94cad286bc
In a few previous PR's we restructured the ES|QL docs to make it possible to generate them dynamically. This PR just moves a few files around to make the query languages docs easier to work with, and a little more organized like the ES|QL docs. A bit part of this was setting up redirects to the new locations, so other repo's could correctly link to the elasticsearch docs.
2.9 KiB
| navigation_title | mapped_pages | |
|---|---|---|
| Semantic |
|
Semantic query [query-dsl-semantic-query]
::::{warning} This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features. ::::
The semantic query type enables you to perform semantic search on data stored in a semantic_text field.
Example request [semantic-query-example]
GET my-index-000001/_search
{
"query": {
"semantic": {
"field": "inference_field",
"query": "Best surfing places"
}
}
}
Top-level parameters for semantic [semantic-query-params]
field- (Required, string) The
semantic_textfield to perform the query on. query- (Required, string) The query text to be searched for on the field.
Refer to this tutorial to learn more about semantic search using semantic_text and semantic query.
Hybrid search with the semantic query [hybrid-search-semantic]
The semantic query can be used as a part of a hybrid search where the semantic query is combined with lexical queries. For example, the query below finds documents with the title field matching "mountain lake", and combines them with results from a semantic search on the field title_semantic, that is a semantic_text field. The combined documents are then scored, and the top 3 top scored documents are returned.
POST my-index/_search
{
"size" : 3,
"query": {
"bool": {
"should": [
{
"match": {
"title": {
"query": "mountain lake",
"boost": 1
}
}
},
{
"semantic": {
"field": "title_semantic",
"query": "mountain lake",
"boost": 2
}
}
]
}
}
}
You can also use semantic_text as part of Reciprocal Rank Fusion to make ranking relevant results easier:
GET my-index/_search
{
"retriever": {
"rrf": {
"retrievers": [
{
"standard": {
"query": {
"term": {
"text": "shoes"
}
}
}
},
{
"standard": {
"query": {
"semantic": {
"field": "semantic_field",
"query": "shoes"
}
}
}
}
],
"rank_window_size": 50,
"rank_constant": 20
}
}
}