Filter Results Inside a Rectangle

Dataset

The dataset contains 3000+ of the biggest airports in the world.

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[
 {
    "objectID": "3797",
    "name": "John F Kennedy Intl",
    "city": "New York",
    "country": "United States",
    "iata_code": "JFK",
    "_geoloc": {
      "lat": 40.639751,
      "lng": -73.778925
    },
    "links_count": 911
  }
]

To tell Algolia where each record is located, we need to have the latitude and longitude stored in the _geoloc attribute.

You can download the dataset here. Have look at how to import it in Algolia here

Initialize the client

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// composer autoload
require __DIR__ . '/vendor/autoload.php';

// if you are not using composer
// require_once 'path/to/algoliasearch.php';

$client = \Algolia\AlgoliaSearch\SearchClient::create(
  'YourApplicationID',
  'YourAdminAPIKey'
);

$index = $client->initIndex('your_index_name');

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// for the default version
const algoliasearch = require('algoliasearch');

// for the default version
import algoliasearch from 'algoliasearch';

// for the search only version
import algoliasearch from 'algoliasearch/lite';

// or just use algoliasearch if you are using a <script> tag
// if you are using AMD module loader, algoliasearch will not be defined in window,
// but in the AMD modules of the page

const client = algoliasearch('YourApplicationID', 'YourAdminAPIKey');
const index = client.initIndex('your_index_name');

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from algoliasearch.search_client import SearchClient

client = SearchClient.create('YourApplicationID', 'YourAdminAPIKey')
index = client.init_index('your_index_name')

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package main

import "github.com/algolia/algoliasearch-client-go/v3/algolia/search"

func main() {
  client := search.NewClient("YourApplicationID", "YourAdminAPIKey")
  index := client.InitIndex("your_index_name")
}

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val client = ClientSearch(
    applicationID = ApplicationID("YourApplicationID"),
    apiKey = APIKey("YourAdminAPIKey")
)
val indexName = IndexName("your_index_name")

client.initIndex(indexName)

Configure Index Settings

Even if we want to sort by distance to a location we need the textual relevance to be good in case refine the search with a query.

First, let’s configure the index.

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$index->setSettings({
  'searchableAttributes' => [
    'name',
    'city',
    'country',
    'iata_code'
  ],
  'customRanking': [
    'desc(links_count)'
  ]
});

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index.set_settings(
  searchableAttributes: [
    'name',
    'city',
    'country',
    'iata_code'
  ],
  customRanking: [
    'desc(links_count)'
  ]
)

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index.setSettings({
  searchableAttributes: ['name', 'city', 'country', 'iata_code'],
  customRanking: ['desc(links_count)']
}).then(() => {
  // done
});

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index.setSettings(new IndexSettings()
    .setSearchableAttributes(Arrays.asList("name", "city", "country", "iata_code"))
    .setCustomRanking(Collections.singletonList("desc(links_count"))
);

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res, err := index.SetSettings(search.Settings{
  SearchableAttributes: opt.SearchableAttributes(
    "name",
    "city",
    "country",
    "iata_code",
  ),
  CustomRanking: opt.CustomRanking("desc(links_count)"),
})

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val settings = settings {
    searchableAttributes {
        +"name"
        +"city"
        +"country"
        +"iata_code"
    }
    customRanking {
        +Desc("links_count")
    }
}

index.setSettings(settings)

Searchable attributes

We’re going to search in our 4 textual attributes: name, city, country and iata_code.

Custom Ranking

We’ll use the number of other connected airports to any airport as a ranking metric. The more connection the better.

Filtering inside a rectangle area

Let’s filter inside the United State of America. The USA can be considered as a rectangle:

To filter inside this rectangle we need the upper-left and bottom-right latitude and longitude:

49.067996905313834, 65.73828125
25.905859247243498, 128.8046875

We are going to use the insideBoundingBox parameter:

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$boundingBox = [
  49.067996905313834, // p1Lat
  65.73828125, // p1Lng
  25.905859247243498, // p2Lat
  128.8046875 // p2Lng
];

$results = $index->search('', [
  'insideBoundingBox' => [$boundingBox]
]);

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bounding_box = [
  49.067996905313834, # p1Lat
  65.73828125,        # p1Lng
  25.905859247243498, # p2Lat
  128.8046875         # p2Lng
]

results = index.search('', { insideBoundingBox: [ bounding_box ] })

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const boundingBox = [
  49.067996905313834, // p1Lat
  65.73828125, // p1Lng
  25.905859247243498, // p2Lat
  128.8046875 // p2Lng
];

index.search('', {
  insideBoundingBox: [boundingBox]
}).then(({ hits }) => {
  console.log(hits);
});

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index.search(new Query().setInsideBoundingBox(
          Collections.singletonList(Arrays.asList(
            49.067996905313834f, // p1Lat
            65.73828125f, // p1Lng
            25.905859247243498f, // p2Lat
            128.8046875f // p2Lng
  ))));
);

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boundingBox := [][4]float64{
  {
    49.067996905313834, // p1Lat
    65.73828125,        // p1Lng
    25.905859247243498, // p2Lat
    128.8046875,        // p2Lng
  },
}

res, err := index.Search("", opt.InsideBoundingBox(boundingBox))

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val query = query {
    insideBoundingBox {
        +BoundingBox(
            Point(49.067996905313834f, 65.73828125f),
            Point(25.905859247243498f, 128.8046875f)
        )
    }
}

index.search(query)

We are using the empty query ('') to tell that we want all airports.

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Filter Results Inside a Rectangle

On this page

Dataset

Initialize the client

Configure Index Settings

Searchable attributes

Custom Ranking

Filtering inside a rectangle area

On this page