If you are using Elasticsearch default index mapping, then you can use a [term query][1] on `text.keyword` field.
The term query is used to return documents that match exactly with the search term.
You can include the `term` query in the bool should clause, which will increase the score of exact matching documents, as compared to the other documents' score.
```
{
"query": {
"bool": {
"should": [
{
"match": {
"text": "tonight"
}
},
{
"term": {
"text.keyword": "tonight"
}
}
]
}
}
}
```
Search Results will be
```
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 5,
"relation": "eq"
},
"max_score": 1.5025805,
"hits": [
{
"_index": "stof",
"_id": "1",
"_score": 1.5025805,
"_source": {
"id": 1,
"text": "tonight"
}
},
{
"_index": "stof",
"_id": "3",
"_score": 0.13236837,
"_source": {
"id": 3,
"text": "tonight tonight tonight"
}
},
{
"_index": "stof",
"_id": "2",
"_score": 0.12794474,
"_source": {
"id": 2,
"text": "tonight tonight"
}
},
{
"_index": "stof",
"_id": "5",
"_score": 0.08185939,
"_source": {
"id": 5,
"text": "tonight and you"
}
},
{
"_index": "stof",
"_id": "4",
"_score": 0.07130444,
"_source": {
"id": 4,
"text": "tonight and something else"
}
}
]
}
}
```
[1]: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
There is no direct way to do it in elastic search.
The closest thing that can be done is to use [multi-term vectors](https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-multi-termvectors.html)
Query
````
POST /index51/_mtermvectors
{
"ids" : ["1", "2"], --> Ids of all documents (_id)
"parameters": {
"fields": [
"text"
],
"term_statistics": true
}
}
````
It will return list of all documents with statistics for each word in the field
Result:
````
{
"docs" : [
{
"_index" : "index51",
"_type" : "_doc",
"_id" : "1",
"_version" : 2,
"found" : true,
"took" : 3,
"term_vectors" : {
"text" : {
"field_statistics" : {
"sum_doc_freq" : 7,
"doc_count" : 3,
"sum_ttf" : 7
},
"terms" : {
"another" : {
"doc_freq" : 2,
"ttf" : 2,
"term_freq" : 1,
"tokens" : [
{
"position" : 0,
"start_offset" : 0,
"end_offset" : 7
}
]
},
"test" : {
"doc_freq" : 3,
"ttf" : 3,
"term_freq" : 1,
"tokens" : [
{
"position" : 2,
"start_offset" : 16,
"end_offset" : 20
}
]
},
"twitter" : {
"doc_freq" : 2,
"ttf" : 2,
"term_freq" : 1,
"tokens" : [
{
"position" : 1,
"start_offset" : 8,
"end_offset" : 15
}
]
}
}
}
}
},
{
"_index" : "index51",
"_type" : "_doc",
"_id" : "2",
"_version" : 1,
"found" : true,
"took" : 2,
"term_vectors" : {
"text" : {
"field_statistics" : {
"sum_doc_freq" : 7,
"doc_count" : 3,
"sum_ttf" : 7
},
"terms" : {
"test" : {
"doc_freq" : 3,
"ttf" : 3,
"term_freq" : 1,
"tokens" : [
{
"position" : 0,
"start_offset" : 0,
"end_offset" : 4
}
]
}
}
}
}
}
]
}
````
Ids of all documents can be fetched using [scroll api](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-body.html#request-body-search-scroll)
