The Hexagonal Hierarchical Geospatial Indexing System (H3) partitions the Earth's areas into identifiable hexagon-shaped cells.
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.
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).
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).
{: .note}
## Low-precision requests
Run a low-precision request that buckets all three documents together:
All three documents are bucketed separately because of higher granularity:
```json
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "national_parks",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "Yellowstone National Park",
"location" : "44.42, -110.59"
}
},
{
"_index" : "national_parks",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"name" : "Yosemite National Park",
"location" : "37.87, -119.53"
}
},
{
"_index" : "national_parks",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"name" : "Death Valley National Park",
"location" : "36.53, -116.93"
}
}
]
},
"aggregations" : {
"grouped" : {
"buckets" : [
{
"key" : "8629ab6dfffffff",
"doc_count" : 1
},
{
"key" : "8629857a7ffffff",
"doc_count" : 1
},
{
"key" : "862896017ffffff",
"doc_count" : 1
}
]
}
}
}
```
## Filtering requests
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:
The response contains the two documents that are within the `geo_bounding_box` bounds:
```json
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"filtered" : {
"doc_count" : 2,
"grouped" : {
"buckets" : [
{
"key" : "8629ab6dfffffff",
"doc_count" : 1
},
{
"key" : "8629857a7ffffff",
"doc_count" : 1
}
]
}
}
}
}
```
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:
The response contains only the two results that are within the specified bounds:
```json
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"grouped" : {
"buckets" : [
{
"key" : "8629ab6dfffffff",
"doc_count" : 1
},
{
"key" : "8629857a7ffffff",
"doc_count" : 1
}
]
}
}
}
```
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.
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.
precision | Integer | The granularity level used to determine grid cells for bucketing results. Cells cannot exceed the specified size (diagonal) of the required precision. Valid values are in the [0, 15] range. Optional. Default is 5.
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.
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.
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.
