Envelope Query
A GeoJSON Envelope Query against any GeoJSON type.
QueryShape for an Envelope Query
A GeoJSON query via a GeoShape of Envelope to find GeoJSON types in a Search index using the 3 relations intersects, contains, and within.
Also called a bounded rectangle query by specifying [[minLon, maxLat], [maxLon, minLat]]. This is a Couchbase extension to GeoJSON.
Envelope Intersects
Query
An intersect
query for the envelope returns all the matched documents with shapes that overlap with the area of the rectangle shape in the query.
A envelope intersection
query sample is given below.
{
"query": {
"field": "<<fieldName>>",
"geometry": {
"shape": {
"type": "Envelope",
"coordinates": [
[-2.235143, 53.482358],
[28.955043, 40.991862]
]
},
"relation": "intersects"
}
}
}
Intersection rules for the Envelope Query with other indexed GeoJSON shapes in the document set are given below.
Intersects (relation) |
|
Point |
Matches if the point lies within the query rectangle region. |
LineString |
Matches if the linestring intersects or lies within the query rectangle. |
Polygon |
Matches if the polygon area is overlapping the query rectangle. |
MultiPoint |
Matches if any of the points in the array lie within the rectangle region. |
MultiLineString |
Matches if any of the linestrings intersect or lie within the rectangle area. |
MultiPolygon |
Matches if any of the polygon areas is overlapping the rectangle region. |
GeometryCollection |
Matches if there is an overlap between any heterogeneous (above 6) shapes in the geometrycollection array in the document and the query rectangle. |
Circle |
Matches if the area of the query rectangle overlaps the document circle. |
Envelope |
Matches if the query rectangle overlaps the document rectangle area. |
Envelope Contains
Query
A contains
query for the envelope returns all the matched documents with shapes that contain the area of the rectangle shape in the query.
A envelope contains
query sample is given below.
{
"query": {
"field": "<<fieldName>>",
"geometry": {
"shape": {
"type": "Polygon",
"coordinates": [
[-2.235143, 53.482358],
[28.955043, 40.991862]
]
},
"relation": "contains"
}
}
}
Containment rules for the Envelope Query with other indexed GeoJSON shapes in the document set are given below.
Contains (relation) |
|
Point |
NA, Point can’t contain an envelope. |
LineString |
NA, LineString can’t contain an envelope. |
Polygon |
Matches if the polygon area is containing the rectangle region in the query. |
MultiPoint |
NA, MultiPoint can’t contain an envelope. |
MultiLineString |
NA, MultiLineString can’t contain an envelope. |
MultiPolygon |
Matches if any of the polygon areas contains the entire rectangle region. |
GeometryCollection |
Matches if there is a containment between any heterogeneous (above 6) shapes in the geometrycollection array in the document and the query rectangle. |
Circle |
Matches if the query rectangle resides within the document circle. |
Envelope |
Matches if the query rectangle resides within the document rectangle. |
Envelope WithIn
Query
The Within query is not supported by line geometries.
A within
query for the envelope returns all the matched documents with shapes that are contained within the area of the rectangle shape in the query.
A envelope contains
query sample is given below.
{
"query": {
"field": "<<fieldName>>",
"geometry": {
"shape": {
"type": "Polygon",
"coordinates": [
[-2.235143, 53.482358],
[28.955043, 40.991862]
]
},
"relation": "within"
}
}
}
WithIn rules for the Envelope Query with other indexed GeoJSON shapes in the document set are given below.
Contains (relation) |
|
Point |
Matches if the point lies within the query rectangle region. |
LineString |
Matches if the linestring resides completely within the query rectangle. |
Polygon |
Matches if the polygon resides completely within the query rectangle. |
MultiPoint |
Matches if all the points in the array lie within the query rectangle. |
MultiLineString |
Matches if all the linestrings lie within the query rectangle area. |
MultiPolygon |
Matches if all the polygons reside within the query rectangle region. |
GeometryCollection |
Matches if there is within relation between all the heterogeneous (above 6) shapes in the geometrycollection array in the document and the query rectangle. |
Circle |
Matches if the document circle resides within the query rectangle. |
Envelope |
Matches if the document rectangle resides within the query rectangle. |
Example Envelope Query (against Points)
It is assumed that you your cluster has 1) a modified travel-sample with GeoJSON data and 2) a Search index as per Creating a GeoJSON Index via the REST API prior to running this example. |
Matches if the point lies within the query rectangle region.
The results are specified to be sorted on name
. Note type hotel and landmark have a name field and type airport has an airportname field all these values are analyzed as a keyword (exposed as name
).
curl -s -XPOST -H "Content-Type: application/json" \
-u ${CB_USERNAME}:${CB_PASSWORD} http://${CB_HOSTNAME}:8094/api/index/test_geojson/query \
-d '{
"query": {
"field": "geojson",
"geometry": {
"shape": {
"type": "Envelope",
"coordinates": [
[-2.235143, 53.482358],
[28.955043, 40.991862]
]
},
"relation": "within"
}
},
"size": 5,
"from": 0,
"sort": ["name"]
}' | jq .
The output of five (5) hits (from a total of 2024 matching docs) is as follows
{
"status": {
"total": 1,
"failed": 0,
"successful": 1
},
"request": {
"query": {
"geometry": {
"shape": {
"type": "Envelope",
"coordinates": [
[
-2.235143,
53.482358
],
[
28.955043,
40.991862
]
]
},
"relation": "within"
},
"field": "geojson"
},
"size": 5,
"from": 0,
"highlight": null,
"fields": null,
"facets": null,
"explain": false,
"sort": [
"name"
],
"includeLocations": false,
"search_after": null,
"search_before": null
},
"hits": [
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "hotel_1364",
"score": 0.05896334942635901,
"sort": [
"'La Mirande Hotel"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "landmark_16144",
"score": 0.004703467956838207,
"sort": [
"02 Shepherd's Bush Empire"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "landmark_16181",
"score": 0.004703467956838207,
"sort": [
"2 Willow Road"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "landmark_16079",
"score": 0.004703467956838207,
"sort": [
"20 Fenchurch Street"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "landmark_40437",
"score": 0.004703467956838207,
"sort": [
"30 St. Mary Axe"
]
}
],
"total_hits": 2024,
"max_score": 0.12470500060351324,
"took": 17259514,
"facets": null
}
Example Envelope Query (against Circles)
It is assumed that you your cluster has 1) a modified travel-sample with GeoJSON data and 2) a Search index as per Creating a GeoJSON Index via the REST API prior to running this example. |
Matches if the area of the query rectangle overlaps the document circle.
The results are specified to be sorted on name
. Note type hotel and landmark have a name field and type airport has an airportname field all these values are analyzed as a keyword (exposed as name
).
curl -s -XPOST -H "Content-Type: application/json" \
-u ${CB_USERNAME}:${CB_PASSWORD} http://${CB_HOSTNAME}:8094/api/index/test_geojson/query \
-d '{
"query": {
"field": "geoarea",
"geometry": {
"shape": {
"type": "Envelope",
"coordinates": [
[-2.235143, 53.482358],
[28.955043, 40.991862]
]
},
"relation": "intersects"
}
},
"size": 5,
"from": 0,
"sort": ["name"]
}' | jq .
The output of five (5) hits (from a total of 293 matching docs) is as follows
{
"status": {
"total": 1,
"failed": 0,
"successful": 1
},
"request": {
"query": {
"geometry": {
"shape": {
"type": "Envelope",
"coordinates": [
[
-2.235143,
53.482358
],
[
28.955043,
40.991862
]
]
},
"relation": "intersects"
},
"field": "geoarea"
},
"size": 5,
"from": 0,
"highlight": null,
"fields": null,
"facets": null,
"explain": false,
"sort": [
"name"
],
"includeLocations": false,
"search_after": null,
"search_before": null
},
"hits": [
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "airport_1372",
"score": 0.008758192642105457,
"sort": [
"Abbeville"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "airport_1294",
"score": 0.07778849955604289,
"sort": [
"Aire Sur L Adour"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "airport_1329",
"score": 0.009493654411662942,
"sort": [
"Aix Les Bains"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "airport_1347",
"score": 0.06002598189280991,
"sort": [
"Aix Les Milles"
]
},
{
"index": "test_geojson_3397081757afba65_4c1c5584",
"id": "airport_8588",
"score": 0.010149143194537646,
"sort": [
"All Airports"
]
}
],
"total_hits": 293,
"max_score": 0.4253566663133814,
"took": 13358586,
"facets": null
}