2.1 KiB
| layout | title | parent | grand_parent | nav_order |
|---|---|---|---|---|
| default | Geohash grid | Bucket aggregations | Aggregations | 80 |
Geohash grid aggregations
The geohash_grid aggregation buckets documents for geographical analysis. It organizes a geographical region into a grid of smaller regions of different sizes or precisions. Lower values of precision represent larger geographical areas and higher values represent smaller, more precise geographical areas.
The number of results returned by a query might be far too many to display each geopoint individually on a map. The geohash_grid aggregation buckets nearby geopoints together by calculating the geohash for each point, at the level of precision that you define (between 1 to 12; the default is 5). To learn more about geohash, see Wikipedia.
The web logs example data is spread over a large geographical area, so you can use a lower precision value. You can zoom in on this map by increasing the precision value:
GET opensearch_dashboards_sample_data_logs/_search
{
"size": 0,
"aggs": {
"geo_hash": {
"geohash_grid": {
"field": "geo.coordinates",
"precision": 4
}
}
}
}
Example response
...
"aggregations" : {
"geo_hash" : {
"buckets" : [
{
"key" : "c1cg",
"doc_count" : 104
},
{
"key" : "dr5r",
"doc_count" : 26
},
{
"key" : "9q5b",
"doc_count" : 20
},
{
"key" : "c20g",
"doc_count" : 19
},
{
"key" : "dr70",
"doc_count" : 18
}
...
]
}
}
}
You can visualize the aggregated response on a map using OpenSearch Dashboards.
The more accurate you want the aggregation to be, the more resources OpenSearch consumes, because of the number of buckets that the aggregation has to calculate. By default, OpenSearch does not generate more than 10,000 buckets. You can change this behavior by using the size attribute, but keep in mind that the performance might suffer for very wide queries consisting of thousands of buckets.