We want to leverage ElasticSearch to find us similar objects.
Lets say I have an Object with 4 fields: product_name, seller_name, seller_phone, platform_id.
Similar products can have different product names and seller names across different platforms (fuzzy match).
While, phone is strict and a single variation might cause yield a wrong record (strict match).
What were trying to create is a query that will:
If I would write it in pseudo code, I would write something like:
((product_name like 'some_product_name') OR (seller_name like 'some_seller_name') OR (seller_phone = 'some_phone')) AND (platform_id = 123)
To do exact match on seller_phone
i am indexing this field without ngram analyzers along with fuzzy_query for product_name
and seller_name
Mapping
PUT index111
{
"settings": {
"analysis": {
"analyzer": {
"edge_n_gram_analyzer": {
"tokenizer": "whitespace",
"filter" : ["lowercase", "ednge_gram_filter"]
}
},
"filter": {
"ednge_gram_filter" : {
"type" : "NGram",
"min_gram" : 2,
"max_gram": 10
}
}
}
},
"mappings": {
"document_type" : {
"properties": {
"product_name" : {
"type": "text",
"analyzer": "edge_n_gram_analyzer"
},
"seller_name" : {
"type": "text",
"analyzer": "edge_n_gram_analyzer"
},
"seller_phone" : {
"type": "text"
},
"platform_id" : {
"type": "text"
}
}
}
}
}
Index documents
POST index111/document_type
{
"product_name":"macbok",
"seller_name":"apple",
"seller_phone":"9988",
"platform_id":"123"
}
For following pseudo sql query
((product_name like 'some_product_name') OR (seller_name like 'some_seller_name') OR (seller_phone = 'some_phone')) AND (platform_id = 123)
Elastic Query
POST index111/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"platform_id": {
"value": "123"
}
}
},
{
"bool": {
"should": [{
"fuzzy": {
"product_name": {
"value": "macbouk",
"boost": 1.0,
"fuzziness": 2,
"prefix_length": 0,
"max_expansions": 100
}
}
},
{
"fuzzy": {
"seller_name": {
"value": "apdle",
"boost": 1.0,
"fuzziness": 2,
"prefix_length": 0,
"max_expansions": 100
}
}
},
{
"term": {
"seller_phone": {
"value": "9988"
}
}
}
]
}
}]
}
}
}
Hope this helps