizer):
映射
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"filter": [
"lowercase"
],
"type": "custom",
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"token_chars": [
"letter",
"digit"
],
"min_gram": "3",
"type": "ngram",
"max_gram": "4"
}
}
}
},
"mappings": {
"properties": {
"full_name": {
"type": "text",
"analyzer": "my_analyzer",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
索引文档
POST my_index/_doc/1
{
"full_name":"Bob Smith"
}
POST my_index/_doc/2
{
"full_name":"Bobby Smith"
}
POST my_index/_doc/3
{
"full_name":"Bobbette Smith"
}
搜索查询
GET my_index/_search
{
"query": {
"match": {
"full_name": "Bob"
}
}
}
结果
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.1626403,
"_source" : {
"full_name" : "Bob Smith"
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 0.13703513,
"_source" : {
"full_name" : "Bobby Smith"
}
},
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "3",
"_score" : 0.11085624,
"_source" : {
"full_name" : "Bobbette Smith"
}
}
]
希望这会有所帮助
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