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---------
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
Co-authored-by: Liam Thompson <leemthompo@gmail.com>
Co-authored-by: Martijn Laarman <Mpdreamz@gmail.com>
Co-authored-by: István Zoltán Szabó <szabosteve@gmail.com>
181 lines
7.2 KiB
Markdown
181 lines
7.2 KiB
Markdown
---
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navigation_title: "Distance feature"
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mapped_pages:
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- https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-distance-feature-query.html
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---
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# Distance feature query [query-dsl-distance-feature-query]
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Boosts the [relevance score](/reference/query-languages/query-filter-context.md#relevance-scores) of documents closer to a provided `origin` date or point. For example, you can use this query to give more weight to documents closer to a certain date or location.
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You can use the `distance_feature` query to find the nearest neighbors to a location. You can also use the query in a [`bool`](/reference/query-languages/query-dsl-bool-query.md) search’s `should` filter to add boosted relevance scores to the `bool` query’s scores.
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## Example request [distance-feature-query-ex-request]
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### Index setup [distance-feature-index-setup]
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To use the `distance_feature` query, your index must include a [`date`](/reference/elasticsearch/mapping-reference/date.md), [`date_nanos`](/reference/elasticsearch/mapping-reference/date_nanos.md) or [`geo_point`](/reference/elasticsearch/mapping-reference/geo-point.md) field.
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To see how you can set up an index for the `distance_feature` query, try the following example.
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1. Create an `items` index with the following field mapping:
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* `name`, a [`keyword`](/reference/elasticsearch/mapping-reference/keyword.md) field
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* `production_date`, a [`date`](/reference/elasticsearch/mapping-reference/date.md) field
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* `location`, a [`geo_point`](/reference/elasticsearch/mapping-reference/geo-point.md) field
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```console
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PUT /items
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{
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"mappings": {
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"properties": {
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"name": {
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"type": "keyword"
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},
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"production_date": {
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"type": "date"
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},
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"location": {
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"type": "geo_point"
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}
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}
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}
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}
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```
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2. Index several documents to this index.
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```console
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PUT /items/_doc/1?refresh
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{
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"name" : "chocolate",
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"production_date": "2018-02-01",
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"location": [-71.34, 41.12]
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}
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PUT /items/_doc/2?refresh
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{
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"name" : "chocolate",
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"production_date": "2018-01-01",
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"location": [-71.3, 41.15]
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}
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PUT /items/_doc/3?refresh
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{
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"name" : "chocolate",
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"production_date": "2017-12-01",
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"location": [-71.3, 41.12]
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}
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```
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### Example queries [distance-feature-query-ex-query]
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#### Boost documents based on date [distance-feature-query-date-ex]
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The following `bool` search returns documents with a `name` value of `chocolate`. The search also uses the `distance_feature` query to increase the relevance score of documents with a `production_date` value closer to `now`.
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```console
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GET /items/_search
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{
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"query": {
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"bool": {
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"must": {
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"match": {
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"name": "chocolate"
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}
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},
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"should": {
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"distance_feature": {
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"field": "production_date",
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"pivot": "7d",
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"origin": "now"
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}
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}
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}
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}
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}
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```
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#### Boost documents based on location [distance-feature-query-distance-ex]
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The following `bool` search returns documents with a `name` value of `chocolate`. The search also uses the `distance_feature` query to increase the relevance score of documents with a `location` value closer to `[-71.3, 41.15]`.
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```console
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GET /items/_search
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{
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"query": {
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"bool": {
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"must": {
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"match": {
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"name": "chocolate"
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}
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},
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"should": {
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"distance_feature": {
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"field": "location",
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"pivot": "1000m",
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"origin": [-71.3, 41.15]
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}
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}
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}
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}
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}
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```
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## Top-level parameters for `distance_feature` [distance-feature-top-level-params]
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`field`
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: (Required, string) Name of the field used to calculate distances. This field must meet the following criteria:
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* Be a [`date`](/reference/elasticsearch/mapping-reference/date.md), [`date_nanos`](/reference/elasticsearch/mapping-reference/date_nanos.md) or [`geo_point`](/reference/elasticsearch/mapping-reference/geo-point.md) field
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* Have an [`index`](/reference/elasticsearch/mapping-reference/mapping-index.md) mapping parameter value of `true`, which is the default
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* Have an [`doc_values`](/reference/elasticsearch/mapping-reference/doc-values.md) mapping parameter value of `true`, which is the default
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`origin`
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: (Required, string) Date or point of origin used to calculate distances.
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If the `field` value is a [`date`](/reference/elasticsearch/mapping-reference/date.md) or [`date_nanos`](/reference/elasticsearch/mapping-reference/date_nanos.md) field, the `origin` value must be a [date](/reference/data-analysis/aggregations/search-aggregations-bucket-daterange-aggregation.md#date-format-pattern). [Date Math](/reference/elasticsearch/rest-apis/common-options.md#date-math), such as `now-1h`, is supported.
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If the `field` value is a [`geo_point`](/reference/elasticsearch/mapping-reference/geo-point.md) field, the `origin` value must be a geopoint.
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`pivot`
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: (Required, [time unit](/reference/elasticsearch/rest-apis/api-conventions.md#time-units) or [distance unit](/reference/elasticsearch/rest-apis/api-conventions.md#distance-units)) Distance from the `origin` at which relevance scores receive half of the `boost` value.
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If the `field` value is a [`date`](/reference/elasticsearch/mapping-reference/date.md) or [`date_nanos`](/reference/elasticsearch/mapping-reference/date_nanos.md) field, the `pivot` value must be a [time unit](/reference/elasticsearch/rest-apis/api-conventions.md#time-units), such as `1h` or `10d`.
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If the `field` value is a [`geo_point`](/reference/elasticsearch/mapping-reference/geo-point.md) field, the `pivot` value must be a [distance unit](/reference/elasticsearch/rest-apis/api-conventions.md#distance-units), such as `1km` or `12m`.
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`boost`
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: (Optional, float) Floating point number used to multiply the [relevance score](/reference/query-languages/query-filter-context.md#relevance-scores) of matching documents. This value cannot be negative. Defaults to `1.0`.
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## Notes [distance-feature-notes]
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### How the `distance_feature` query calculates relevance scores [distance-feature-calculation]
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The `distance_feature` query dynamically calculates the distance between the `origin` value and a document’s field values. It then uses this distance as a feature to boost the [relevance score](/reference/query-languages/query-filter-context.md#relevance-scores) of closer documents.
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The `distance_feature` query calculates a document’s [relevance score](/reference/query-languages/query-filter-context.md#relevance-scores) as follows:
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```
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relevance score = boost * pivot / (pivot + distance)
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```
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The `distance` is the absolute difference between the `origin` value and a document’s field value.
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### Skip non-competitive hits [distance-feature-skip-hits]
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Unlike the [`function_score`](/reference/query-languages/query-dsl-function-score-query.md) query or other ways to change [relevance scores](/reference/query-languages/query-filter-context.md#relevance-scores), the `distance_feature` query efficiently skips non-competitive hits when the [`track_total_hits`](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-search) parameter is **not** `true`.
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