写入时聚合

Cloud Firestore 中的查询可让您查找大型集合中的文档。如需从整体上深入了解相关集合的属性，您可以对集合进行数据聚合。

您可以在读取或写入时聚合数据：

读取时聚合在请求时计算结果。Cloud Firestore 支持在读取时运行 count()、sum() 和 average() 聚合查询。读取时聚合查询比写入时聚合查询更容易添加到应用中。如需详细了解聚合查询，请参阅使用聚合查询聚合数据。
写入时聚合在应用每次执行相关写入操作时计算结果。写入时聚合需要执行更多工作，但您可能会出于以下某个原因而需要使用写入时聚合，而不是读取时聚合：
- 您想要监听聚合结果以获取实时更新。count()、sum() 和 average() 聚合查询不支持实时更新。
- 您希望将聚合结果存储在客户端缓存中。count()、sum() 和 average() 聚合查询不支持缓存。
- 您要聚合每个用户的数以万计的文档中的数据，并且要考虑费用。文档数量较少时，读取时聚合的费用较低。聚合涉及大量文档时，写入时聚合的费用可能较低。

您可以使用客户端事务或 Cloud Functions 实现写入时聚合。以下部分介绍了如何实现写入时聚合。

解决方案：使用客户端事务实现写入时聚合

假设有一个帮助用户寻找人气餐厅的本地推荐类应用。以下查询会检索指定餐厅的所有评分：

Web

db.collection("restaurants")
  .doc("arinell-pizza")
  .collection("ratings")
  .get();test.solution-aggregation.js

Swift

注意：此产品不适用于 watchOS 和 App Clip 目标。

do {
  let snapshot = try await db.collection("restaurants")
    .document("arinell-pizza")
    .collection("ratings")
    .getDocuments()
  print(snapshot)
} catch {
  print(error)
}SolutionAggregationViewController.swift

Objective-C

注意：此产品不适用于 watchOS 和 App Clip 目标。

FIRQuery *query = [[[self.db collectionWithPath:@"restaurants"]
    documentWithPath:@"arinell-pizza"] collectionWithPath:@"ratings"];
[query getDocumentsWithCompletion:^(FIRQuerySnapshot * _Nullable snapshot,
                                    NSError * _Nullable error) {
  // ...
}];FIRSolutionAggregationViewController.m

Kotlin+KTX

db.collection("restaurants")
    .document("arinell-pizza")
    .collection("ratings")
    .get()SolutionAggregation.kt

Java

db.collection("restaurants")
        .document("arinell-pizza")
        .collection("ratings")
        .get();SolutionAggregation.java

我们无需提取所有评分再计算聚合信息，而是可以将这些信息存储在这家餐厅的文档中：

Web

var arinellDoc = {
  name: 'Arinell Pizza',
  avgRating: 4.65,
  numRatings: 683
};test.solution-aggregation.js

Swift

注意：此产品不适用于 watchOS 和 App Clip 目标。

struct Restaurant {

  let name: String
  let avgRating: Float
  let numRatings: Int

}

let arinell = Restaurant(name: "Arinell Pizza", avgRating: 4.65, numRatings: 683)SolutionAggregationViewController.swift

Objective-C

注意：此产品不适用于 watchOS 和 App Clip 目标。

@interface FIRRestaurant : NSObject

@property (nonatomic, readonly) NSString *name;
@property (nonatomic, readonly) float averageRating;
@property (nonatomic, readonly) NSInteger ratingCount;

- (instancetype)initWithName:(NSString *)name
               averageRating:(float)averageRating
                 ratingCount:(NSInteger)ratingCount;

@end

@implementation FIRRestaurant

- (instancetype)initWithName:(NSString *)name
               averageRating:(float)averageRating
                 ratingCount:(NSInteger)ratingCount {
  self = [super init];
  if (self != nil) {
    _name = name;
    _averageRating = averageRating;
    _ratingCount = ratingCount;
  }
  return self;
}

@endFIRSolutionAggregationViewController.m

Kotlin+KTX

data class Restaurant(
    // default values required for use with "toObject"
    internal var name: String = "",
    internal var avgRating: Double = 0.0,
    internal var numRatings: Int = 0,
)

val arinell = Restaurant("Arinell Pizza", 4.65, 683)SolutionAggregation.kt

Java

public class Restaurant {
    String name;
    double avgRating;
    int numRatings;

    public Restaurant(String name, double avgRating, int numRatings) {
        this.name = name;
        this.avgRating = avgRating;
        this.numRatings = numRatings;
    }
}

Restaurant arinell = new Restaurant("Arinell Pizza", 4.65, 683);SolutionAggregation.java

为了保持这些聚合数据的一致性，每当有新的评分添加到子集合时，都必须对数据进行更新。实现一致性的一种方法是在单个事务中执行添加和更新操作：

Web

function addRating(restaurantRef, rating) {
    // Create a reference for a new rating, for use inside the transaction
    var ratingRef = restaurantRef.collection('ratings').doc();

    // In a transaction, add the new rating and update the aggregate totals
    return db.runTransaction((transaction) => {
        return transaction.get(restaurantRef).then((res) => {
            if (!res.exists) {
                throw "Document does not exist!";
            }

            // Compute new number of ratings
            var newNumRatings = res.data().numRatings + 1;

            // Compute new average rating
            var oldRatingTotal = res.data().avgRating * res.data().numRatings;
            var newAvgRating = (oldRatingTotal + rating) / newNumRatings;

            // Commit to Firestore
            transaction.update(restaurantRef, {
                numRatings: newNumRatings,
                avgRating: newAvgRating
            });
            transaction.set(ratingRef, { rating: rating });
        });
    });
}test.firestore.js

Swift

注意：此产品不适用于 watchOS 和 App Clip 目标。

func addRatingTransaction(restaurantRef: DocumentReference, rating: Float) async {
  let ratingRef: DocumentReference = restaurantRef.collection("ratings").document()

  do {
    let _ = try await db.runTransaction({ (transaction, errorPointer) -> Any? in
      do {
        let restaurantDocument = try transaction.getDocument(restaurantRef).data()
        guard var restaurantData = restaurantDocument else { return nil }

        // Compute new number of ratings
        let numRatings = restaurantData["numRatings"] as! Int
        let newNumRatings = numRatings + 1

        // Compute new average rating
        let avgRating = restaurantData["avgRating"] as! Float
        let oldRatingTotal = avgRating * Float(numRatings)
        let newAvgRating = (oldRatingTotal + rating) / Float(newNumRatings)

        // Set new restaurant info
        restaurantData["numRatings"] = newNumRatings
        restaurantData["avgRating"] = newAvgRating

        // Commit to Firestore
        transaction.setData(restaurantData, forDocument: restaurantRef)
        transaction.setData(["rating": rating], forDocument: ratingRef)
      } catch {
        // Error getting restaurant data
        // ...
      }

      return nil
    })
  } catch {
    // ...
  }
}SolutionAggregationViewController.swift

Objective-C

注意：此产品不适用于 watchOS 和 App Clip 目标。

- (void)addRatingTransactionWithRestaurantReference:(FIRDocumentReference *)restaurant
                                             rating:(float)rating {
  FIRDocumentReference *ratingReference =
      [[restaurant collectionWithPath:@"ratings"] documentWithAutoID];

  [self.db runTransactionWithBlock:^id (FIRTransaction *transaction,
                                        NSError **errorPointer) {
    FIRDocumentSnapshot *restaurantSnapshot =
        [transaction getDocument:restaurant error:errorPointer];

    if (restaurantSnapshot == nil) {
      return nil;
    }

    NSMutableDictionary *restaurantData = [restaurantSnapshot.data mutableCopy];
    if (restaurantData == nil) {
      return nil;
    }

    // Compute new number of ratings
    NSInteger ratingCount = [restaurantData[@"numRatings"] integerValue];
    NSInteger newRatingCount = ratingCount + 1;

    // Compute new average rating
    float averageRating = [restaurantData[@"avgRating"] floatValue];
    float newAverageRating = (averageRating * ratingCount + rating) / newRatingCount;

    // Set new restaurant info

    restaurantData[@"numRatings"] = @(newRatingCount);
    restaurantData[@"avgRating"] = @(newAverageRating);

    // Commit to Firestore
    [transaction setData:restaurantData forDocument:restaurant];
    [transaction setData:@{@"rating": @(rating)} forDocument:ratingReference];
    return nil;
  } completion:^(id  _Nullable result, NSError * _Nullable error) {
    // ...
  }];
}FIRSolutionAggregationViewController.m

Kotlin+KTX

private fun addRating(restaurantRef: DocumentReference, rating: Float): Task<Void> {
    // Create reference for new rating, for use inside the transaction
    val ratingRef = restaurantRef.collection("ratings").document()

    // In a transaction, add the new rating and update the aggregate totals
    return db.runTransaction { transaction ->
        val restaurant = transaction.get(restaurantRef).toObject<Restaurant>()!!

        // Compute new number of ratings
        val newNumRatings = restaurant.numRatings + 1

        // Compute new average rating
        val oldRatingTotal = restaurant.avgRating * restaurant.numRatings
        val newAvgRating = (oldRatingTotal + rating) / newNumRatings

        // Set new restaurant info
        restaurant.numRatings = newNumRatings
        restaurant.avgRating = newAvgRating

        // Update restaurant
        transaction.set(restaurantRef, restaurant)

        // Update rating
        val data = hashMapOf<String, Any>(
            "rating" to rating,
        )
        transaction.set(ratingRef, data, SetOptions.merge())

        null
    }
}SolutionAggregation.kt

Java

private Task<Void> addRating(final DocumentReference restaurantRef, final float rating) {
    // Create reference for new rating, for use inside the transaction
    final DocumentReference ratingRef = restaurantRef.collection("ratings").document();

    // In a transaction, add the new rating and update the aggregate totals
    return db.runTransaction(new Transaction.Function<Void>() {
        @Override
        public Void apply(@NonNull Transaction transaction) throws FirebaseFirestoreException {
            Restaurant restaurant = transaction.get(restaurantRef).toObject(Restaurant.class);

            // Compute new number of ratings
            int newNumRatings = restaurant.numRatings + 1;

            // Compute new average rating
            double oldRatingTotal = restaurant.avgRating * restaurant.numRatings;
            double newAvgRating = (oldRatingTotal + rating) / newNumRatings;

            // Set new restaurant info
            restaurant.numRatings = newNumRatings;
            restaurant.avgRating = newAvgRating;

            // Update restaurant
            transaction.set(restaurantRef, restaurant);

            // Update rating
            Map<String, Object> data = new HashMap<>();
            data.put("rating", rating);
            transaction.set(ratingRef, data, SetOptions.merge());

            return null;
        }
    });
}SolutionAggregation.java

利用事务让您的聚合数据与底层集合保持一致。如需详细了解 Cloud Firestore 中的事务，请参阅事务和批量写入。

限制

上述解决方案演示了如何使用 Cloud Firestore 客户端库聚合数据，但请注意以下限制：

安全性 - 客户端事务要求授予客户端更新数据库中聚合数据的权限。虽然您可以通过编写高级安全规则来降低此方法的风险，但安全规则并非在所有情况下都适用。
离线支持 - 如果用户的设备离线，客户端事务将失败，这意味着您需要在自己的应用中处理这种情况，并在适当的时候重试。
性能 - 如果事务包含多个读取、写入和更新操作，则可能需要多次对 Cloud Firestore 后端提出请求。在移动设备上，可能需要很长时间才能完成事务。
写入速率 - 此解决方案可能不适用于频繁更新的聚合，因为 Cloud Firestore 文档每秒最多只能更新一次。此外，如果某个事务读取在该事务之外修改的文档，则它会重试一定次数，然后失败。对于需要更频繁地更新的聚合，请参阅分布式计数器了解相关的临时解决方法。

解决方案：使用 Cloud Functions 实现写入时聚合

如果客户端事务不适合您的应用，您可以使用 Cloud Functions 函数，在每次有新的评分添加到餐厅时更新聚合信息：

Node.js

exports.aggregateRatings = functions.firestore
    .document('restaurants/{restId}/ratings/{ratingId}')
    .onWrite(async (change, context) => {
      // Get value of the newly added rating
      const ratingVal = change.after.data().rating;

      // Get a reference to the restaurant
      const restRef = db.collection('restaurants').doc(context.params.restId);

      // Update aggregations in a transaction
      await db.runTransaction(async (transaction) => {
        const restDoc = await transaction.get(restRef);

        // Compute new number of ratings
        const newNumRatings = restDoc.data().numRatings + 1;

        // Compute new average rating
        const oldRatingTotal = restDoc.data().avgRating * restDoc.data().numRatings;
        const newAvgRating = (oldRatingTotal + ratingVal) / newNumRatings;

        // Update restaurant info
        transaction.update(restRef, {
          avgRating: newAvgRating,
          numRatings: newNumRatings
        });
      });
    });index.js

该解决方案将客户端的工作分流到一个托管函数中，这意味着您的移动应用无需等待事务完成即可添加评分。在 Cloud Function 中执行的代码不受安全规则约束，这意味着您无需再为客户端提供写入聚合数据的权限。

限制

使用 Cloud Functions 函数进行聚合可以避免客户端事务存在的一些问题，但也有其他限制：

费用 - 添加的每个评分都将引发一次 Cloud Functions 函数调用，这可能会增加费用。有关详细信息，请参阅 Cloud Functions 的价格页面。
延迟 - 如果将聚合工作分流到某个 Cloud Functions 函数，则直到该 Cloud Functions 函数执行完毕并且客户端收到有关新数据的通知后，您的应用才会看到更新后的数据。这一过程可能比在本地执行事务所需的时间更长，具体取决于您的 Cloud Functions 函数的执行速度。
写入速率 - 此解决方案可能不适用于频繁更新的聚合，因为 Cloud Firestore 文档每秒最多只能更新一次。此外，如果某个事务读取在该事务之外修改的文档，则它会重试一定次数，然后失败。对于需要更频繁地更新的聚合，请参阅分布式计数器了解相关的临时解决方法。