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Merge branch 'master' into retention-leases-version
* 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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‎client/rest-high-level/src/main/java/org/elasticsearch/client/RestHighLevelClient.java

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import org.elasticsearch.search.aggregations.bucket.filter.ParsedFilters;
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import org.elasticsearch.search.aggregations.bucket.geogrid.GeoHashGridAggregationBuilder;
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import org.elasticsearch.search.aggregations.bucket.geogrid.ParsedGeoHashGrid;
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import org.elasticsearch.search.aggregations.bucket.geogrid.ParsedGeoTileGrid;
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import org.elasticsearch.search.aggregations.bucket.geogrid.GeoTileGridAggregationBuilder;
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import org.elasticsearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
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import org.elasticsearch.search.aggregations.bucket.global.ParsedGlobal;
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import org.elasticsearch.search.aggregations.bucket.histogram.AutoDateHistogramAggregationBuilder;
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map.put(FilterAggregationBuilder.NAME, (p, c) -> ParsedFilter.fromXContent(p, (String) c));
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map.put(InternalSampler.PARSER_NAME, (p, c) -> ParsedSampler.fromXContent(p, (String) c));
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map.put(GeoHashGridAggregationBuilder.NAME, (p, c) -> ParsedGeoHashGrid.fromXContent(p, (String) c));
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map.put(GeoTileGridAggregationBuilder.NAME, (p, c) -> ParsedGeoTileGrid.fromXContent(p, (String) c));
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map.put(RangeAggregationBuilder.NAME, (p, c) -> ParsedRange.fromXContent(p, (String) c));
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map.put(DateRangeAggregationBuilder.NAME, (p, c) -> ParsedDateRange.fromXContent(p, (String) c));
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map.put(GeoDistanceAggregationBuilder.NAME, (p, c) -> ParsedGeoDistance.fromXContent(p, (String) c));

‎client/rest-high-level/src/test/java/org/elasticsearch/client/ClusterClientIT.java

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assertThat(response.getIndices().size(), equalTo(0));
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}
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@AwaitsFix(bugUrl="https://github.com/elastic/elasticsearch/issues/35450")
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public void testClusterHealthYellowIndicesLevel() throws IOException {
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createIndex("index", Settings.EMPTY);
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createIndex("index2", Settings.EMPTY);

‎docs/reference/aggregations/bucket/geotilegrid-aggregation.asciidoc

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[[search-aggregations-bucket-geotilegrid-aggregation]]
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=== GeoTile Grid Aggregation
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A multi-bucket aggregation that works on `geo_point` fields and groups points into
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buckets that represent cells in a grid. The resulting grid can be sparse and only
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contains cells that have matching data. Each cell corresponds to a
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https://en.wikipedia.org/wiki/Tiled_web_map[map tile] as used by many online map
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sites. Each cell is labeled using a "{zoom}/{x}/{y}" format, where zoom is equal
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to the user-specified precision.
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* High precision keys have a larger range for x and y, and represent tiles that
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cover only a small area.
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* Low precision keys have a smaller range for x and y, and represent tiles that
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each cover a large area.
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See https://wiki.openstreetmap.org/wiki/Zoom_levels[Zoom level documentation]
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on how precision (zoom) correlates to size on the ground. Precision for this
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aggregation can be between 0 and 29, inclusive.
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WARNING: The highest-precision geotile of length 29 produces cells that cover
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less than a 10cm by 10cm of land and so high-precision requests can be very
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costly in terms of RAM and result sizes. Please see the example below on how
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to first filter the aggregation to a smaller geographic area before requesting
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high-levels of detail.
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The specified field must be of type `geo_point` (which can only be set
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explicitly in the mappings) and it can also hold an array of `geo_point`
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fields, in which case all points will be taken into account during aggregation.
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==== Simple low-precision request
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[source,js]
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--------------------------------------------------
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PUT /museums
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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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POST /museums/_bulk?refresh
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{"index":{"_id":1}}
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{"location": "52.374081,4.912350", "name": "NEMO Science Museum"}
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{"index":{"_id":2}}
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{"location": "52.369219,4.901618", "name": "Museum Het Rembrandthuis"}
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{"index":{"_id":3}}
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{"location": "52.371667,4.914722", "name": "Nederlands Scheepvaartmuseum"}
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{"index":{"_id":4}}
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{"location": "51.222900,4.405200", "name": "Letterenhuis"}
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{"index":{"_id":5}}
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{"location": "48.861111,2.336389", "name": "Musée du Louvre"}
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{"index":{"_id":6}}
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{"location": "48.860000,2.327000", "name": "Musée d'Orsay"}
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POST /museums/_search?size=0
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{
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"aggregations" : {
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"large-grid" : {
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"geotile_grid" : {
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"field" : "location",
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"precision" : 8
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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Response:
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[source,js]
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--------------------------------------------------
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{
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...
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"aggregations": {
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"large-grid": {
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"buckets": [
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{
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"key" : "8/131/84",
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"doc_count" : 3
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},
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{
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"key" : "8/129/88",
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"doc_count" : 2
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},
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{
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"key" : "8/131/85",
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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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// 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)
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a filter like <<query-dsl-geo-bounding-box-query,geo_bounding_box>> should be
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applied to narrow the subject area otherwise potentially millions of buckets
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will be created and returned.
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[source,js]
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--------------------------------------------------
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POST /museums/_search?size=0
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{
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"aggregations" : {
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"zoomed-in" : {
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"filter" : {
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"geo_bounding_box" : {
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"location" : {
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"top_left" : "52.4, 4.9",
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"bottom_right" : "52.3, 5.0"
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}
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}
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},
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"aggregations":{
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"zoom1":{
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"geotile_grid" : {
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"field": "location",
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"precision": 22
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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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// CONSOLE
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// TEST[continued]
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[source,js]
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--------------------------------------------------
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{
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...
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"aggregations" : {
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"zoomed-in" : {
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"doc_count" : 3,
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"zoom1" : {
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"buckets" : [
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{
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"key" : "22/2154412/1378379",
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"doc_count" : 1
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},
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{
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"key" : "22/2154385/1378332",
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"doc_count" : 1
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},
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{
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"key" : "22/2154259/1378425",
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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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// TESTRESPONSE[s/\.\.\./"took": $body.took,"_shards": $body._shards,"hits":$body.hits,"timed_out":false,/]
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==== Options
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[horizontal]
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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
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cells/buckets in the results. Defaults to 7.
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Values outside of [0,29] will be rejected.
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size:: Optional. The maximum number of geohash buckets to return
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(defaults to 10,000). When results are trimmed, buckets are
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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
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returned in the final result the aggregation defaults to
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returning `max(10,(size x number-of-shards))` buckets from each
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shard. If this heuristic is undesirable, the number considered
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from each shard can be over-ridden using this parameter.

‎docs/reference/ingest/processors/user-agent.asciidoc

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"version": "10.10.5",
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"full": "Mac OS X 10.10.5"
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},
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"device": "Other"
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"device" : {
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"name" : "Other"
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},
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}
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}
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}

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