バケット集約 - ジオ距離（Geo-distance） - 《Elasticsearchガイドv8.15》日本語

地理距離集約
キー付きレスポンス

地理距離集約

geo_point フィールドで動作するマルチバケット集約で、概念的には range 集約と非常に似ています。ユーザーは起点と一連の距離範囲バケットを定義できます。集約は各ドキュメント値の起点からの距離を評価し、距離がバケットの範囲内に収まる場合、そのバケットに属するかどうかを判断します（ドキュメントと起点の距離がバケットの距離範囲内にある場合、ドキュメントはそのバケットに属します）。

Python

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",
   aggs={
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   {
   "to": 100000
   },
   {
   "from": 100000,
   "to": 300000
   },
   {
   "from": 300000
   }
   ]
   }
   }
   },
)
print(resp2)

Ruby

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: {
   aggregations: {
   rings_around_amsterdam: {
   geo_distance: {
   field: 'location',
   origin: 'POINT (4.894 52.3760)',
   ranges: [
   {
   to: 100_000
   },
   {
   from: 100_000,
   to: 300_000
   },
   {
   from: 300_000
   }
   ]
   }
   }
   }
  }
)
puts response

Js

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,
  aggs: {
   rings_around_amsterdam: {
   geo_distance: {
   field: "location",
   origin: "POINT (4.894 52.3760)",
   ranges: [
   {
   to: 100000,
   },
   {
   from: 100000,
   to: 300000,
   },
   {
   from: 300000,
   },
   ],
   },
   },
  },
});
console.log(response2);

コンソール

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
{
  "aggs": {
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   { "to": 100000 },
   { "from": 100000, "to": 300000 },
   { "from": 300000 }
   ]
   }
   }
  }
}

レスポンス:

コンソール-結果

{
  ...
  "aggregations": {
   "rings_around_amsterdam": {
   "buckets": [
   {
   "key": "*-100000.0",
   "from": 0.0,
   "to": 100000.0,
   "doc_count": 3
   },
   {
   "key": "100000.0-300000.0",
   "from": 100000.0,
   "to": 300000.0,
   "doc_count": 1
   },
   {
   "key": "300000.0-*",
   "from": 300000.0,
   "doc_count": 2
   }
   ]
   }
  }
}

指定されたフィールドは geo_point 型でなければなりません（これはマッピングで明示的に設定することができます）。また、geo_point フィールドの配列を保持することもでき、その場合、すべてが集約中に考慮されます。起点は geo_point 型によってサポートされるすべての形式を受け入れることができます:

オブジェクト形式: { "lat" : 52.3760, "lon" : 4.894 } - これは lat と lon の値について最も明示的で安全な形式です
文字列形式: "52.3760, 4.894" - 最初の数値が lat で、2番目が lon です
配列形式: [4.894, 52.3760] - これは GeoJSON 標準に基づいており、最初の数値が lon で、2番目が lat です

デフォルトでは、距離単位は m (メートル) ですが、次のものも受け入れられます: mi (マイル)、in (インチ)、yd (ヤード)、km (キロメートル)、cm (センチメートル)、mm (ミリメートル)。

Python

resp = client.search(
   index="museums",
   size="0",
   aggs={
   "rings": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "unit": "km",
   "ranges": [
   {
   "to": 100
   },
   {
   "from": 100,
   "to": 300
   },
   {
   "from": 300
   }
   ]
   }
   }
   },
)
print(resp)

Ruby

response = client.search(
  index: 'museums',
  size: 0,
  body: {
   aggregations: {
   rings: {
   geo_distance: {
   field: 'location',
   origin: 'POINT (4.894 52.3760)',
   unit: 'km',
   ranges: [
   {
   to: 100
   },
   {
   from: 100,
   to: 300
   },
   {
   from: 300
   }
   ]
   }
   }
   }
  }
)
puts response

Js

const response = await client.search({
  index: "museums",
  size: 0,
  aggs: {
   rings: {
   geo_distance: {
   field: "location",
   origin: "POINT (4.894 52.3760)",
   unit: "km",
   ranges: [
   {
   to: 100,
   },
   {
   from: 100,
   to: 300,
   },
   {
   from: 300,
   },
   ],
   },
   },
  },
});
console.log(response);

コンソール

POST /museums/_search?size=0
{
  "aggs": {
   "rings": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "unit": "km",
   "ranges": [
   { "to": 100 },
   { "from": 100, "to": 300 },
   { "from": 300 }
   ]
   }
   }
  }
}


	距離はキロメートルで計算されます

距離計算モードは2つあります: arc (デフォルト) と plane。arc 計算は最も正確です。plane は最も速いですが、最も正確ではありません。検索コンテキストが「狭い」場合（約5km）には plane を使用することを検討してください。plane は非常に大きな地域（例: 大陸を越える検索）での検索に対して高い誤差範囲を返します。距離計算タイプは distance_type パラメータを使用して設定できます:

Python

resp = client.search(
   index="museums",
   size="0",
   aggs={
   "rings": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "unit": "km",
   "distance_type": "plane",
   "ranges": [
   {
   "to": 100
   },
   {
   "from": 100,
   "to": 300
   },
   {
   "from": 300
   }
   ]
   }
   }
   },
)
print(resp)

Ruby

response = client.search(
  index: 'museums',
  size: 0,
  body: {
   aggregations: {
   rings: {
   geo_distance: {
   field: 'location',
   origin: 'POINT (4.894 52.3760)',
   unit: 'km',
   distance_type: 'plane',
   ranges: [
   {
   to: 100
   },
   {
   from: 100,
   to: 300
   },
   {
   from: 300
   }
   ]
   }
   }
   }
  }
)
puts response

Js

const response = await client.search({
  index: "museums",
  size: 0,
  aggs: {
   rings: {
   geo_distance: {
   field: "location",
   origin: "POINT (4.894 52.3760)",
   unit: "km",
   distance_type: "plane",
   ranges: [
   {
   to: 100,
   },
   {
   from: 100,
   to: 300,
   },
   {
   from: 300,
   },
   ],
   },
   },
  },
});
console.log(response);

コンソール

POST /museums/_search?size=0
{
  "aggs": {
   "rings": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "unit": "km",
   "distance_type": "plane",
   "ranges": [
   { "to": 100 },
   { "from": 100, "to": 300 },
   { "from": 300 }
   ]
   }
   }
  }
}

キー付きレスポンス

keyed フラグを true に設定すると、各バケットに一意の文字列キーが関連付けられ、範囲が配列ではなくハッシュとして返されます:

Python

resp = client.search(
   index="museums",
   size="0",
   aggs={
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   {
   "to": 100000
   },
   {
   "from": 100000,
   "to": 300000
   },
   {
   "from": 300000
   }
   ],
   "keyed": True
   }
   }
   },
)
print(resp)

Ruby

response = client.search(
  index: 'museums',
  size: 0,
  body: {
   aggregations: {
   rings_around_amsterdam: {
   geo_distance: {
   field: 'location',
   origin: 'POINT (4.894 52.3760)',
   ranges: [
   {
   to: 100_000
   },
   {
   from: 100_000,
   to: 300_000
   },
   {
   from: 300_000
   }
   ],
   keyed: true
   }
   }
   }
  }
)
puts response

Js

const response = await client.search({
  index: "museums",
  size: 0,
  aggs: {
   rings_around_amsterdam: {
   geo_distance: {
   field: "location",
   origin: "POINT (4.894 52.3760)",
   ranges: [
   {
   to: 100000,
   },
   {
   from: 100000,
   to: 300000,
   },
   {
   from: 300000,
   },
   ],
   keyed: true,
   },
   },
  },
});
console.log(response);

コンソール

POST /museums/_search?size=0
{
  "aggs": {
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   { "to": 100000 },
   { "from": 100000, "to": 300000 },
   { "from": 300000 }
   ],
   "keyed": true
   }
   }
  }
}

レスポンス:

コンソール-結果

{
  ...
  "aggregations": {
   "rings_around_amsterdam": {
   "buckets": {
   "*-100000.0": {
   "from": 0.0,
   "to": 100000.0,
   "doc_count": 3
   },
   "100000.0-300000.0": {
   "from": 100000.0,
   "to": 300000.0,
   "doc_count": 1
   },
   "300000.0-*": {
   "from": 300000.0,
   "doc_count": 2
   }
   }
   }
  }
}

各範囲のキーをカスタマイズすることも可能です:

Python

resp = client.search(
   index="museums",
   size="0",
   aggs={
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   {
   "to": 100000,
   "key": "first_ring"
   },
   {
   "from": 100000,
   "to": 300000,
   "key": "second_ring"
   },
   {
   "from": 300000,
   "key": "third_ring"
   }
   ],
   "keyed": True
   }
   }
   },
)
print(resp)

Ruby

response = client.search(
  index: 'museums',
  size: 0,
  body: {
   aggregations: {
   rings_around_amsterdam: {
   geo_distance: {
   field: 'location',
   origin: 'POINT (4.894 52.3760)',
   ranges: [
   {
   to: 100_000,
   key: 'first_ring'
   },
   {
   from: 100_000,
   to: 300_000,
   key: 'second_ring'
   },
   {
   from: 300_000,
   key: 'third_ring'
   }
   ],
   keyed: true
   }
   }
   }
  }
)
puts response

Js

const response = await client.search({
  index: "museums",
  size: 0,
  aggs: {
   rings_around_amsterdam: {
   geo_distance: {
   field: "location",
   origin: "POINT (4.894 52.3760)",
   ranges: [
   {
   to: 100000,
   key: "first_ring",
   },
   {
   from: 100000,
   to: 300000,
   key: "second_ring",
   },
   {
   from: 300000,
   key: "third_ring",
   },
   ],
   keyed: true,
   },
   },
  },
});
console.log(response);

コンソール

POST /museums/_search?size=0
{
  "aggs": {
   "rings_around_amsterdam": {
   "geo_distance": {
   "field": "location",
   "origin": "POINT (4.894 52.3760)",
   "ranges": [
   { "to": 100000, "key": "first_ring" },
   { "from": 100000, "to": 300000, "key": "second_ring" },
   { "from": 300000, "key": "third_ring" }
   ],
   "keyed": true
   }
   }
  }
}

レスポンス:

コンソール-結果

{
  ...
  "aggregations": {
   "rings_around_amsterdam": {
   "buckets": {
   "first_ring": {
   "from": 0.0,
   "to": 100000.0,
   "doc_count": 3
   },
   "second_ring": {
   "from": 100000.0,
   "to": 300000.0,
   "doc_count": 1
   },
   "third_ring": {
   "from": 300000.0,
   "doc_count": 2
   }
   }
   }
  }
}