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* master: (36 commits) Ensure joda compatibility in custom date formats (elastic#38171) Do not compute cardinality if the `terms` execution mode does not use `global_ordinals` (elastic#38169) Do not set timeout for IndexRequests in GatewayIndexStateIT (elastic#38147) Zen2ify testMasterFailoverDuringIndexingWithMappingChanges (elastic#38178) SQL: [Docs] Add limitation for aggregate functions on scalars (elastic#38186) Add elasticsearch-node detach-cluster command (elastic#37979) Add tests for fractional epoch parsing (elastic#38162) Enable bw tests for elastic#37871 and elastic#38032. (elastic#38167) Clear send behavior rule in CloseWhileRelocatingShardsIT (elastic#38159) Fix testCorruptedIndex (elastic#38161) Add finalReduce flag to SearchRequest (elastic#38104) Forbid negative field boosts in analyzed queries (elastic#37930) Remove AtomiFieldData#getLegacyFieldValues (elastic#38087) Universal cluster bootstrap method for tests with autoMinMasterNodes=false (elastic#38038) Fix FullClusterRestartIT.testHistoryUUIDIsAdded (elastic#38098) Replace joda time in ingest-common module (elastic#38088) Fix eclipse config for ssl-config (elastic#38096) Don't load global ordinals with the `map` execution_hint (elastic#37833) Relax fault detector in some disruption tests (elastic#38101) Fix java time epoch date formatters (elastic#37829) ...
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docs/reference/aggregations/bucket/geotilegrid-aggregation.asciidoc
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| [[search-aggregations-bucket-geotilegrid-aggregation]] | ||
| === GeoTile Grid Aggregation | ||
|
|
||
| A multi-bucket aggregation that works on `geo_point` fields and groups points into | ||
| buckets that represent cells in a grid. The resulting grid can be sparse and only | ||
| contains cells that have matching data. Each cell corresponds to a | ||
| https://en.wikipedia.org/wiki/Tiled_web_map[map tile] as used by many online map | ||
| sites. Each cell is labeled using a "{zoom}/{x}/{y}" format, where zoom is equal | ||
| to the user-specified precision. | ||
|
|
||
| * High precision keys have a larger range for x and y, and represent tiles that | ||
| cover only a small area. | ||
| * Low precision keys have a smaller range for x and y, and represent tiles that | ||
| each cover a large area. | ||
|
|
||
| See https://wiki.openstreetmap.org/wiki/Zoom_levels[Zoom level documentation] | ||
| on how precision (zoom) correlates to size on the ground. Precision for this | ||
| aggregation can be between 0 and 29, inclusive. | ||
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||
| WARNING: The highest-precision geotile of length 29 produces cells that cover | ||
| less than a 10cm by 10cm of land and so high-precision requests can be very | ||
| costly in terms of RAM and result sizes. Please see the example below on how | ||
| to first filter the aggregation to a smaller geographic area before requesting | ||
| high-levels of detail. | ||
|
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| The specified field must be of type `geo_point` (which can only be set | ||
| explicitly in the mappings) and it can also hold an array of `geo_point` | ||
| fields, in which case all points will be taken into account during aggregation. | ||
|
|
||
|
|
||
| ==== Simple low-precision request | ||
|
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||
| [source,js] | ||
| -------------------------------------------------- | ||
| PUT /museums | ||
| { | ||
| "mappings": { | ||
| "properties": { | ||
| "location": { | ||
| "type": "geo_point" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| POST /museums/_bulk?refresh | ||
| {"index":{"_id":1}} | ||
| {"location": "52.374081,4.912350", "name": "NEMO Science Museum"} | ||
| {"index":{"_id":2}} | ||
| {"location": "52.369219,4.901618", "name": "Museum Het Rembrandthuis"} | ||
| {"index":{"_id":3}} | ||
| {"location": "52.371667,4.914722", "name": "Nederlands Scheepvaartmuseum"} | ||
| {"index":{"_id":4}} | ||
| {"location": "51.222900,4.405200", "name": "Letterenhuis"} | ||
| {"index":{"_id":5}} | ||
| {"location": "48.861111,2.336389", "name": "Musée du Louvre"} | ||
| {"index":{"_id":6}} | ||
| {"location": "48.860000,2.327000", "name": "Musée d'Orsay"} | ||
| POST /museums/_search?size=0 | ||
| { | ||
| "aggregations" : { | ||
| "large-grid" : { | ||
| "geotile_grid" : { | ||
| "field" : "location", | ||
| "precision" : 8 | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // CONSOLE | ||
|
|
||
| Response: | ||
|
|
||
| [source,js] | ||
| -------------------------------------------------- | ||
| { | ||
| ... | ||
| "aggregations": { | ||
| "large-grid": { | ||
| "buckets": [ | ||
| { | ||
| "key" : "8/131/84", | ||
| "doc_count" : 3 | ||
| }, | ||
| { | ||
| "key" : "8/129/88", | ||
| "doc_count" : 2 | ||
| }, | ||
| { | ||
| "key" : "8/131/85", | ||
| "doc_count" : 1 | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/] | ||
|
|
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| ==== High-precision requests | ||
|
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||
| When requesting detailed buckets (typically for displaying a "zoomed in" map) | ||
| a filter like <<query-dsl-geo-bounding-box-query,geo_bounding_box>> should be | ||
| applied to narrow the subject area otherwise potentially millions of buckets | ||
| will be created and returned. | ||
|
|
||
| [source,js] | ||
| -------------------------------------------------- | ||
| POST /museums/_search?size=0 | ||
| { | ||
| "aggregations" : { | ||
| "zoomed-in" : { | ||
| "filter" : { | ||
| "geo_bounding_box" : { | ||
| "location" : { | ||
| "top_left" : "52.4, 4.9", | ||
| "bottom_right" : "52.3, 5.0" | ||
| } | ||
| } | ||
| }, | ||
| "aggregations":{ | ||
| "zoom1":{ | ||
| "geotile_grid" : { | ||
| "field": "location", | ||
| "precision": 22 | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // CONSOLE | ||
| // TEST[continued] | ||
|
|
||
| [source,js] | ||
| -------------------------------------------------- | ||
| { | ||
| ... | ||
| "aggregations" : { | ||
| "zoomed-in" : { | ||
| "doc_count" : 3, | ||
| "zoom1" : { | ||
| "buckets" : [ | ||
| { | ||
| "key" : "22/2154412/1378379", | ||
| "doc_count" : 1 | ||
| }, | ||
| { | ||
| "key" : "22/2154385/1378332", | ||
| "doc_count" : 1 | ||
| }, | ||
| { | ||
| "key" : "22/2154259/1378425", | ||
| "doc_count" : 1 | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| } | ||
| -------------------------------------------------- | ||
| // TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/] | ||
|
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|
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| ==== Options | ||
|
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||
| [horizontal] | ||
| field:: Mandatory. The name of the field indexed with GeoPoints. | ||
|
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| precision:: Optional. The integer zoom of the key used to define | ||
| cells/buckets in the results. Defaults to 7. | ||
| Values outside of [0,29] will be rejected. | ||
|
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| size:: Optional. The maximum number of geohash buckets to return | ||
| (defaults to 10,000). When results are trimmed, buckets are | ||
| prioritised based on the volumes of documents they contain. | ||
|
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| shard_size:: Optional. To allow for more accurate counting of the top cells | ||
| returned in the final result the aggregation defaults to | ||
| returning `max(10,(size x number-of-shards))` buckets from each | ||
| shard. If this heuristic is undesirable, the number considered | ||
| from each shard can be over-ridden using this parameter. |
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