Building an effective Elasticsearch query for cross_fields with fuzziness - elasticsearch

Question

I know that Elasticsearch does not support fuzziness with the cross_fields type in a multi_match query. I have a very difficult time with the Elasticsearch API and so I'm finding it challenging to build an analogous query that searches across multiple document fields with fuzzy string matching.
I have an index called papers with various fields such as Title, Author.FirstName, Author.LastName, PublicationDate, Journal etc... I want to be able to query with a string like "John Doe paper title 2015 journal name". cross_fields is the perfect multi_match type but it doesn't support fuzziness which is critical for my application.
Can anyone suggest a reasonable way to approach this? I've spent hours going through solutions on SO and the Elasticsearch forums with little success.

Answer 1

You can make use of copy_to field for this scenario. Basically you are copying all the values from different fields into one new field (my_search_field in the below details) and on this field, you would be able to perform fuzzy query via fuzziness parameter using simple match query.
Below is how a sample mapping, document and query would be:
Mapping:
PUT my_fuzzy_index
{
"mappings": {
"properties": {
"my_search_field":{ <---- Note this field
"type": "text"
},
"Title":{
"type": "text",
"copy_to": "my_search_field" <---- Note this
},
"Author":{
"type": "nested",
"properties": {
"FirstName":{
"type":"text",
"copy_to": "my_search_field" <---- Note this
},
"LastName":{
"type":"text",
"copy_to": "my_search_field" <---- Note this
}
}
},
"PublicationDate":{
"type": "date",
"copy_to": "my_search_field" <---- Note this
},
"Journal":{
"type":"text",
"copy_to": "my_search_field" <---- Note this
}
}
}
}
Sample Document:
POST my_fuzzy_index/_doc/1
{
"Title": "Fountainhead",
"Author":[
{
"FirstName": "Ayn",
"LastName": "Rand"
}
],
"PublicationDate": "2015",
"Journal": "journal"
}
Query Request:
POST my_fuzzy_index/_search
{
"query": {
"match": {
"my_search_field": { <---- Note this field
"query": "Aynnn Ranaad Fountainhead 2015 journal",
"fuzziness": 3 <---- Fuzzy parameter
}
}
}
}
Response:
{
"took" : 15,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.1027813,
"hits" : [
{
"_index" : "my_fuzzy_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.1027813,
"_source" : {
"Title" : "Fountainhead",
"Author" : [
{
"FirstName" : "Ayn",
"LastName" : "Rand"
}
],
"PublicationDate" : "2015",
"Journal" : "journal"
}
}
]
}
}
So instead of thinking of applying fuzzy query on multiple fields, you can instead go for this approach. That way your query would be simplified.
Let me know if this helps!