我的文档如下:
"hits": {
"total": 4,
"max_score": 1,
"hits": [
{
"_index": "test_db2",
"_type": "test",
"_id": "1",
"_score": 1,
"_source": {
"name": "very cool shoes",
"price": 26
}
},
{
"_index": "test_db2",
"_type": "test",
"_id": "2",
"_score": 1,
"_source": {
"name": "great shampoo",
"price": 15
}
},
{
"_index": "test_db2",
"_type": "test",
"_id": "3",
"_score": 1,
"_source": {
"name": "shirt",
"price": 25
}
}
]
}
如何在elasticsearch中创建自动完成功能,例如: 我输入了输入字" sh"之后我应该看到结果
SH OES
SH ampoo
SH IRT
.....
答案 0 :(得分:0)
看看ngrams。或者实际上,edge ngrams可能就是你所需要的。
Qbox有一些关于使用ngrams设置自动完成功能的博客文章,因此,为了进行更深入的讨论,我会向您推荐这些:
https://qbox.io/blog/an-introduction-to-ngrams-in-elasticsearch
https://qbox.io/blog/multi-field-partial-word-autocomplete-in-elasticsearch-using-ngrams
但是很快,这应该让你开始。
首先我设置索引:
PUT /test_index
{
"settings": {
"analysis": {
"analyzer": {
"autocomplete": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"standard",
"stop",
"kstem",
"edgengram_filter"
]
}
},
"filter": {
"edgengram_filter": {
"type": "edgeNGram",
"min_gram": 2,
"max_gram": 15
}
}
}
},
"mappings": {
"doc": {
"properties": {
"name": {
"type": "string",
"index_analyzer": "autocomplete",
"search_analyzer": "standard"
},
"price":{
"type": "integer"
}
}
}
}
}
然后我将你的文件编入索引:
POST /test_index/doc/_bulk
{"index":{"_id":1}}
{"name": "very cool shoes","price": 26}
{"index":{"_id":2}}
{"name": "great shampoo","price": 15}
{"index":{"_id":3}}
{"name": "shirt","price": 25}
现在,我可以通过简单的match query:
获得自动填充结果POST /test_index/_search
{
"query": {
"match": {
"name": "sh"
}
}
}
返回:
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.30685282,
"hits": [
{
"_index": "test_index",
"_type": "doc",
"_id": "3",
"_score": 0.30685282,
"_source": {
"name": "shirt",
"price": 25
}
},
{
"_index": "test_index",
"_type": "doc",
"_id": "2",
"_score": 0.19178301,
"_source": {
"name": "great shampoo",
"price": 15
}
},
{
"_index": "test_index",
"_type": "doc",
"_id": "1",
"_score": 0.15342641,
"_source": {
"name": "very cool shoes",
"price": 26
}
}
]
}
}
以下是我用来测试它的代码:
http://sense.qbox.io/gist/0886488ddfb045c69eed67b15e9734187c8b2491