How to sort result set in order of matching words - elasticsearch

Question

How to sort result set in order of matching words?
I have a couple words "heinz meyer"
my query returns:
Heinz A. Meyer
Heinz Meyer GmbH Heizung-Sanitär
Heinz Meyer
Karl-Heinz Meyer GmbH
but i need, order by positions matching like next :
Heinz Meyer
Heinz Meyer GmbH Heizung-Sanitär
Heinz A. Meyer
Karl-Heinz Meyer GmbH
my query is:
{
"query": {
"bool": {
"must": [{
"wildcard": {
"name": "heinz*"
}
}, {
"wildcard": {
"name": "meyer*"
}
}],
"must_not": [],
"should": [],
"filter": {
"bool": {
"must": [{
"range": {
"latestRevenueStatistics.revenue": {
"gte": "0",
"lte": "40000000"
}
}
}, {
"range": {
"latestRevenueStatistics.number_of_employees": {
"gte": "0",
"lte": "300"
}
}
}, {
"term": {
"addresses.postal_code_length": 5
}
}]
}
}
}
},
"from": 0,
"size": 10
}
FINAL SOLUTION:
{
"query": {
"bool": {
"must": [{
"wildcard": {
"name": "heinz*"
}
}, {
"wildcard": {
"name": "mayer*"
}
}, {
"span_near": {
"clauses": [{
"span_term": {
"name": {
"value": "heinz"
}
}
}, {
"span_term": {
"name": {
"value": "mayer"
}
}
}],
"slop": 4,
"in_order": true
}
}],
"must_not": [],
"should": [{
"span_first": {
"match": {
"span_term": {
"name": "heinz"
}
},
"end": 1
}
}, {
"span_first": {
"match": {
"span_term": {
"name": "mayer"
}
},
"end": 2
}
}],
"filter": {
"bool": {
"must": [{
"range": {
"latestRevenueStatistics.revenue": {
"gte": "0",
"lte": "40000000"
}
}
}, {
"range": {
"latestRevenueStatistics.number_of_employees": {
"gte": "0",
"lte": "300"
}
}
}, {
"term": {
"addresses.postal_code_length": 5
}
}]
}
}
}
},
"from": 0,
"size": 10
}

Answer 1

You can implement the match query using combination of Span First, Span Term and Span Near Query
For the sake of simplicity, I've created a sample index with only one field labeled name of type text along with the below documents.
Documents:
POST sortindex/_doc/1
{
"name": "Heinz A. Meyer"
}
POST sortindex/_doc/2
{
"name": "Heinz Meyer GmbH Heizung-Sanitär"
}
POST sortindex/_doc/3
{
"name": "Heinz Meyer"
}
POST sortindex/_doc/4
{
"name": "Karl-Heinz Meyer GmbH"
}
Query:
POST sortindex/_search
{
"query": {
"bool": {
"must": [
{
"span_near": { <---- Span Near Query
"clauses": [
{
"span_term": { <---- Span Term Query
"name": {
"value": "heinz"
}
}
},
{
"span_term": {
"name": {
"value": "meyer"
}
}
}
],
"slop": 4, <---- Retrieve all docs having both heinz and meyer with distance of <= 4 words
"in_order": true <---- Heinz must always come before Meyer
}
}
],
"should": [
{
"span_first": { <---- Span First Query
"match": {
"span_term": { <---- Span Term Query
"name": "heinz"
}
},
"end": 1 <---- Retrieve docs having heinz's postition <= 1 and > 0 i.e. the first word
}
}
]
}
}
}
Notice that Span Near is placed in must clause whereas Span First is placed in should clause. That way the documents conforming to the should clause would get higher score as compared to the ones that doesn't match.
Internally for both, we search using Span Term which is nothing but like a term query but it is specifically mean for using with Span Queries.
I'd suggest you to go through the links if you would like to understand more on Span Queries.
From the link:
Span queries are low-level positional queries which provide expert
control over the order and proximity of the specified terms. These are
typically used to implement very specific queries on legal documents
or patents.
Response:
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 0.38327998,
"hits" : [
{
"_index" : "sortindex",
"_type" : "_doc",
"_id" : "3",
"_score" : 0.38327998,
"_source" : {
"name" : "Heinz Meyer"
}
},
{
"_index" : "sortindex",
"_type" : "_doc",
"_id" : "2",
"_score" : 0.26893127,
"_source" : {
"name" : "Heinz Meyer GmbH Heizung-Sanitär"
}
},
{
"_index" : "sortindex",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.25940484,
"_source" : {
"name" : "Heinz A. Meyer"
}
},
{
"_index" : "sortindex",
"_type" : "_doc",
"_id" : "4",
"_score" : 0.19908611,
"_source" : {
"name" : "Karl-Heinz Meyer GmbH"
}
}
]
}
}
You can go ahead and add the above query to the one you have.
Hope this helps!