393 lines
10 KiB
Markdown
393 lines
10 KiB
Markdown
---
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layout: default
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title: Geohex grid
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parent: Bucket aggregations
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grand_parent: Aggregations
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nav_order: 85
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redirect_from:
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- /aggregations/geohexgrid/
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- /query-dsl/aggregations/geohexgrid/
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- /query-dsl/aggregations/bucket/geohex-grid/
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---
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# Geohex grid aggregations
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The Hexagonal Hierarchical Geospatial Indexing System (H3) partitions the Earth's areas into identifiable hexagon-shaped cells.
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The H3 grid system works well for proximity applications because it overcomes the limitations of Geohash's non-uniform partitions. Geohash encodes latitude and longitude pairs, leading to significantly smaller partitions near the poles and a degree of longitude near the equator. However, the H3 grid system's distortions are low and limited to 5 partitions of 122. These five partitions are placed in low-use areas (for example, in the middle of the ocean), leaving the essential areas error free. Thus, grouping documents based on the H3 grid system provides a better aggregation than the Geohash grid.
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The geohex grid aggregation groups [geopoints]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/geo-point/) into grid cells for geographical analysis. Each grid cell corresponds to an [H3 cell](https://h3geo.org/docs/core-library/h3Indexing/#h3-cell-indexp) and is identified using the [H3Index representation](https://h3geo.org/docs/core-library/h3Indexing/#h3index-representation).
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## Precision
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The `precision` parameter controls the level of granularity that determines the grid cell size. The lower the precision, the larger the grid cells.
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The following example illustrates low-precision and high-precision aggregation requests.
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To start, create an index and map the `location` field as a `geo_point`:
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```json
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PUT national_parks
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{
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"mappings": {
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"properties": {
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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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{% include copy-curl.html %}
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Index the following documents into the sample index:
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```json
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PUT national_parks/_doc/1
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{
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"name": "Yellowstone National Park",
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"location": "44.42, -110.59"
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}
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```
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{% include copy-curl.html %}
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```json
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PUT national_parks/_doc/2
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{
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"name": "Yosemite National Park",
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"location": "37.87, -119.53"
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}
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```
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{% include copy-curl.html %}
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```json
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PUT national_parks/_doc/3
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{
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"name": "Death Valley National Park",
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"location": "36.53, -116.93"
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}
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```
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{% include copy-curl.html %}
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You can index geopoints in several formats. For a list of all supported formats, see the [geopoint documentation]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/geo-point#formats).
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{: .note}
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## Low-precision requests
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Run a low-precision request that buckets all three documents together:
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```json
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GET national_parks/_search
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{
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"aggregations": {
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"grouped": {
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"geohex_grid": {
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"field": "location",
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"precision": 1
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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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You can use either the `GET` or `POST` HTTP method for geohex grid aggregation queries.
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{: .note}
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The response groups documents 2 and 3 together because they are close enough to be bucketed in one grid cell:
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```json
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{
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"took" : 4,
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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" : "44.42, -110.59"
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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" : "37.87, -119.53"
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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" : "36.53, -116.93"
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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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"buckets" : [
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{
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"key" : "8129bffffffffff",
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"doc_count" : 2
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},
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{
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"key" : "8128bffffffffff",
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"doc_count" : 1
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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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## High-precision requests
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Now run a high-precision request:
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```json
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GET national_parks/_search
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{
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"aggregations": {
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"grouped": {
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"geohex_grid": {
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"field": "location",
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"precision": 6
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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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All three documents are bucketed separately because of higher granularity:
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```json
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{
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"took" : 5,
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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" : "44.42, -110.59"
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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" : "37.87, -119.53"
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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" : "36.53, -116.93"
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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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"buckets" : [
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{
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"key" : "8629ab6dfffffff",
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"doc_count" : 1
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},
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{
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"key" : "8629857a7ffffff",
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"doc_count" : 1
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},
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{
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"key" : "862896017ffffff",
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"doc_count" : 1
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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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## Filtering requests
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High-precision requests are resource intensive, so we recommend using a filter like `geo_bounding_box` to limit the geographical area. For example, the following query applies a filter to limit the search area:
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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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"filtered": {
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"filter": {
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"geo_bounding_box": {
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"location": {
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"top_left": "38, -120",
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"bottom_right": "36, -116"
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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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"geohex_grid": {
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"field": "location",
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"precision": 6
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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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{% include copy-curl.html %}
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The response contains the two documents that are within the `geo_bounding_box` bounds:
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```json
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{
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"took" : 4,
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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" : null,
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"hits" : [ ]
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},
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"aggregations" : {
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"filtered" : {
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"doc_count" : 2,
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"grouped" : {
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"buckets" : [
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{
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"key" : "8629ab6dfffffff",
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"doc_count" : 1
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},
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{
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"key" : "8629857a7ffffff",
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"doc_count" : 1
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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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You can also restrict the geographical area by providing the coordinates of the bounding envelope in the `bounds` parameter. Both `bounds` and `geo_bounding_box` coordinates can be specified in any of the [geopoint formats]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/geo-point#formats). The following query uses the well-known text (WKT) "POINT(`longitude` `latitude`)" format for the `bounds` parameter:
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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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"geohex_grid": {
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"field": "location",
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"precision": 6,
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"bounds": {
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"top_left": "POINT (-120 38)",
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"bottom_right": "POINT (-116 36)"
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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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{% include copy-curl.html %}
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The response contains only the two results that are within the specified bounds:
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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" : null,
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"hits" : [ ]
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},
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"aggregations" : {
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"grouped" : {
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"buckets" : [
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{
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"key" : "8629ab6dfffffff",
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"doc_count" : 1
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},
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{
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"key" : "8629857a7ffffff",
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"doc_count" : 1
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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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The `bounds` parameter can be used with or without the `geo_bounding_box` filter; these two parameters are independent and can have any spatial relationship to each other.
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## Supported parameters
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Geohex grid aggregation requests support the following parameters.
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Parameter | Data type | Description
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:--- | :--- | :---
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field | String | The field that contains the geopoints. This field must be mapped as a `geo_point` field. If the field contains an array, all array values are aggregated. Required.
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precision | Integer | The zoom level used to determine grid cells for bucketing results. Valid values are in the [0, 15] range. Optional. Default is 5.
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bounds | Object | The bounding box for filtering geopoints. The bounding box is defined by the upper-left and lower-right vertices. The vertices are specified as geopoints in one of the following formats: <br>- An object with a latitude and longitude<br>- An array in the [`longitude`, `latitude`] format<br>- A string in the "`latitude`,`longitude`" format<br>- A geohash <br>- WKT<br> See the [geopoint formats]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/geo-point#formats) for formatting examples. Optional.
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size | Integer | The maximum number of buckets to return. When there are more buckets than `size`, OpenSearch returns buckets with more documents. Optional. Default is 10,000.
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shard_size | Integer | The maximum number of buckets to return from each shard. Optional. Default is max (10, `size` · number of shards), which provides a more accurate count of more highly prioritized buckets. |