我已经使用“AND”默认运算符设置了查询字符串搜索。我的查询如下:
{
"query": {
"query_string" : {
"query" : "Adam KT2 7AJ",
"default_operator" : "AND"
}
}
}
我希望这将提供与以下相同的结果...但是事实并非如此。
{
"query": {
"query_string" : {
"query" : "Adam AND KT2 AND 7AJ",
"default_operator" : "OR"
}
}
}
虽然我看到default_operator对我的搜索结果有所影响，但它并没有达到我想要的效果。
例如:
QUERY1:
Adam AND KT2 AND 7AJ，默认运算符(operator):or QUERY2:
Adam KT2 7AJ，默认运算符(operator):and and，因为default_operator与查询中的AND产生不同的结果)QUERY3:
KT2 7AJ，默认运算符(operator):and QUERY4:
KT2 7AJ，默认运算符(operator):or 编辑
这是我的映射。您会注意到，帐单邮寄地址中有一个邮政编码字段，但shipping_address和客户都附加了名称字段。
当我以
Adam AND KT2 7AJ的形式运行查询时，我们得到的结果是customer.name:Adam，AND，billing_address.post_code:KT2 7AJ，这正是我所期望的。如果删除AND，我们将得到0个结果。
{
"t1_orders_1584882055": {
"mappings": {
"properties": {
"__class_name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"billing_address": {
"properties": {
"address1": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"address2": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"address3": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"company": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"country_code": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"created_at": {
"type": "date",
"format": "date_time"
},
"customer_id": {
"type": "long"
},
"email": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"id": {
"type": "keyword"
},
"name": {
"type": "text",
"analyzer": "edge_ngram_analyzer"
},
"phone": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"post_code": {
"type": "text",
"fields": {
"text": {
"type": "text"
}
},
"analyzer": "no_space_analyzer"
},
"redacted": {
"type": "boolean"
},
"region": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"town": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"updated_at": {
"type": "date",
"format": "date_time"
}
}
},
"billing_address_id": {
"type": "long"
},
"channel": {
"properties": {
"created_at": {
"type": "date"
},
"id": {
"type": "long"
},
"identifier": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"updated_at": {
"type": "date"
}
}
},
"channel_id": {
"type": "long"
},
"created_at": {
"type": "date",
"format": "date_time"
},
"customer": {
"properties": {
"created_at": {
"type": "date",
"format": "date_time"
},
"email": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"id": {
"type": "keyword"
},
"name": {
"type": "text",
"analyzer": "edge_ngram_analyzer"
},
"redacted": {
"type": "boolean"
},
"updated_at": {
"type": "date",
"format": "date_time"
}
}
},
"customer_id": {
"type": "long"
},
"id": {
"type": "keyword"
},
"name": {
"type": "text",
"analyzer": "edge_ngram_analyzer"
},
"order_id": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"order_items": {
"properties": {
"created_at": {
"type": "date"
},
"id": {
"type": "long"
},
"order_id": {
"type": "long"
},
"qty": {
"type": "long"
},
"sku": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"updated_at": {
"type": "date"
}
}
},
"received_at": {
"type": "date",
"format": "date_time"
},
"reference_number": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"ship_by": {
"type": "date"
},
"shipping_address": {
"properties": {
"address1": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"address2": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"address3": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"company": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"country_code": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"created_at": {
"type": "date",
"format": "date_time"
},
"customer_id": {
"type": "long"
},
"email": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"id": {
"type": "keyword"
},
"name": {
"type": "text",
"analyzer": "edge_ngram_analyzer"
},
"phone": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"post_code": {
"type": "text",
"fields": {
"text": {
"type": "text"
}
},
"analyzer": "no_space_analyzer"
},
"redacted": {
"type": "boolean"
},
"region": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"town": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"updated_at": {
"type": "date",
"format": "date_time"
}
}
},
"shipping_address_id": {
"type": "long"
},
"status": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"updated_at": {
"type": "date",
"format": "date_time"
}
}
}
}
}
范例文件:
{
"_source": {
"id": 6,
"channel_id": 1,
"customer_id": 1,
"shipping_address_id": 11,
"billing_address_id": 12,
"order_id": "1234",
"reference_number": "1234",
"status": "open",
"received_at": "2020-02-24T18:03:21.000000Z",
"ship_by": "2020-02-24T18:03:21.000000Z",
"completed_at": null,
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z",
"channel": {
"id": 1,
"name": "Amazon",
"identifier": "The",
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z"
},
"customer": {
"id": 1,
"name": "Nam Test",
"email": "[email protected]",
"redacted": false,
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z"
},
"shipping_address": {
"id": 11,
"customer_id": 1,
"name": "Nam Test",
"email": "[email protected]",
"company": "",
"address1": "44",
"address2": "AD CLOSE",
"address3": "",
"town": "KINGSTON UPON THAMES",
"region": "",
"post_code": "KT2 7AJ",
"country_code": null,
"phone": "213223123",
"redacted": false,
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z"
},
"billing_address": {
"id": 12,
"customer_id": 1,
"name": "Nam Test",
"email": "[email protected]",
"company": "",
"address1": "44",
"address2": "AD CLOSE",
"address3": "",
"town": "KINGSTON UPON THAMES",
"region": "",
"post_code": "KT2 7AJ",
"country_code": null,
"phone": "213223123",
"redacted": false,
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z"
},
"order_items": [
{
"id": 6,
"order_id": 6,
"sku": "10-2-sk-ue",
"qty": 1,
"created_at": "2020-03-18T16:17:28.000000Z",
"updated_at": "2020-03-18T16:17:28.000000Z"
}
]
}
}
最佳答案
从 Elasticsearch 版本6.x开始，不再按空格分割。
说明:
取两个字段Name和PostalCode
1. Adam AND KT2 AND 7AJ，default_operator:或
查询翻译成:-
(名称:Adam或邮政编码:Adam)或(名称:KT2或邮政编码:KT2)或(名称:7AJ或邮政编码:7AJ)
文本在运算符(AND，OR)上拆分，每个拆分都传递到相应的字段
因此它将返回所有名称为Adam且邮政编码包含7AJ或KT2的文档( token 匹配)
2. Adam AND KT2 AND 7AJ，default_operator:和
查询翻译成:-
(名称:Adam或邮递区号:Adam)AND(名称:KT2或邮递区号:KT2)AND(名称:7AJ或邮递区号:7AJ)
3. Adam KT2 7AJ，default_operator:和
查询翻译成:-
(名称:(Adam AND KT2 AND 7AJ)或邮政编码:(Adam AND KT2 AND 7AJ))
文本不会在空格上分割(这是在版本6之前完成的)，并且被视为文本块。因此，仅返回在任何字段中具有所有三个标记的文档
4. KT2 7AJ，default_operator:和
与点2文档相同，该文档在任何字段中都具有两个标记。
5. KT2 7AJ，default_operator:或
返回与第2点文档相同的字段中包含任何token(OR)
github上的 Elasticsearch 团队对此link进行了类似的澄清
如果您想继续使用现有结构，则可以使用方括号将类似的单词合并在一起。下面的查询将文本分为两个 token Adam和单个块KT2 7AJ
这将转化为
(名称:Adam或邮政编码:Adam)AND(名称:(KT2 AND 7AJ)或邮政编码:(KT2 AND 7AJ)
{
"query": {
"query_string" : {
"query" : "Adam (KT2 7AJ)",
"default_operator" : "AND"
}
}
}
关于Elasticsearch default_operator "AND"无法正常工作，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/60794719/