问题
I am trying to convert my MYSQL query to Elasticsearch. The query includes multiple conditions on different fields. Let me explain what i am trying to achieve. My Mysql query is
Select * from data_fl where city IN 'miami,miamibeach,etc' AND phone!=0 AND (name like '%abc%' OR address like '%abc%' OR zip_code like '%abc%' OR phone Like '%abc')
how this query can be replicated in elasticsearch. My attempt is
$params = [
'index'=>'us_data_'.strtolower($state_code),
'body' => [
'query' => [
'bool'=>[
'filter'=>[
'term'=>['city_code'=>$city_name]
],
'should' => [
'query_string'=>[
'query'=>"*".$service."*",
'fields'=>['name','contact_no','zip_code','city_code'],
]
]
]
]
]
];
But this doesn't return anything. I am using Elasticsearch 7.6 and trying to replicate this query with curl on Kibana but the answer is still the same.
Looking forward for help
As requested the mapping of the index is
{
"mapping": {
"_doc": {
"properties": {
"@timestamp": {
"type": "date"
},
"@version": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"address": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"city_code": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"contact_no": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"date_added": {
"type": "date"
},
"date_updated": {
"type": "date"
},
"featured": {
"type": "long"
},
"id": {
"type": "long"
},
"location_id": {
"type": "long"
},
"main_cate": {
"type": "long"
},
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"slug": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"source": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"state_code": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"status": {
"type": "long"
},
"zip_code": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
The document which i accept is
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "us_data_al",
"_type" : "_doc",
"_id" : "8kmR1HABkLcaz3xayZOg",
"_score" : 1.0,
"_source" : {
"promotion" : null,
"image" : null,
"name" : "Port City Realty",
"city_code" : "Mobile",
"services" : null,
"promotion_exp_date" : null,
"tuesdayopen" : null,
"tuesdayclose" : null,
"wednesdayopen" : null,
"thursdayclose" : null,
"@timestamp" : "2020-03-13T15:44:45.330Z",
"date_updated" : "2020-03-06T00:00:00.000Z",
"mondayopen" : null,
"contact_no" : "2516891228",
"id" : 1941,
"fridayclose" : null,
"featured" : 0,
"main_cate" : 1,
"wednesdayclose" : null,
"sundayopen" : null,
"state_code" : "AL",
"video" : null,
"address" : "4826 Whispering Oaks Lane",
"user_id" : null,
"slug" : "2516891228-port-city-realty-mobile-al-36695",
"timezone" : null,
"source" : "USA Business",
"description" : null,
"fridayopen" : null,
"price" : null,
"saturdayopen" : null,
"saturdayclose" : null,
"date_added" : "2020-03-05T19:00:00.000Z",
"thursdayopen" : null,
"@version" : "1",
"status" : 1,
"mondayclose" : null,
"zip_code" : "36695",
"private_contact" : null,
"location_id" : 0,
"sundayclose" : null
}
}
回答1:
You are complicating the things and trying to fit MySQL concept in Elasticsearch, In this case, you need to properly define your index mapping(fields data types and their analyzer based on the search requirements) and accordingly build your queries.
I've taken your sample and didn't change your index mapping and sample document, but changed the search query to show, how with your existing data and requirement(may not work in all cases, but you gets an idea) it can bring the search.
Search query
{
"query": {
"multi_match": { --> note and read about multi_match query
"query": "36695",
"fields": [
"address",
"city_code", --> add more fields if you need to be
"zip_code",
"contact_no"
]
}
}
}
Search result brings your sample doc:
"hits": [
{
"_index": "so_mysql_dsl",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"promotion": null,
"image": null,
"name": "Port City Realty",
"city_code": "Mobile",
"services": null,
"promotion_exp_date": null,
"tuesdayopen": null,
"tuesdayclose": null,
"wednesdayopen": null,
"thursdayclose": null,
"@timestamp": "2020-03-13T15:44:45.330Z",
"date_updated": "2020-03-06T00:00:00.000Z",
"mondayopen": null,
"contact_no": "2516891228",
"id": 1941,
"fridayclose": null,
"featured": 0,
"main_cate": 1,
"wednesdayclose": null,
"sundayopen": null,
"state_code": "AL",
"video": null,
"address": "4826 Whispering Oaks Lane",
"user_id": null,
"slug": "2516891228-port-city-realty-mobile-al-36695",
"timezone": null,
"source": "USA Business",
"description": null,
"fridayopen": null,
"price": null,
"saturdayopen": null,
"saturdayclose": null,
"date_added": "2020-03-05T19:00:00.000Z",
"thursdayopen": null,
"@version": "1",
"status": 1,
"mondayclose": null,
"zip_code": "36695",
"private_contact": null,
"location_id": 0,
"sundayclose": null
}
}
]
来源：https://stackoverflow.com/questions/60771999/mysql-query-to-elasticsearch