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craigtavernercraigtaverner
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Enhanced REST tests for geo and cartesian centroid (#94964)
* Enhanced REST tests for geo and cartesian centroid Coverage increased to cover cases for: * centroid over points * centroid over shapes * centroid over points with filter * centroid over shapes with filter * centroid over points with grouping * centroid over shapes with grouping * centroid over shapes with grouping and filter The last one was not done for points because the purpose of that test was primarily to validate the shape rules where centroids over GEOMETRYCOLLECTION would use only the highest dimensionality geometries for centroid calculation. * Enforce single shard So reduce risk of flakiness in aggregating over multiple documents
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‎x-pack/plugin/src/yamlRestTest/resources/rest-api-spec/test/spatial/20_cartesian_centroid.yml‎

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setup:
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- skip:
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features: close_to
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- do:
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indices.create:
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index: locations
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body:
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mappings:
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properties:
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location:
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type: shape
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city:
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type: keyword
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name:
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type: keyword
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- do:
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bulk:
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refresh: true
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index: locations
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body: |
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{"index":{}}
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{"location": "POINT(488.9187 5237.3184)", "city": "Amsterdam", "name": "Royal Palace Amsterdam"}
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{"index":{}}
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{"location": "POINT(488.5057 5237.0159)", "city": "Amsterdam", "name": "The Amsterdam Dungeon"}
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{"index":{}}
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{"location": "POINT(490.1618 5236.9219)", "city": "Amsterdam", "name": "Museum Het Rembrandthuis"}
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{"index":{}}
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{"location": "POINT(491.2350 5237.4081)", "city": "Amsterdam", "name": "NEMO Science Museum"}
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{"index":{}}
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{"location": "POINT(491.4722 5237.1667)", "city": "Amsterdam", "name": "Nederlands Scheepvaartmuseum"}
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{"index":{}}
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{"location": "POINT(488.394 5237.52)", "city": "Amsterdam", "name": "Anne Frank House"}
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{"index":{}}
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{"location": "POINT(440.5200 5122.2900)", "city": "Antwerp", "name": "Letterenhuis"}
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{"index":{}}
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{"location": "POINT(233.6389 4886.1111)", "city": "Paris", "name": "Musée du Louvre"}
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{"index":{}}
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{"location": "POINT(232.7000 4886.0000)", "city": "Paris", "name": "Musée dOrsay"}
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- do:
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indices.create:
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index: shapes
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body:
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mappings:
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properties:
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shape:
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type: shape
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category:
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type: keyword
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name:
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type: keyword
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- do:
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bulk:
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refresh: true
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index: shapes
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body: |
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{"index":{}}
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{"shape": "POINT(488.9187 5237.3184)", "category": "points", "name": "Royal Palace Amsterdam"}
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{"index":{}}
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{"shape": "POINT(488.5057 5237.0159)", "category": "points", "name": "The Amsterdam Dungeon"}
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{"index":{}}
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{"shape": "POINT(490.1618 5236.9219)", "category": "points", "name": "Museum Het Rembrandthuis"}
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{"index":{}}
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{"shape": "POINT(491.2350 5237.4081)", "category": "points", "name": "NEMO Science Museum"}
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{"index":{}}
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{"shape": "POINT(491.4722 5237.1667)", "category": "points", "name": "Nederlands Scheepvaartmuseum"}
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{"index":{}}
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{"shape": "POINT(488.394 5237.52)", "category": "points", "name": "Anne Frank House"}
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{"index":{}}
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{"shape": "LINESTRING(491.4722 5237.1667, 488.9187 5237.3184)", "category": "linestrings", "name": "Path of: Nederlands Scheepvaartmuseum, Royal Palace Amsterdam"}
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{"index":{}}
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{"shape": "LINESTRING(490.1618 5236.9219, 491.2350 5237.4081, 491.4722 5237.1667)", "category": "linestrings", "name": "Path of: Museum Het Rembrandthuis, NEMO Science Museum, Nederlands Scheepvaartmuseum"}
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{"index":{}}
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{"shape": "LINESTRING(488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.2350 5237.4081, 491.4722 5237.1667)", "category": "linestrings", "name": "Path of: Royal Palace Amsterdam, The Amsterdam Dungeon, Museum Het Rembrandthuis, NEMO Science Museum, Nederlands Scheepvaartmuseum"}
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{"index":{}}
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{"shape": "POLYGON((488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.4722 5237.1667, 491.2350 5237.4081, 488.9187 5237.3184))", "category": "polygons", "name": "Area of: Royal Palace Amsterdam, The Amsterdam Dungeon, Museum Het Rembrandthuis, Nederlands Scheepvaartmuseum, NEMO Science Museum"}
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{"index":{}}
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{"shape": "POLYGON((488.35 5237.50, 488.44 5237.50, 488.44 5237.54, 488.35 5237.54, 488.35 5237.50))", "category": "polygons", "name": "Box around: Anne Frank House"}
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{"index":{}}
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{"shape": "MULTIPOLYGON(((488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.4722 5237.1667, 491.2350 5237.4081, 488.9187 5237.3184)), ((488.35 5237.50, 488.44 5237.50, 488.44 5237.54, 488.35 5237.54, 488.35 5237.50)))", "category": "multipolygons", "name": "Two areas"}
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{"index":{}}
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{"shape": "GEOMETRYCOLLECTION(POINT(488.394 5237.52), LINESTRING(488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.2350 5237.4081, 491.4722 5237.1667), POLYGON((488.35 5237.50, 488.44 5237.50, 488.44 5237.54, 488.35 5237.54, 488.35 5237.50)), MULTIPOLYGON(((488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.4722 5237.1667, 491.2350 5237.4081, 488.9187 5237.3184)), ((488.35 5237.50, 488.44 5237.50, 488.44 5237.54, 488.35 5237.54, 488.35 5237.50))))", "category": "collections", "name": "Collection of point, line, polygon and multipolygon"}
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{"index":{}}
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{"shape": "GEOMETRYCOLLECTION(POINT(488.394 5237.52), LINESTRING(488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.2350 5237.4081, 491.4722 5237.1667), POLYGON((488.35 5237.50, 488.44 5237.50, 488.44 5237.54, 488.35 5237.54, 488.35 5237.50)))", "category": "collections", "name": "Collection of point, line and polygon"}
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{"index":{}}
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{"shape": "GEOMETRYCOLLECTION(POINT(488.394 5237.52), LINESTRING(488.9187 5237.3184, 488.5057 5237.0159, 490.1618 5236.9219, 491.2350 5237.4081, 491.4722 5237.1667))", "category": "collections", "name": "Collection of point and line"}
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{"index":{}}
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{"shape": "GEOMETRYCOLLECTION(POINT(488.394 5237.52))", "category": "collections", "name": "Collection of one point"}
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{"index":{}}
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{"shape": "GEOMETRYCOLLECTION(POINT(488.394 5237.52), POINT(488.9187 5237.3184))", "category": "collections", "name": "Collection of two points"}
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- do:
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indices.refresh: { }
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---
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"Test cartesian_centroid aggregation on cartesian shape points":
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- do:
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search:
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rest_total_hits_as_int: true
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index: locations
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size: 0
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body:
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aggs:
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centroid:
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cartesian_centroid:
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field: location
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- match: { hits.total: 9 }
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- match: { aggregations.centroid.count: 9 }
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- close_to: { aggregations.centroid.location.x: { value: 427.2829, error: 0.0001 } }
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- close_to: { aggregations.centroid.location.y: { value: 5146.4169, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape shapes":
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- do:
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search:
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rest_total_hits_as_int: true
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index: shapes
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size: 0
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body:
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aggs:
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centroid:
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cartesian_centroid:
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field: shape
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- match: { hits.total: 17 }
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- match: { aggregations.centroid.count: 17 }
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- close_to: { aggregations.centroid.location.x: { value: 490.0065, error: 0.0001 } }
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- close_to: { aggregations.centroid.location.y: { value: 5237.1722, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape points with filter":
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- do:
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search:
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rest_total_hits_as_int: true
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index: locations
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size: 0
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body:
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query:
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term:
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city: "Amsterdam"
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aggs:
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centroid:
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cartesian_centroid:
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field: location
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- match: { hits.total: 6 }
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- match: { aggregations.centroid.count: 6 }
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- close_to: { aggregations.centroid.location.x: { value: 489.7812, error: 0.0001 } }
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- close_to: { aggregations.centroid.location.y: { value: 5237.2252, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape shapes with filter":
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- do:
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search:
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rest_total_hits_as_int: true
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index: shapes
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size: 0
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body:
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query:
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term:
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category: "points"
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aggs:
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centroid:
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cartesian_centroid:
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field: shape
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- match: { hits.total: 6 }
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- match: { aggregations.centroid.count: 6 }
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- close_to: { aggregations.centroid.location.x: { value: 489.7812, error: 0.0001 } }
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- close_to: { aggregations.centroid.location.y: { value: 5237.2252, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape points with grouping":
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- do:
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search:
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rest_total_hits_as_int: true
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index: locations
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size: 0
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body:
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aggs:
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cities:
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terms:
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field: "city"
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aggs:
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centroid:
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cartesian_centroid:
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field: location
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- match: { hits.total: 9 }
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- length: { aggregations.cities.buckets: 3 }
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- match: { aggregations.cities.buckets.0.key: "Amsterdam" }
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- match: { aggregations.cities.buckets.0.doc_count: 6 }
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- match: { aggregations.cities.buckets.0.centroid.count: 6 }
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- close_to: { aggregations.cities.buckets.0.centroid.location.x: { value: 489.7812, error: 0.0001 } }
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- close_to: { aggregations.cities.buckets.0.centroid.location.y: { value: 5237.2252, error: 0.0001 } }
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- match: { aggregations.cities.buckets.1.key: "Paris" }
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- match: { aggregations.cities.buckets.1.doc_count: 2 }
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- match: { aggregations.cities.buckets.1.centroid.count: 2 }
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- close_to: { aggregations.cities.buckets.1.centroid.location.x: { value: 233.1694, error: 0.0001 } }
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- close_to: { aggregations.cities.buckets.1.centroid.location.y: { value: 4886.0557, error: 0.0001 } }
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- match: { aggregations.cities.buckets.2.key: "Antwerp" }
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- match: { aggregations.cities.buckets.2.doc_count: 1 }
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- match: { aggregations.cities.buckets.2.centroid.count: 1 }
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- close_to: { aggregations.cities.buckets.2.centroid.location.x: { value: 440.5200, error: 0.0001 } }
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- close_to: { aggregations.cities.buckets.2.centroid.location.y: { value: 5122.2900, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape shapes with grouping":
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- do:
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search:
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rest_total_hits_as_int: true
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index: shapes
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size: 0
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body:
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aggs:
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categories:
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terms:
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field: "category"
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aggs:
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centroid:
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cartesian_centroid:
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field: shape
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- match: { hits.total: 17 }
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- length: { aggregations.categories.buckets: 5 }
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- match: { aggregations.categories.buckets.0.key: "points" }
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- match: { aggregations.categories.buckets.0.doc_count: 6 }
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- match: { aggregations.categories.buckets.0.centroid.count: 6 }
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- close_to: { aggregations.categories.buckets.0.centroid.location.x: { value: 489.7812, error: 0.0001 } }
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- close_to: { aggregations.categories.buckets.0.centroid.location.y: { value: 5237.2252, error: 0.0001 } }
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- match: { aggregations.categories.buckets.1.key: "collections" }
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- match: { aggregations.categories.buckets.1.doc_count: 5 }
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- match: { aggregations.categories.buckets.1.centroid.count: 5 }
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- close_to: { aggregations.categories.buckets.1.centroid.location.x: { value: 489.9987, error: 0.0001 } }
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- close_to: { aggregations.categories.buckets.1.centroid.location.y: { value: 5237.1741, error: 0.0001 } }
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- match: { aggregations.categories.buckets.2.key: "linestrings" }
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- match: { aggregations.categories.buckets.2.doc_count: 3 }
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- match: { aggregations.categories.buckets.2.centroid.count: 3 }
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- close_to: { aggregations.categories.buckets.2.centroid.location.x: { value: 490.1672, error: 0.0001 } }
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- close_to: { aggregations.categories.buckets.2.centroid.location.y: { value: 5237.1595, error: 0.0001 } }
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- match: { aggregations.categories.buckets.3.key: "polygons" }
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- match: { aggregations.categories.buckets.3.doc_count: 2 }
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- match: { aggregations.categories.buckets.3.centroid.count: 2 }
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- close_to: { aggregations.categories.buckets.3.centroid.location.x: { value: 490.0105, error: 0.0001 } }
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- close_to: { aggregations.categories.buckets.3.centroid.location.y: { value: 5237.1712, error: 0.0001 } }
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- match: { aggregations.categories.buckets.4.key: "multipolygons" }
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- match: { aggregations.categories.buckets.4.doc_count: 1 }
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- match: { aggregations.categories.buckets.4.centroid.count: 1 }
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- close_to: { aggregations.categories.buckets.4.centroid.location.x: { value: 490.0105, error: 0.0001 } }
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- close_to: { aggregations.categories.buckets.4.centroid.location.y: { value: 5237.1714, error: 0.0001 } }
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---
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"Test cartesian_centroid aggregation on cartesian shape shapes with grouping and filter":
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- do:
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search:
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rest_total_hits_as_int: true
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index: shapes
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size: 0
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body:
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query:
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term:
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category: "collections"
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aggs:
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names:
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terms:
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field: "name"
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order:
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_key: "asc"
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aggs:
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centroid:
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cartesian_centroid:
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field: shape
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- match: { hits.total: 5 }
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- length: { aggregations.names.buckets: 5 }
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- match: { aggregations.names.buckets.0.key: "Collection of one point" }
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- match: { aggregations.names.buckets.0.doc_count: 1 }
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- match: { aggregations.names.buckets.0.centroid.count: 1 }
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- close_to: { aggregations.names.buckets.0.centroid.location.x: { value: 488.394, error: 0.0001 } }
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- close_to: { aggregations.names.buckets.0.centroid.location.y: { value: 5237.5200, error: 0.0001 } }
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- match: { aggregations.names.buckets.1.key: "Collection of point and line" }
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- match: { aggregations.names.buckets.1.doc_count: 1 }
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- match: { aggregations.names.buckets.1.centroid.count: 1 }
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- close_to: { aggregations.names.buckets.1.centroid.location.x: { value: 489.86888, error: 0.0001 } }
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- close_to: { aggregations.names.buckets.1.centroid.location.y: { value: 5237.0883, error: 0.0001 } }
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- match: { aggregations.names.buckets.2.key: "Collection of point, line and polygon" }
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- match: { aggregations.names.buckets.2.doc_count: 1 }
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- match: { aggregations.names.buckets.2.centroid.count: 1 }
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- close_to: { aggregations.names.buckets.2.centroid.location.x: { value: 488.395, error: 0.0001 } }
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- close_to: { aggregations.names.buckets.2.centroid.location.y: { value: 5237.5201, error: 0.0001 } }
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- match: { aggregations.names.buckets.3.key: "Collection of point, line, polygon and multipolygon" }
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- match: { aggregations.names.buckets.3.doc_count: 1 }
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- match: { aggregations.names.buckets.3.centroid.count: 1 }
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- close_to: { aggregations.names.buckets.3.centroid.location.x: { value: 490.0046, error: 0.0001 } }
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- close_to: { aggregations.names.buckets.3.centroid.location.y: { value: 5237.1729, error: 0.0001 } }
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- match: { aggregations.names.buckets.4.key: "Collection of two points" }
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- match: { aggregations.names.buckets.4.doc_count: 1 }
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- match: { aggregations.names.buckets.4.centroid.count: 1 }
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- close_to: { aggregations.names.buckets.4.centroid.location.x: { value: 488.6563, error: 0.0001 } }
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- close_to: { aggregations.names.buckets.4.centroid.location.y: { value: 5237.4194, error: 0.0001 } }

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