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new geo_grid query to be used with geogrid aggregations (#86596)
Query that allows users to define a query where the input is the key of the bucket and it will match the documents inside that bucket.
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| [[query-dsl-geo-grid-query]] | ||
| === Geo-grid query | ||
| ++++ | ||
| <titleabbrev>Geo-grid</titleabbrev> | ||
| ++++ | ||
|
|
||
| Matches <<geo-point,`geo_point`>> and <<geo-shape,`geo_shape`>> values that | ||
| intersect a grid cell from a GeoGrid aggregation. | ||
|
|
||
| The query is designed to match the documents that fall inside a bucket of a geogrid aggregation by | ||
| providing the key of the bucket. For geohash and geotile grids, the query can be used for geo_point | ||
| and geo_shape fields. For geo_hex grid, it can only be used for geo_point fields. | ||
|
|
||
| [discrete] | ||
| [[geo-grid-query-ex]] | ||
| ==== Example | ||
| Assume the following the following documents are indexed: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| PUT /my_locations | ||
| { | ||
| "mappings": { | ||
| "properties": { | ||
| "location": { | ||
| "type": "geo_point" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| PUT /my_locations/_doc/1?refresh | ||
| { | ||
| "location" : "POINT(4.912350 52.374081)", | ||
| "city": "Amsterdam", | ||
| "name": "NEMO Science Museum" | ||
| } | ||
| PUT /my_locations/_doc/2?refresh | ||
| { | ||
| "location" : "POINT(4.405200 51.222900)", | ||
| "city": "Antwerp", | ||
| "name": "Letterenhuis" | ||
| } | ||
| PUT /my_locations/_doc/3?refresh | ||
| { | ||
| "location" : "POINT(2.336389 48.861111)", | ||
| "city": "Paris", | ||
| "name": "Musée du Louvre" | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTSETUP | ||
|
|
||
| [[query-dsl-geo-grid-query-geohash]] | ||
| ==== geohash grid | ||
|
|
||
| Using a geohash_grid aggregation, it is possible to group documents depending on their geohash value: | ||
|
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||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "size" : 0, | ||
| "aggs" : { | ||
| "grouped" : { | ||
| "geohash_grid" : { | ||
| "field" : "location", | ||
| "precision" : 2 | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 10, | ||
| "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" : "u1", | ||
| "doc_count" : 2 | ||
| }, | ||
| { | ||
| "key" : "u0", | ||
| "doc_count" : 1 | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 10/"took" : $body.took/] | ||
|
|
||
| We can extract the documents on one of those buckets by executing a geo_grid query | ||
| using the bucket key with the following syntax: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "query": { | ||
| "geo_grid" :{ | ||
| "location" : { | ||
| "geohash" : "u0" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 1, | ||
| "timed_out" : false, | ||
| "_shards" : { | ||
| "total" : 1, | ||
| "successful" : 1, | ||
| "skipped" : 0, | ||
| "failed" : 0 | ||
| }, | ||
| "hits" : { | ||
| "total" : { | ||
| "value" : 1, | ||
| "relation" : "eq" | ||
| }, | ||
| "max_score" : 1.0, | ||
| "hits" : [ | ||
| { | ||
| "_index" : "my_locations", | ||
| "_id" : "3", | ||
| "_score" : 1.0, | ||
| "_source" : { | ||
| "location" : "POINT(2.336389 48.861111)", | ||
| "city" : "Paris", | ||
| "name" : "Musée du Louvre" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 1/"took" : $body.took/] | ||
|
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||
|
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||
| [[query-dsl-geo-grid-query-geotile]] | ||
| ==== geotile grid | ||
|
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||
| Using a geotile_grid aggregation, it is possible to group documents depending on their geotile value: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "size" : 0, | ||
| "aggs" : { | ||
| "grouped" : { | ||
| "geotile_grid" : { | ||
| "field" : "location", | ||
| "precision" : 6 | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 1, | ||
| "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" : "6/32/21", | ||
| "doc_count" : 2 | ||
| }, | ||
| { | ||
| "key" : "6/32/22", | ||
| "doc_count" : 1 | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 1/"took" : $body.took/] | ||
|
|
||
| We can extract the documents on one of those buckets by executing a geo_grid query | ||
| using the bucket key with the following syntax: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "query": { | ||
| "geo_grid" :{ | ||
| "location" : { | ||
| "geotile" : "6/32/22" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 1, | ||
| "timed_out" : false, | ||
| "_shards" : { | ||
| "total" : 1, | ||
| "successful" : 1, | ||
| "skipped" : 0, | ||
| "failed" : 0 | ||
| }, | ||
| "hits" : { | ||
| "total" : { | ||
| "value" : 1, | ||
| "relation" : "eq" | ||
| }, | ||
| "max_score" : 1.0, | ||
| "hits" : [ | ||
| { | ||
| "_index" : "my_locations", | ||
| "_id" : "3", | ||
| "_score" : 1.0, | ||
| "_source" : { | ||
| "location" : "POINT(2.336389 48.861111)", | ||
| "city" : "Paris", | ||
| "name" : "Musée du Louvre" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 1/"took" : $body.took/] | ||
|
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||
|
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| [[query-dsl-geo-grid-query-geohex]] | ||
| ==== geohex grid | ||
|
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| Using a geohex_grid aggregation, it is possible to group documents depending on their geohex value: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "size" : 0, | ||
| "aggs" : { | ||
| "grouped" : { | ||
| "geohex_grid" : { | ||
| "field" : "location", | ||
| "precision" : 1 | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 2, | ||
| "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" : "81197ffffffffff", | ||
| "doc_count" : 2 | ||
| }, | ||
| { | ||
| "key" : "811fbffffffffff", | ||
| "doc_count" : 1 | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 2/"took" : $body.took/] | ||
|
|
||
| We can extract the documents on one of those buckets by executing a geo_grid query | ||
| using the bucket key with the following syntax: | ||
|
|
||
| [source,console] | ||
| -------------------------------------------------- | ||
| GET /my_locations/_search | ||
| { | ||
| "query": { | ||
| "geo_grid" :{ | ||
| "location" : { | ||
| "geohex" : "811fbffffffffff" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
|
|
||
|
|
||
| [source,console-result] | ||
| -------------------------------------------------- | ||
| { | ||
| "took" : 26, | ||
| "timed_out" : false, | ||
| "_shards" : { | ||
| "total" : 1, | ||
| "successful" : 1, | ||
| "skipped" : 0, | ||
| "failed" : 0 | ||
| }, | ||
| "hits" : { | ||
| "total" : { | ||
| "value" : 1, | ||
| "relation" : "eq" | ||
| }, | ||
| "max_score" : 1.0, | ||
| "hits" : [ | ||
| { | ||
| "_index" : "my_locations", | ||
| "_id" : "3", | ||
| "_score" : 1.0, | ||
| "_source" : { | ||
| "location" : "POINT(2.336389 48.861111)", | ||
| "city" : "Paris", | ||
| "name" : "Musée du Louvre" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/"took" : 26/"took" : $body.took/] |
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