Kueri geografis

Banyak aplikasi memiliki dokumen yang diindeks berdasarkan lokasi fisik. Misalnya, aplikasi Anda mungkin mengizinkan pengguna untuk mencari toko yang dekat dengan lokasi mereka saat ini.

Solusi: Geohash

Geohash adalah sistem untuk mengenkode pasangan (latitude, longitude) menjadi string Base32 tunggal. Dalam sistem Geohash, dunia dibagi menjadi petak-petak persegi panjang. Setiap karakter string Geohash menentukan salah satu dari 32 subdivisi hash awalan. Misalnya, abcd Geohash adalah salah satu dari 32 hash empat karakter yang sepenuhnya terdapat dalam abc Geohash yang lebih besar.

Makin panjang awalan yang sama pada dua hash, makin berdekatan kedua hash tersebut satu sama lain. Misalnya, abcdef lebih dekat ke abcdeg daripada abcdff. Namun, tidak demikian dengan yang sebaliknya. Dua area bisa sangat berdekatan satu sama lain tetapi memiliki Geohash yang sangat berbeda:

Kita dapat menggunakan Geohash untuk menyimpan dan membuat kueri dokumen berdasarkan posisi di Cloud Firestore dengan cukup efisien dan hanya memerlukan satu kolom terindeks.

Menginstal library helper

Membuat dan mengurai Geohash memerlukan perhitungan matematika yang rumit, jadi kami membuat library helper untuk memisahkan bagian yang paling sulit di Android, Apple, dan Web:

Web

// Install from NPM. If you prefer to use a static .js file visit
// https://github.com/firebase/geofire-js/releases and download
// geofire-common.min.js from the latest version
npm install --save geofire-common

Web

// Install from NPM. If you prefer to use a static .js file visit
// https://github.com/firebase/geofire-js/releases and download
// geofire-common.min.js from the latest version
npm install --save geofire-common

Swift

Catatan: Produk ini tidak tersedia di target watchOS dan App Clip.

// Add this to your Podfile pod 'GeoFire/Utils'

Kotlin

// Add this to your app/build.gradle
implementation 'com.firebase:geofire-android-common:3.2.0'

Java

// Add this to your app/build.gradle
implementation 'com.firebase:geofire-android-common:3.1.0'

Menyimpan Geohash

Untuk setiap dokumen yang ingin diindeks berdasarkan lokasi, Anda harus menyimpan kolom Geohash:

Web

import { doc, updateDoc } from 'firebase/firestore';

// Compute the GeoHash for a lat/lng point
const lat = 51.5074;
const lng = 0.1278;
const hash = geofire.geohashForLocation([lat, lng]);

// Add the hash and the lat/lng to the document. We will use the hash
// for queries and the lat/lng for distance comparisons.
const londonRef = doc(db, 'cities', 'LON');
await updateDoc(londonRef, {
  geohash: hash,
  lat: lat,
  lng: lng
});
fs_geo_add_hash.js

Web

// Compute the GeoHash for a lat/lng point
const lat = 51.5074;
const lng = 0.1278;
const hash = geofire.geohashForLocation([lat, lng]);

// Add the hash and the lat/lng to the document. We will use the hash
// for queries and the lat/lng for distance comparisons.
const londonRef = db.collection('cities').doc('LON');
londonRef.update({
  geohash: hash,
  lat: lat,
  lng: lng
}).then(() => {
  // ...
});
test.solution-geoqueries.js

Swift

Catatan: Produk ini tidak tersedia di target watchOS dan App Clip.

// Compute the GeoHash for a lat/lng point
let latitude = 51.5074
let longitude = 0.12780
let location = CLLocationCoordinate2D(latitude: latitude, longitude: longitude)

let hash = GFUtils.geoHash(forLocation: location)

// Add the hash and the lat/lng to the document. We will use the hash
// for queries and the lat/lng for distance comparisons.
let documentData: [String: Any] = [
  "geohash": hash,
  "lat": latitude,
  "lng": longitude
]

let londonRef = db.collection("cities").document("LON")
londonRef.updateData(documentData) { error in
  // ...
}
SolutionGeoPointViewController.swift

Kotlin

// Compute the GeoHash for a lat/lng point
val lat = 51.5074
val lng = 0.1278
val hash = GeoFireUtils.getGeoHashForLocation(GeoLocation(lat, lng))

// Add the hash and the lat/lng to the document. We will use the hash
// for queries and the lat/lng for distance comparisons.
val updates: MutableMap<String, Any> = mutableMapOf(
    "geohash" to hash,
    "lat" to lat,
    "lng" to lng,
)
val londonRef = db.collection("cities").document("LON")
londonRef.update(updates)
    .addOnCompleteListener {
        // ...
    }
SolutionGeoqueries.kt

Java

// Compute the GeoHash for a lat/lng point
double lat = 51.5074;
double lng = 0.1278;
String hash = GeoFireUtils.getGeoHashForLocation(new GeoLocation(lat, lng));

// Add the hash and the lat/lng to the document. We will use the hash
// for queries and the lat/lng for distance comparisons.
Map<String, Object> updates = new HashMap<>();
updates.put("geohash", hash);
updates.put("lat", lat);
updates.put("lng", lng);

DocumentReference londonRef = db.collection("cities").document("LON");
londonRef.update(updates)
        .addOnCompleteListener(new OnCompleteListener<Void>() {
            @Override
            public void onComplete(@NonNull Task<Void> task) {
                // ...
            }
        });
SolutionGeoqueries.java

Membuat kueri Geohash

Geohash memungkinkan kita untuk memperkirakan kueri area dengan menggabungkan sekumpulan kueri di kolom Geohash, lalu memfilter dan menyingkirkan beberapa positif palsu (PP):

Web

import { collection, query, orderBy, startAt, endAt, getDocs } from 'firebase/firestore';

// Find cities within 50km of London
const center = [51.5074, 0.1278];
const radiusInM = 50 * 1000;

// Each item in 'bounds' represents a startAt/endAt pair. We have to issue
// a separate query for each pair. There can be up to 9 pairs of bounds
// depending on overlap, but in most cases there are 4.
const bounds = geofire.geohashQueryBounds(center, radiusInM);
const promises = [];
for (const b of bounds) {
  const q = query(
    collection(db, 'cities'), 
    orderBy('geohash'), 
    startAt(b[0]), 
    endAt(b[1]));

  promises.push(getDocs(q));
}

// Collect all the query results together into a single list
const snapshots = await Promise.all(promises);

const matchingDocs = [];
for (const snap of snapshots) {
  for (const doc of snap.docs) {
    const lat = doc.get('lat');
    const lng = doc.get('lng');

    // We have to filter out a few false positives due to GeoHash
    // accuracy, but most will match
    const distanceInKm = geofire.distanceBetween([lat, lng], center);
    const distanceInM = distanceInKm * 1000;
    if (distanceInM <= radiusInM) {
      matchingDocs.push(doc);
    }
  }
}
fs_geo_query_hashes.js

Web

// Find cities within 50km of London
const center = [51.5074, 0.1278];
const radiusInM = 50 * 1000;

// Each item in 'bounds' represents a startAt/endAt pair. We have to issue
// a separate query for each pair. There can be up to 9 pairs of bounds
// depending on overlap, but in most cases there are 4.
const bounds = geofire.geohashQueryBounds(center, radiusInM);
const promises = [];
for (const b of bounds) {
  const q = db.collection('cities')
    .orderBy('geohash')
    .startAt(b[0])
    .endAt(b[1]);

  promises.push(q.get());
}

// Collect all the query results together into a single list
Promise.all(promises).then((snapshots) => {
  const matchingDocs = [];

  for (const snap of snapshots) {
    for (const doc of snap.docs) {
      const lat = doc.get('lat');
      const lng = doc.get('lng');

      // We have to filter out a few false positives due to GeoHash
      // accuracy, but most will match
      const distanceInKm = geofire.distanceBetween([lat, lng], center);
      const distanceInM = distanceInKm * 1000;
      if (distanceInM <= radiusInM) {
        matchingDocs.push(doc);
      }
    }
  }

  return matchingDocs;
}).then((matchingDocs) => {
  // Process the matching documents
  // ...
});
test.solution-geoqueries.js

Swift

Catatan: Produk ini tidak tersedia di target watchOS dan App Clip.

// Find cities within 50km of London
let center = CLLocationCoordinate2D(latitude: 51.5074, longitude: 0.1278)
let radiusInM: Double = 50 * 1000

// Each item in 'bounds' represents a startAt/endAt pair. We have to issue
// a separate query for each pair. There can be up to 9 pairs of bounds
// depending on overlap, but in most cases there are 4.
let queryBounds = GFUtils.queryBounds(forLocation: center,
                                      withRadius: radiusInM)
let queries = queryBounds.map { bound -> Query in
  return db.collection("cities")
    .order(by: "geohash")
    .start(at: [bound.startValue])
    .end(at: [bound.endValue])
}

@Sendable func fetchMatchingDocs(from query: Query,
                       center: CLLocationCoordinate2D,
                       radiusInMeters: Double) async throws -> [QueryDocumentSnapshot] {
  let snapshot = try await query.getDocuments()
  // Collect all the query results together into a single list
  return snapshot.documents.filter { document in
    let lat = document.data()["lat"] as? Double ?? 0
    let lng = document.data()["lng"] as? Double ?? 0
    let coordinates = CLLocation(latitude: lat, longitude: lng)
    let centerPoint = CLLocation(latitude: center.latitude, longitude: center.longitude)

    // We have to filter out a few false positives due to GeoHash accuracy, but
    // most will match
    let distance = GFUtils.distance(from: centerPoint, to: coordinates)
    return distance <= radiusInM
  }
}

// After all callbacks have executed, matchingDocs contains the result. Note that this code
// executes all queries serially, which may not be optimal for performance.
do {
  let matchingDocs = try await withThrowingTaskGroup(of: [QueryDocumentSnapshot].self) { group -> [QueryDocumentSnapshot] in
    for query in queries {
      group.addTask {
        try await fetchMatchingDocs(from: query, center: center, radiusInMeters: radiusInM)
      }
    }
    var matchingDocs = [QueryDocumentSnapshot]()
    for try await documents in group {
      matchingDocs.append(contentsOf: documents)
    }
    return matchingDocs
  }

  print("Docs matching geoquery: \(matchingDocs)")
} catch {
  print("Unable to fetch snapshot data. \(error)")
}
SolutionGeoPointViewController.swift

Kotlin

// Find cities within 50km of London
val center = GeoLocation(51.5074, 0.1278)
val radiusInM = 50.0 * 1000.0

// Each item in 'bounds' represents a startAt/endAt pair. We have to issue
// a separate query for each pair. There can be up to 9 pairs of bounds
// depending on overlap, but in most cases there are 4.
val bounds = GeoFireUtils.getGeoHashQueryBounds(center, radiusInM)
val tasks: MutableList<Task<QuerySnapshot>> = ArrayList()
for (b in bounds) {
    val q = db.collection("cities")
        .orderBy("geohash")
        .startAt(b.startHash)
        .endAt(b.endHash)
    tasks.add(q.get())
}

// Collect all the query results together into a single list
Tasks.whenAllComplete(tasks)
    .addOnCompleteListener {
        val matchingDocs: MutableList<DocumentSnapshot> = ArrayList()
        for (task in tasks) {
            val snap = task.result
            for (doc in snap!!.documents) {
                val lat = doc.getDouble("lat")!!
                val lng = doc.getDouble("lng")!!

                // We have to filter out a few false positives due to GeoHash
                // accuracy, but most will match
                val docLocation = GeoLocation(lat, lng)
                val distanceInM = GeoFireUtils.getDistanceBetween(docLocation, center)
                if (distanceInM <= radiusInM) {
                    matchingDocs.add(doc)
                }
            }
        }

        // matchingDocs contains the results
        // ...
    }
SolutionGeoqueries.kt

Java

// Find cities within 50km of London
final GeoLocation center = new GeoLocation(51.5074, 0.1278);
final double radiusInM = 50 * 1000;

// Each item in 'bounds' represents a startAt/endAt pair. We have to issue
// a separate query for each pair. There can be up to 9 pairs of bounds
// depending on overlap, but in most cases there are 4.
List<GeoQueryBounds> bounds = GeoFireUtils.getGeoHashQueryBounds(center, radiusInM);
final List<Task<QuerySnapshot>> tasks = new ArrayList<>();
for (GeoQueryBounds b : bounds) {
    Query q = db.collection("cities")
            .orderBy("geohash")
            .startAt(b.startHash)
            .endAt(b.endHash);

    tasks.add(q.get());
}

// Collect all the query results together into a single list
Tasks.whenAllComplete(tasks)
        .addOnCompleteListener(new OnCompleteListener<List<Task<?>>>() {
            @Override
            public void onComplete(@NonNull Task<List<Task<?>>> t) {
                List<DocumentSnapshot> matchingDocs = new ArrayList<>();

                for (Task<QuerySnapshot> task : tasks) {
                    QuerySnapshot snap = task.getResult();
                    for (DocumentSnapshot doc : snap.getDocuments()) {
                        double lat = doc.getDouble("lat");
                        double lng = doc.getDouble("lng");

                        // We have to filter out a few false positives due to GeoHash
                        // accuracy, but most will match
                        GeoLocation docLocation = new GeoLocation(lat, lng);
                        double distanceInM = GeoFireUtils.getDistanceBetween(docLocation, center);
                        if (distanceInM <= radiusInM) {
                            matchingDocs.add(doc);
                        }
                    }
                }

                // matchingDocs contains the results
                // ...
            }
        });
SolutionGeoqueries.java

Batasan

Menggunakan Geohash untuk membuat kueri lokasi memberi kita kemampuan baru, tetapi memiliki batasannya sendiri:

• Positif Palsu (PP) - kueri berdasarkan Geohash tidak tepat, dan Anda harus memfilter dan menyingkirkan hasil positif palsu (PP) di sisi klien. Pembacaan ekstra ini menambahkan biaya dan latensi ke aplikasi Anda.
• Kasus Khusus - metode kueri ini mengandalkan estimasi jarak antara garis bujur/lintang. Keakuratan estimasi ini menurun jika titiknya semakin dekat ke Kutub Utara atau Selatan, yang berarti kueri Geohash memiliki lebih banyak positif palsu (PP) di wilayah lintang yang ekstrem.