地理边界聚合
编辑地理边界聚合
编辑一种度量聚合，用于计算包含 Geopoint 或 Geoshape 字段所有值的地理边界框。
示例
resp = client.indices.create(
index="museums",
mappings={
"properties": {
"location": {
"type": "geo_point"
}
}
},
)
print(resp)
resp1 = client.bulk(
index="museums",
refresh=True,
operations=[
{
"index": {
"_id": 1
}
},
{
"location": "POINT (4.912350 52.374081)",
"name": "NEMO Science Museum"
},
{
"index": {
"_id": 2
}
},
{
"location": "POINT (4.901618 52.369219)",
"name": "Museum Het Rembrandthuis"
},
{
"index": {
"_id": 3
}
},
{
"location": "POINT (4.914722 52.371667)",
"name": "Nederlands Scheepvaartmuseum"
},
{
"index": {
"_id": 4
}
},
{
"location": "POINT (4.405200 51.222900)",
"name": "Letterenhuis"
},
{
"index": {
"_id": 5
}
},
{
"location": "POINT (2.336389 48.861111)",
"name": "Musée du Louvre"
},
{
"index": {
"_id": 6
}
},
{
"location": "POINT (2.327000 48.860000)",
"name": "Musée d'Orsay"
}
],
)
print(resp1)
resp2 = client.search(
index="museums",
size="0",
query={
"match": {
"name": "musée"
}
},
aggs={
"viewport": {
"geo_bounds": {
"field": "location",
"wrap_longitude": True
}
}
},
)
print(resp2)
response = client.indices.create(
index: 'museums',
body: {
mappings: {
properties: {
location: {
type: 'geo_point'
}
}
}
}
)
puts response
response = client.bulk(
index: 'museums',
refresh: true,
body: [
{
index: {
_id: 1
}
},
{
location: 'POINT (4.912350 52.374081)',
name: 'NEMO Science Museum'
},
{
index: {
_id: 2
}
},
{
location: 'POINT (4.901618 52.369219)',
name: 'Museum Het Rembrandthuis'
},
{
index: {
_id: 3
}
},
{
location: 'POINT (4.914722 52.371667)',
name: 'Nederlands Scheepvaartmuseum'
},
{
index: {
_id: 4
}
},
{
location: 'POINT (4.405200 51.222900)',
name: 'Letterenhuis'
},
{
index: {
_id: 5
}
},
{
location: 'POINT (2.336389 48.861111)',
name: 'Musée du Louvre'
},
{
index: {
_id: 6
}
},
{
location: 'POINT (2.327000 48.860000)',
name: "Musée d'Orsay"
}
]
)
puts response
response = client.search(
index: 'museums',
size: 0,
body: {
query: {
match: {
name: 'musée'
}
},
aggregations: {
viewport: {
geo_bounds: {
field: 'location',
wrap_longitude: true
}
}
}
}
)
puts response
const response = await client.indices.create({
index: "museums",
mappings: {
properties: {
location: {
type: "geo_point",
},
},
},
});
console.log(response);
const response1 = await client.bulk({
index: "museums",
refresh: "true",
operations: [
{
index: {
_id: 1,
},
},
{
location: "POINT (4.912350 52.374081)",
name: "NEMO Science Museum",
},
{
index: {
_id: 2,
},
},
{
location: "POINT (4.901618 52.369219)",
name: "Museum Het Rembrandthuis",
},
{
index: {
_id: 3,
},
},
{
location: "POINT (4.914722 52.371667)",
name: "Nederlands Scheepvaartmuseum",
},
{
index: {
_id: 4,
},
},
{
location: "POINT (4.405200 51.222900)",
name: "Letterenhuis",
},
{
index: {
_id: 5,
},
},
{
location: "POINT (2.336389 48.861111)",
name: "Musée du Louvre",
},
{
index: {
_id: 6,
},
},
{
location: "POINT (2.327000 48.860000)",
name: "Musée d'Orsay",
},
],
});
console.log(response1);
const response2 = await client.search({
index: "museums",
size: 0,
query: {
match: {
name: "musée",
},
},
aggs: {
viewport: {
geo_bounds: {
field: "location",
wrap_longitude: true,
},
},
},
});
console.log(response2);
PUT /museums
{
"mappings": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
POST /museums/_bulk?refresh
{"index":{"_id":1}}
{"location": "POINT (4.912350 52.374081)", "name": "NEMO Science Museum"}
{"index":{"_id":2}}
{"location": "POINT (4.901618 52.369219)", "name": "Museum Het Rembrandthuis"}
{"index":{"_id":3}}
{"location": "POINT (4.914722 52.371667)", "name": "Nederlands Scheepvaartmuseum"}
{"index":{"_id":4}}
{"location": "POINT (4.405200 51.222900)", "name": "Letterenhuis"}
{"index":{"_id":5}}
{"location": "POINT (2.336389 48.861111)", "name": "Musée du Louvre"}
{"index":{"_id":6}}
{"location": "POINT (2.327000 48.860000)", "name": "Musée d'Orsay"}
POST /museums/_search?size=0
{
"query": {
"match": { "name": "musée" }
},
"aggs": {
"viewport": {
"geo_bounds": {
"field": "location",
"wrap_longitude": true
}
}
}
}
上述聚合演示了如何计算所有名称匹配“musée”的文档的 location 字段的边界框。
上述聚合的响应
{
...
"aggregations": {
"viewport": {
"bounds": {
"top_left": {
"lat": 48.86111099738628,
"lon": 2.3269999679178
},
"bottom_right": {
"lat": 48.85999997612089,
"lon": 2.3363889567553997
}
}
}
}
}
在 geo_shape 字段上的地理边界聚合
编辑地理边界聚合也支持 geo_shape 字段。
如果 wrap_longitude 设置为 true（默认值），则边界框可以与国际日期变更线重叠，并返回一个边界，其中 top_left 经度大于 top_right 经度。
例如，地理边界框的右上经度通常大于左下经度。但是，当区域跨越 180° 子午线时，左下经度的值将大于右上经度的值。有关更多信息，请参阅开放地理空间联盟网站上的 地理边界框。
示例
resp = client.indices.create(
index="places",
mappings={
"properties": {
"geometry": {
"type": "geo_shape"
}
}
},
)
print(resp)
resp1 = client.bulk(
index="places",
refresh=True,
operations=[
{
"index": {
"_id": 1
}
},
{
"name": "NEMO Science Museum",
"geometry": "POINT(4.912350 52.374081)"
},
{
"index": {
"_id": 2
}
},
{
"name": "Sportpark De Weeren",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
4.965305328369141,
52.39347642069457
],
[
4.966979026794433,
52.391721758934835
],
[
4.969425201416015,
52.39238958618537
],
[
4.967944622039794,
52.39420969150824
],
[
4.965305328369141,
52.39347642069457
]
]
]
}
}
],
)
print(resp1)
resp2 = client.search(
index="places",
size="0",
aggs={
"viewport": {
"geo_bounds": {
"field": "geometry"
}
}
},
)
print(resp2)
response = client.indices.create(
index: 'places',
body: {
mappings: {
properties: {
geometry: {
type: 'geo_shape'
}
}
}
}
)
puts response
response = client.bulk(
index: 'places',
refresh: true,
body: [
{
index: {
_id: 1
}
},
{
name: 'NEMO Science Museum',
geometry: 'POINT(4.912350 52.374081)'
},
{
index: {
_id: 2
}
},
{
name: 'Sportpark De Weeren',
geometry: {
type: 'Polygon',
coordinates: [
[
[
4.965305328369141,
52.39347642069457
],
[
4.966979026794433,
52.391721758934835
],
[
4.969425201416015,
52.39238958618537
],
[
4.967944622039794,
52.39420969150824
],
[
4.965305328369141,
52.39347642069457
]
]
]
}
}
]
)
puts response
response = client.search(
index: 'places',
size: 0,
body: {
aggregations: {
viewport: {
geo_bounds: {
field: 'geometry'
}
}
}
}
)
puts response
const response = await client.indices.create({
index: "places",
mappings: {
properties: {
geometry: {
type: "geo_shape",
},
},
},
});
console.log(response);
const response1 = await client.bulk({
index: "places",
refresh: "true",
operations: [
{
index: {
_id: 1,
},
},
{
name: "NEMO Science Museum",
geometry: "POINT(4.912350 52.374081)",
},
{
index: {
_id: 2,
},
},
{
name: "Sportpark De Weeren",
geometry: {
type: "Polygon",
coordinates: [
[
[4.965305328369141, 52.39347642069457],
[4.966979026794433, 52.391721758934835],
[4.969425201416015, 52.39238958618537],
[4.967944622039794, 52.39420969150824],
[4.965305328369141, 52.39347642069457],
],
],
},
},
],
});
console.log(response1);
const response2 = await client.search({
index: "places",
size: 0,
aggs: {
viewport: {
geo_bounds: {
field: "geometry",
},
},
},
});
console.log(response2);
PUT /places
{
"mappings": {
"properties": {
"geometry": {
"type": "geo_shape"
}
}
}
}
POST /places/_bulk?refresh
{"index":{"_id":1}}
{"name": "NEMO Science Museum", "geometry": "POINT(4.912350 52.374081)" }
{"index":{"_id":2}}
{"name": "Sportpark De Weeren", "geometry": { "type": "Polygon", "coordinates": [ [ [ 4.965305328369141, 52.39347642069457 ], [ 4.966979026794433, 52.391721758934835 ], [ 4.969425201416015, 52.39238958618537 ], [ 4.967944622039794, 52.39420969150824 ], [ 4.965305328369141, 52.39347642069457 ] ] ] } }
POST /places/_search?size=0
{
"aggs": {
"viewport": {
"geo_bounds": {
"field": "geometry"
}
}
}
}
{
...
"aggregations": {
"viewport": {
"bounds": {
"top_left": {
"lat": 52.39420966710895,
"lon": 4.912349972873926
},
"bottom_right": {
"lat": 52.374080987647176,
"lon": 4.969425117596984
}
}
}
}
}