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。
- 您想要监听聚合结果以获取实时更新。
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();
Swift
do { let snapshot = try await db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .getDocuments() print(snapshot) } catch { print(error) }
Objective-C
FIRQuery *query = [[[self.db collectionWithPath:@"restaurants"] documentWithPath:@"arinell-pizza"] collectionWithPath:@"ratings"]; [query getDocumentsWithCompletion:^(FIRQuerySnapshot * _Nullable snapshot, NSError * _Nullable error) { // ... }];
Kotlin
db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .get()
Java
db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .get();
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 };
Swift
struct Restaurant { let name: String let avgRating: Float let numRatings: Int } let arinell = Restaurant(name: "Arinell Pizza", avgRating: 4.65, numRatings: 683)
Objective-C
@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; } @end
Kotlin
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)
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);
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 }); }); }); }
Swift
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 { // ... } }
Objective-C
- (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) { // ... }]; }
Kotlin
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 } }
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; } }); }
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 }); }); });
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。