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The `geo_bounds`metric is a multi-value metric aggregation that calculates the [geographic bounding box](https://docs.ogc.org/is/12-063r5/12-063r5.html#30)containing all values of a given `geo_point` or `geo_shape`field. The bounding box is returned as the upper-left and lower-right vertices of the rectangle in terms of latitude and longitude.
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The `geo_bounds`aggregation is a multi-value aggregation that calculates the [geographic bounding box](https://docs.ogc.org/is/12-063r5/12-063r5.html#30)encompassing a set of [`geo_point`](https://opensearch.org/docs/latest/field-types/supported-field-types/geo-point/) or [`geo_shape`](https://opensearch.org/docs/latest/field-types/supported-field-types/geo-shape/) objects. The bounding box is returned as the upper-left and lower-right vertices of the rectangle given as a decimal-encoded latitude-longitude (lat-lon) pair.
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The following example returns the `geo_bounds` metrics for the `geoip.location` field:
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## Parameters
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The `geo_bounds` aggregation takes the following parameters.
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| Parameter | Required/Optional | Data type | Description |
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| :-- | :-- | :-- | :-- |
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|`field`| Required | String | The name of the field containing the geopoints or geoshapes for which the geobounds are computed. |
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|`wrap_longitude`| Optional | Boolean | Whether to allow the bounding box to overlap the international date line. Default is `true`. |
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## Example
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The following example returns the `geo_bounds` for the `geoip.location` of every order in the e-commerce sample data (each `geoip.location` is a geopoint):
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```json
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GET opensearch_dashboards_sample_data_ecommerce/_search
@@ -26,30 +37,52 @@ GET opensearch_dashboards_sample_data_ecommerce/_search
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}
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}
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```
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{% include copy-curl.html %}
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## Example response
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#### Example response
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As shown in the following example response, the aggregation returns the `geobounds` containing all geopoints in the `geoip.location` field:
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```json
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"aggregations" : {
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"geo" : {
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"bounds" : {
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"top_left" : {
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"lat" : 52.49999997206032,
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"lon" : -118.20000001229346
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},
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"bottom_right" : {
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"lat" : 4.599999985657632,
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"lon" : 55.299999956041574
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{
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"took": 16,
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"timed_out": false,
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"_shards": {
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"total": 1,
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"successful": 1,
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"skipped": 0,
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"failed": 0
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},
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"hits": {
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"total": {
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"value": 4675,
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"relation": "eq"
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},
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"max_score": null,
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"hits": []
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},
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"aggregations": {
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"geo": {
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"bounds": {
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"top_left": {
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"lat": 52.49999997206032,
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"lon": -118.20000001229346
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},
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"bottom_right": {
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"lat": 4.599999985657632,
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"lon": 55.299999956041574
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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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```
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## Aggregating geoshapes
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To run an aggregation on a geoshape field, first create an index and map the `location` field as a `geo_shape`:
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You can run a `geo_bounds` aggregation on geoshapes.
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Prepare an example by inserting an index containing a geoshape field:
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```json
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PUT national_parks
@@ -65,164 +98,119 @@ PUT national_parks
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```
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{% include copy-curl.html %}
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Next, index some documents into the `national_parks`index:
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Ingest documents into the index. GeoJSON input specifies longitude first:
You can run a `geo_bounds` aggregation on the `location` field as follows:
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## Wrapping longitude
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If the optional `wrap_longitude` parameter is set to `true`, the bounding box can overlap the international date line (180° meridian) and return a `bounds` object in which the upper-left longitude is greater than the lower-right longitude. The default value for `wrap_longitude` is `true`.
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Rerun the `geo_bounds` aggregation on the national parks geoshape with `wrap_longitude` set to `false`:
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```json
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GET national_parks/_search
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{
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"size": 0,
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"aggregations": {
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"grouped": {
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"geo_bounds": {
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"field": "location",
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"wrap_longitude": true
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"wrap_longitude": false
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}
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}
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}
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}
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```
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{% include copy-curl.html %}
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The optional `wrap_longitude` parameter specifies whether the bounding box returned by the aggregation can overlap the international date line (180° meridian). If `wrap_longitude` is set to `true`, the bounding box can overlap the international date line and return a `bounds` object in which the lower-left longitude is greater than the upper-right longitude. The default value for `wrap_longitude` is `true`.
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The response contains the geo-bounding box that encloses all shapes in the `location` field:
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<detailsopenmarkdown="block">
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<summary>
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Response
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</summary>
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{: .text-delta}
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Note that the new resulting geobound encompasses a larger area to avoid overlapping the dateline:
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```json
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{
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"took" : 3,
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"timed_out" : false,
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"_shards" : {
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"total" : 1,
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"successful" : 1,
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"skipped" : 0,
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"failed" : 0
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},
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"hits" : {
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"total" : {
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"value" : 3,
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"relation" : "eq"
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},
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"max_score" : 1.0,
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"hits" : [
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{
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"_index" : "national_parks",
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"_id" : "1",
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"_score" : 1.0,
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"_source" : {
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"name" : "Yellowstone National Park",
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"location" : {
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"type" : "envelope",
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"coordinates" : [
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[
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-111.15,
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45.12
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],
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[
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-109.83,
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44.12
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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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"_index" : "national_parks",
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"_id" : "2",
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"_score" : 1.0,
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"_source" : {
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"name" : "Yosemite National Park",
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"location" : {
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"type" : "envelope",
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"coordinates" : [
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[
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-120.23,
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],
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[
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-119.05,
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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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"_index" : "national_parks",
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"_id" : "3",
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"_score" : 1.0,
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"_source" : {
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"name" : "Death Valley National Park",
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"location" : {
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"type" : "envelope",
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"coordinates" : [
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[
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-117.34,
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37.01
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],
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[
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-116.38,
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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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},
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"aggregations" : {
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"Grouped" : {
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"bounds" : {
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"top_left" : {
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"lat" : 45.11999997776002,
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"lon" : -120.23000006563962
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...
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"aggregations": {
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"grouped": {
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"bounds": {
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"top_left": {
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"lat": 45.11999997776002,
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"lon": -120.23000006563962
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},
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"bottom_right": {
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"lat" : 36.249999976716936,
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"lon" : -109.83000006526709
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"bottom_right": {
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"lat": 13.469999986700714,
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"lon": 144.71999991685152
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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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</details>
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Currently, OpenSearch supports geoshape aggregation through the API but not in OpenSearch Dashboards visualizations. If you'd like to see geoshape aggregation implemented for visualizations, upvote the related [GitHub issue](https://github.com/opensearch-project/dashboards-maps/issues/250).
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OpenSearch supports geoshape aggregation through the API but not in OpenSearch Dashboards visualizations.
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