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SQL: Add support for shape type (elastic#46464)
Enables support for Cartesian geometries shape type. We still need to decide how to handle the distance function since it is currently using the haversine distance formula and returns results in meters, which doesn't make any sense for Cartesian geometries. Closes elastic#46412 Relates to elastic#43644
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-115
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20 files changed

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-115
lines changed

‎docs/reference/sql/functions/geo.asciidoc

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -5,14 +5,15 @@
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beta[]
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8-
The geo functions work with geometries stored in `geo_point` and `geo_shape` fields, or returned by other geo functions.
8+
The geo functions work with geometries stored in `geo_point`, `geo_shape` and `shape` fields, or returned by other geo functions.
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==== Limitations
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Both <<geo-point, `geo_point`>> and <<geo-shape, `geo_shape`>> types are represented in SQL as geometry and can be used
13-
interchangeably with the following exceptions:
12+
<<geo-point, `geo_point`>>, <<geo-shape, `geo_shape`>> and <<shape, `shape`>> and types are represented in SQL as
13+
geometry and can be used interchangeably with the following exceptions:
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15-
* `geo_shape` fields don't have doc values, therefore these fields cannot be used for filtering, grouping or sorting.
15+
* `geo_shape` and `shape` fields don't have doc values, therefore these fields cannot be used for filtering, grouping
16+
or sorting.
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* `geo_points` fields are indexed and have doc values by default, however only latitude and longitude are stored and
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indexed with some loss of precision from the original values (4.190951585769653E-8 for the latitude and

‎docs/reference/sql/language/data-types.asciidoc

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@@ -83,6 +83,7 @@ s|SQL precision
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| interval_minute_to_second | 23
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| geo_point | 52
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| geo_shape | 2,147,483,647
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| shape | 2,147,483,647
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|===
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‎x-pack/plugin/sql/jdbc/src/main/java/org/elasticsearch/xpack/sql/jdbc/EsType.java

Lines changed: 3 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@
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import java.sql.Types;
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public enum EsType implements SQLType {
14-
14+
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NULL( Types.NULL),
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UNSUPPORTED( Types.OTHER),
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BOOLEAN( Types.BOOLEAN),
@@ -46,7 +46,8 @@ public enum EsType implements SQLType {
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INTERVAL_HOUR_TO_SECOND( ExtraTypes.INTERVAL_HOUR_SECOND),
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INTERVAL_MINUTE_TO_SECOND(ExtraTypes.INTERVAL_MINUTE_SECOND),
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GEO_POINT( ExtraTypes.GEOMETRY),
49-
GEO_SHAPE( ExtraTypes.GEOMETRY);
49+
GEO_SHAPE( ExtraTypes.GEOMETRY),
50+
SHAPE( ExtraTypes.GEOMETRY);
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private final Integer type;
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‎x-pack/plugin/sql/jdbc/src/main/java/org/elasticsearch/xpack/sql/jdbc/TypeConverter.java

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@@ -248,6 +248,7 @@ static Object convert(Object v, EsType columnType, String typeString) throws SQL
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return Duration.parse(v.toString());
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case GEO_POINT:
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case GEO_SHAPE:
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case SHAPE:
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try {
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return WKT.fromWKT(v.toString());
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} catch (IOException | ParseException ex) {

‎x-pack/plugin/sql/jdbc/src/main/java/org/elasticsearch/xpack/sql/jdbc/TypeUtils.java

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@@ -94,6 +94,7 @@ private TypeUtils() {}
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types.put(EsType.INTERVAL_MINUTE_TO_SECOND, Duration.class);
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types.put(EsType.GEO_POINT, String.class);
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types.put(EsType.GEO_SHAPE, String.class);
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types.put(EsType.SHAPE, String.class);
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TYPE_TO_CLASS = unmodifiableMap(types);
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‎x-pack/plugin/sql/qa/src/main/java/org/elasticsearch/xpack/sql/qa/geo/GeoDataLoader.java

Lines changed: 8 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -73,25 +73,25 @@ private static String createOGCIndexRequest() throws Exception {
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createString("name", createIndex);
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// Type specific
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createIndex.startObject("shore").field("type", "geo_shape").endObject(); // lakes
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createIndex.startObject("shore").field("type", "shape").endObject(); // lakes
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createString("aliases", createIndex); // road_segments
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createIndex.startObject("num_lanes").field("type", "integer").endObject(); // road_segments, divided_routes
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createIndex.startObject("centerline").field("type", "geo_shape").endObject(); // road_segments, streams
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createIndex.startObject("centerline").field("type", "shape").endObject(); // road_segments, streams
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createIndex.startObject("centerlines").field("type", "geo_shape").endObject(); // divided_routes
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createIndex.startObject("centerlines").field("type", "shape").endObject(); // divided_routes
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createIndex.startObject("boundary").field("type", "geo_shape").endObject(); // forests, named_places
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createIndex.startObject("boundary").field("type", "shape").endObject(); // forests, named_places
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createIndex.startObject("position").field("type", "geo_shape").endObject(); // bridges, buildings
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createIndex.startObject("position").field("type", "shape").endObject(); // bridges, buildings
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createString("address", createIndex); // buildings
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createIndex.startObject("footprint").field("type", "geo_shape").endObject(); // buildings
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createIndex.startObject("footprint").field("type", "shape").endObject(); // buildings
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createIndex.startObject("type").field("type", "keyword").endObject(); // ponds
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createIndex.startObject("shores").field("type", "geo_shape").endObject(); // ponds
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createIndex.startObject("shores").field("type", "shape").endObject(); // ponds
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createIndex.startObject("neatline").field("type", "geo_shape").endObject(); // map_neatlines
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createIndex.startObject("neatline").field("type", "shape").endObject(); // map_neatlines
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}
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createIndex.endObject();

‎x-pack/plugin/sql/qa/src/main/resources/geo/geo.csv

Lines changed: 16 additions & 16 deletions
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city,region,region_point,location,shape
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Mountain View,Americas,POINT(-105.2551 54.5260),POINT (-122.083843 37.386483),POINT (-122.083843 37.386483)
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Chicago,Americas,POINT(-105.2551 54.5260),POINT (-87.637874 41.888783),POINT (-87.637874 41.888783)
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New York,Americas,POINT(-105.2551 54.5260),POINT (-73.990027 40.745171),POINT (-73.990027 40.745171)
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San Francisco,Americas,POINT(-105.2551 54.5260),POINT (-122.394228 37.789541),POINT (-122.394228 37.789541)
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Phoenix,Americas,POINT(-105.2551 54.5260),POINT (-111.973505 33.376242),POINT (-111.973505 33.376242)
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Amsterdam,Europe,POINT(15.2551 54.5260),POINT (4.850312 52.347557),POINT (4.850312 52.347557)
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Berlin,Europe,POINT(15.2551 54.5260),POINT (13.390889 52.486701),POINT (13.390889 52.486701)
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Munich,Europe,POINT(15.2551 54.5260),POINT (11.537505 48.146321),POINT (11.537505 48.146321)
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London,Europe,POINT(15.2551 54.5260),POINT (-0.121672 51.510871),POINT (-0.121672 51.510871)
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Paris,Europe,POINT(15.2551 54.5260),POINT (2.351773 48.845538),POINT (2.351773 48.845538)
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Singapore,Asia,POINT(100.6197 34.0479),POINT (103.855535 1.295868),POINT (103.855535 1.295868)
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Hong Kong,Asia,POINT(100.6197 34.0479),POINT (114.183925 22.281397),POINT (114.183925 22.281397)
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Seoul,Asia,POINT(100.6197 34.0479),POINT (127.060851 37.509132),POINT (127.060851 37.509132)
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Tokyo,Asia,POINT(100.6197 34.0479),POINT (139.76402225 35.669616),POINT (139.76402225 35.669616)
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Sydney,Asia,POINT(100.6197 34.0479),POINT (151.208629 -33.863385),POINT (151.208629 -33.863385)
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city,region,region_point,location,geoshape,shape
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Mountain View,Americas,POINT(-105.2551 54.5260),POINT (-122.083843 37.386483),POINT (-122.083843 37.386483)),POINT (-122.083843 37.386483)
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Chicago,Americas,POINT(-105.2551 54.5260),POINT (-87.637874 41.888783),POINT (-87.637874 41.888783),POINT (-87.637874 41.888783)
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New York,Americas,POINT(-105.2551 54.5260),POINT (-73.990027 40.745171),POINT (-73.990027 40.745171),POINT (-73.990027 40.745171)
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San Francisco,Americas,POINT(-105.2551 54.5260),POINT (-122.394228 37.789541),POINT (-122.394228 37.789541),POINT (-122.394228 37.789541)
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Phoenix,Americas,POINT(-105.2551 54.5260),POINT (-111.973505 33.376242),POINT (-111.973505 33.376242),POINT (-111.973505 33.376242)
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Amsterdam,Europe,POINT(15.2551 54.5260),POINT (4.850312 52.347557),POINT (4.850312 52.347557),POINT (4.850312 52.347557)
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Berlin,Europe,POINT(15.2551 54.5260),POINT (13.390889 52.486701),POINT (13.390889 52.486701),POINT (13.390889 52.486701)
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Munich,Europe,POINT(15.2551 54.5260),POINT (11.537505 48.146321),POINT (11.537505 48.146321),POINT (11.537505 48.146321)
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London,Europe,POINT(15.2551 54.5260),POINT (-0.121672 51.510871),POINT (-0.121672 51.510871),POINT (-0.121672 51.510871)
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Paris,Europe,POINT(15.2551 54.5260),POINT (2.351773 48.845538),POINT (2.351773 48.845538),POINT (2.351773 48.845538)
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Singapore,Asia,POINT(100.6197 34.0479),POINT (103.855535 1.295868),POINT (103.855535 1.295868),POINT (103.855535 1.295868)
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Hong Kong,Asia,POINT(100.6197 34.0479),POINT (114.183925 22.281397),POINT (114.183925 22.281397),POINT (114.183925 22.281397)
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Seoul,Asia,POINT(100.6197 34.0479),POINT (127.060851 37.509132),POINT (127.060851 37.509132),POINT (127.060851 37.509132)
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Tokyo,Asia,POINT(100.6197 34.0479),POINT (139.76402225 35.669616),POINT (139.76402225 35.669616),POINT (139.76402225 35.669616)
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Sydney,Asia,POINT(100.6197 34.0479),POINT (151.208629 -33.863385),POINT (151.208629 -33.863385),POINT (151.208629 -33.863385)

‎x-pack/plugin/sql/qa/src/main/resources/geo/geosql-bulk.json

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@@ -1,33 +1,33 @@
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{"index":{"_id": "1"}}
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{"region": "Americas", "city": "Mountain View", "location": {"lat":"37.386483", "lon":"-122.083843"}, "location_no_dv": {"lat":"37.386483", "lon":"-122.083843"}, "shape": "POINT (-122.083843 37.386483 30)", "region_point": "POINT(-105.2551 54.5260)"}
2+
{"region": "Americas", "city": "Mountain View", "location": {"lat":"37.386483", "lon":"-122.083843"}, "location_no_dv": {"lat":"37.386483", "lon":"-122.083843"}, "geoshape": "POINT (-122.083843 37.386483 30)", "shape": "POINT (-122.083843 37.386483 30)", "region_point": "POINT(-105.2551 54.5260)"}
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{"index":{"_id": "2"}}
4-
{"region": "Americas", "city": "Chicago", "location": [-87.637874, 41.888783], "location_no_dv": [-87.637874, 41.888783], "shape": {"type" : "point", "coordinates" : [-87.637874, 41.888783, 181]}, "region_point": "POINT(-105.2551 54.5260)"}
4+
{"region": "Americas", "city": "Chicago", "location": [-87.637874, 41.888783], "location_no_dv": [-87.637874, 41.888783], "geoshape": {"type" : "point", "coordinates" : [-87.637874, 41.888783, 181]}, "shape": {"type" : "point", "coordinates" : [-87.637874, 41.888783, 181]}, "region_point": "POINT(-105.2551 54.5260)"}
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{"index":{"_id": "3"}}
6-
{"region": "Americas", "city": "New York", "location": "40.745171,-73.990027", "location_no_dv": "40.745171,-73.990027", "shape": "POINT (-73.990027 40.745171 10)", "region_point": "POINT(-105.2551 54.5260)"}
6+
{"region": "Americas", "city": "New York", "location": "40.745171,-73.990027", "location_no_dv": "40.745171,-73.990027", "geoshape": "POINT (-73.990027 40.745171 10)", "shape": "POINT (-73.990027 40.745171 10)", "region_point": "POINT(-105.2551 54.5260)"}
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{"index":{"_id": "4"}}
8-
{"region": "Americas", "city": "San Francisco", "location": "37.789541,-122.394228", "location_no_dv": "37.789541,-122.394228", "shape": "POINT (-122.394228 37.789541 16)", "region_point": "POINT(-105.2551 54.5260)"}
8+
{"region": "Americas", "city": "San Francisco", "location": "37.789541,-122.394228", "location_no_dv": "37.789541,-122.394228", "geoshape": "POINT (-122.394228 37.789541 16)", "shape": "POINT (-122.394228 37.789541 16)", "region_point": "POINT(-105.2551 54.5260)"}
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{"index":{"_id": "5"}}
10-
{"region": "Americas", "city": "Phoenix", "location": "33.376242,-111.973505", "location_no_dv": "33.376242,-111.973505", "shape": "POINT (-111.973505 33.376242 331)", "region_point": "POINT(-105.2551 54.5260)"}
10+
{"region": "Americas", "city": "Phoenix", "location": "33.376242,-111.973505", "location_no_dv": "33.376242,-111.973505", "geoshape": "POINT (-111.973505 33.376242 331)", "shape": "POINT (-111.973505 33.376242 331)", "region_point": "POINT(-105.2551 54.5260)"}
1111
{"index":{"_id": "6"}}
12-
{"region": "Europe", "city": "Amsterdam", "location": "52.347557,4.850312", "location_no_dv": "52.347557,4.850312", "shape": "POINT (4.850312 52.347557 2)", "region_point": "POINT(15.2551 54.5260)"}
12+
{"region": "Europe", "city": "Amsterdam", "location": "52.347557,4.850312", "location_no_dv": "52.347557,4.850312", "geoshape": "POINT (4.850312 52.347557 2)", "shape": "POINT (4.850312 52.347557 2)", "region_point": "POINT(15.2551 54.5260)"}
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{"index":{"_id": "7"}}
14-
{"region": "Europe", "city": "Berlin", "location": "52.486701,13.390889", "location_no_dv": "52.486701,13.390889", "shape": "POINT (13.390889 52.486701 34)", "region_point": "POINT(15.2551 54.5260)"}
14+
{"region": "Europe", "city": "Berlin", "location": "52.486701,13.390889", "location_no_dv": "52.486701,13.390889", "geoshape": "POINT (13.390889 52.486701 34)", "shape": "POINT (13.390889 52.486701 34)", "region_point": "POINT(15.2551 54.5260)"}
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{"index":{"_id": "8"}}
16-
{"region": "Europe", "city": "Munich", "location": "48.146321,11.537505", "location_no_dv": "48.146321,11.537505", "shape": "POINT (11.537505 48.146321 519)", "region_point": "POINT(15.2551 54.5260)"}
16+
{"region": "Europe", "city": "Munich", "location": "48.146321,11.537505", "location_no_dv": "48.146321,11.537505", "geoshape": "POINT (11.537505 48.146321 519)", "shape": "POINT (11.537505 48.146321 519)", "region_point": "POINT(15.2551 54.5260)"}
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{"index":{"_id": "9"}}
18-
{"region": "Europe", "city": "London", "location": "51.510871,-0.121672", "location_no_dv": "51.510871,-0.121672", "shape": "POINT (-0.121672 51.510871 11)", "region_point": "POINT(15.2551 54.5260)"}
18+
{"region": "Europe", "city": "London", "location": "51.510871,-0.121672", "location_no_dv": "51.510871,-0.121672", "geoshape": "POINT (-0.121672 51.510871 11)", "shape": "POINT (-0.121672 51.510871 11)", "region_point": "POINT(15.2551 54.5260)"}
1919
{"index":{"_id": "10"}}
20-
{"region": "Europe", "city": "Paris", "location": "48.845538,2.351773", "location_no_dv": "48.845538,2.351773", "shape": "POINT (2.351773 48.845538 35)", "region_point": "POINT(15.2551 54.5260)"}
20+
{"region": "Europe", "city": "Paris", "location": "48.845538,2.351773", "location_no_dv": "48.845538,2.351773", "geoshape": "POINT (2.351773 48.845538 35)", "shape": "POINT (2.351773 48.845538 35)", "region_point": "POINT(15.2551 54.5260)"}
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{"index":{"_id": "11"}}
22-
{"region": "Asia", "city": "Singapore", "location": "1.295868,103.855535", "location_no_dv": "1.295868,103.855535", "shape": "POINT (103.855535 1.295868 15)", "region_point": "POINT(100.6197 34.0479)"}
22+
{"region": "Asia", "city": "Singapore", "location": "1.295868,103.855535", "location_no_dv": "1.295868,103.855535", "geoshape": "POINT (103.855535 1.295868 15)", "shape": "POINT (103.855535 1.295868 15)", "region_point": "POINT(100.6197 34.0479)"}
2323
{"index":{"_id": "12"}}
24-
{"region": "Asia", "city": "Hong Kong", "location": "22.281397,114.183925", "location_no_dv": "22.281397,114.183925", "shape": "POINT (114.183925 22.281397 552)", "region_point": "POINT(100.6197 34.0479)"}
24+
{"region": "Asia", "city": "Hong Kong", "location": "22.281397,114.183925", "location_no_dv": "22.281397,114.183925", "geoshape": "POINT (114.183925 22.281397 552)", "shape": "POINT (114.183925 22.281397 552)", "region_point": "POINT(100.6197 34.0479)"}
2525
{"index":{"_id": "13"}}
26-
{"region": "Asia", "city": "Seoul", "location": "37.509132,127.060851", "location_no_dv": "37.509132,127.060851", "shape": "POINT (127.060851 37.509132 38)", "region_point": "POINT(100.6197 34.0479)"}
26+
{"region": "Asia", "city": "Seoul", "location": "37.509132,127.060851", "location_no_dv": "37.509132,127.060851", "geoshape": "POINT (127.060851 37.509132 38)", "shape": "POINT (127.060851 37.509132 38)", "region_point": "POINT(100.6197 34.0479)"}
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{"index":{"_id": "14"}}
28-
{"region": "Asia", "city": "Tokyo", "location": "35.669616,139.76402225", "location_no_dv": "35.669616,139.76402225", "shape": "POINT (139.76402225 35.669616 40)", "region_point": "POINT(100.6197 34.0479)"}
28+
{"region": "Asia", "city": "Tokyo", "location": "35.669616,139.76402225", "location_no_dv": "35.669616,139.76402225", "geoshape": "POINT (139.76402225 35.669616 40)", "shape": "POINT (139.76402225 35.669616 40)", "region_point": "POINT(100.6197 34.0479)"}
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{"index":{"_id": "15"}}
30-
{"region": "Asia", "city": "Sydney", "location": "-33.863385,151.208629", "location_no_dv": "-33.863385,151.208629", "shape": "POINT (151.208629 -33.863385 100)", "region_point": "POINT(100.6197 34.0479)"}
30+
{"region": "Asia", "city": "Sydney", "location": "-33.863385,151.208629", "location_no_dv": "-33.863385,151.208629", "geoshape": "POINT (151.208629 -33.863385 100)", "shape": "POINT (151.208629 -33.863385 100)", "region_point": "POINT(100.6197 34.0479)"}
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