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Ranking evaluation
Introduced 1.0
The rank eval endpoint allows you to evaluate the quality of ranked search results.
Path and HTTP methods
GET <index_name>/_rank_eval
POST <index_name>/_rank_eval
Query parameters
Query parameters are optional.
Parameter | Data type | Description |
---|---|---|
ignore_unavailable | Boolean | Defaults to false . When set to false the response body will return an error if an index is closed or missing. |
allow_no_indices | Boolean | Defaults to true . When set to false the response body will return an error if a wildcard expression points to indexes that are closed or missing. |
expand_wildcards | String | Expand wildcard expressions for indexes that are open , closed , hidden , none , or all . |
search_type | String | Set search type to either query_then_fetch or dfs_query_then_fetch . |
Request fields
The request body must contain at least one parameter.
Field Type | Description |
---|---|
id | Document or template ID. |
requests | Set multiple search requests within the request field section. |
ratings | Document relevance score. |
k | The number of documents returned per query. Default is set to 10. |
relevant_rating_threshold | The threshold at which documents are considered relevant. Default is set to 1. |
normalize | Discounted cumulative gain will be calculated when set to true . |
maximum_relevance | Sets the maximum relevance score when using the expected reciprocal rank metric. |
ignore_unlabeled | Defaults to false . Unlabeled documents are ignored when set to true . |
template_id | Template ID. |
params | Parameters used in the template. |
Example request
GET shakespeare/_rank_eval
{
"requests": [
{
"id": "books_query",
"request": {
"query": { "match": { "text": "thou" } }
},
"ratings": [
{ "_index": "shakespeare", "_id": "80", "rating": 0 },
{ "_index": "shakespeare", "_id": "115", "rating": 1 },
{ "_index": "shakespeare", "_id": "117", "rating": 2 }
]
},
{
"id": "words_query",
"request": {
"query": { "match": { "text": "art" } }
},
"ratings": [
{ "_index": "shakespeare", "_id": "115", "rating": 2 }
]
}
]
}
Example response
{
"rank_eval": {
"metric_score": 0.7,
"details": {
"query_1": {
"metric_score": 0.9,
"unrated_docs": [
{
"_index": "shakespeare",
"_id": "1234567"
}, ...
],
"hits": [
{
"hit": {
"_index": "shakespeare",
"_type": "page",
"_id": "1234567",
"_score": 5.123456789
},
"rating": 1
}, ...
],
"metric_details": {
"precision": {
"relevant_docs_retrieved": 3,
"docs_retrieved": 6
}
}
},
"query_2": { [... ] }
},
"failures": { [... ] }
}
}