确保您的应用在网络连接不稳定或用户离线时也可以正常使用,从而提供更好的用户体验。一种方式是同时从网络和本地数据库加载页面。这样,您的应用就会从本地数据库缓存驱动界面,并且仅在数据库中不再有数据时才向网络发出请求。
本指南假设您熟悉 Room 持久性库以及 Paging 库的基本用法。
协调数据加载
Paging 库针对该用例提供了 RemoteMediator
组件。当应用的已缓存数据用尽时,RemoteMediator
会充当来自 Paging 库的信号。您可以使用此信号从网络加载更多数据并将其存储在本地数据库中,PagingSource
可以从本地数据库加载这些数据并将其提供给界面进行显示。
当需要更多数据时,Paging 库从 RemoteMediator
实现调用 load()
方法。这是一个挂起函数,因此可以放心地执行长时间运行的工作。此函数通常从网络源提取新数据并将其保存到本地存储空间。
此过程会处理新数据,但长期存储在数据库中的数据需要进行失效处理(例如,当用户手动触发刷新时)。这由传递到 load()
方法的 LoadType
属性表示。LoadType
会通知 RemoteMediator
是需要刷新现有数据,还是提取需要附加或前置到现有列表的更多数据。
通过这种方式,RemoteMediator
可确保您的应用以适当的顺序加载用户要查看的数据。
Paging 生命周期
![](https://developer.android.google.cn/static/topic/libraries/architecture/images/paging3-base-lifecycle.png?authuser=6&hl=vi)
直接从网络进行分页时,PagingSource
会加载数据并返回 LoadResult
对象。PagingSource
实现通过 pagingSourceFactory
参数传递给 Pager
。
当界面需要新数据时,Pager
会从 PagingSource
调用 load()
方法并返回一个封装新数据的 PagingData
对象流。通常,每个 PagingData
对象都会先缓存在 ViewModel
中,然后再发送到界面进行显示。
![](https://developer.android.google.cn/static/topic/libraries/architecture/images/paging3-layered-lifecycle.png?authuser=6&hl=vi)
RemoteMediator
会更改此数据流。PagingSource
仍会加载数据;但在分页数据耗尽时,Paging 库会触发 RemoteMediator
以从网络源加载新数据。RemoteMediator
会将新数据存储在本地数据库中,因此无需在 ViewModel
中使用内存缓存。最后,PagingSource
会使自身失效,而 Pager
会创建一个新实例以从数据库中加载新数据。
基本用法
假设您希望应用将 User
项的页面从由项进行键控的网络数据源加载到存储在 Room 数据库中的本地缓存内。
RemoteMediator
实现有助于将来自网络的分页数据加载到数据库中,但不会直接将数据加载到界面中,而是会将数据库用作可信来源。换句话说,该应用仅显示已在数据库中缓存的数据。PagingSource
实现(例如,由 Room 生成的实现)可处理将缓存数据从数据库加载到界面的过程。
创建 Room 实体
第一步是使用 Room 持久性库定义一个数据库,用于在本地缓存来自网络数据源的分页数据。首先,创建 RoomDatabase
的实现,如使用 Room 将数据保存到本地数据库中所述。
接下来,定义一个代表由列表项组成的表的 Room 实体,如使用 Room 实体定义数据中所述。提供 id
字段作为主键,并提供列表项包含的其他任何信息所对应的字段。
Kotlin
@Entity(tableName = "users") data class User(val id: String, val label: String)
Java
@Entity(tableName = "users") public class User { public String id; public String label; }
Java
@Entity(tableName = "users") public class User { public String id; public String label; }
您还必须按照使用 Room DAO 访问数据中所述为此 Room 实体定义数据访问对象 (DAO)。该列表项实体的 DAO 必须包含以下方法:
insertAll()
方法,用于将一系列项插入到表中。- 一个以查询字符串作为参数并返回结果列表的
PagingSource
对象的方法。这样,Pager
对象就可以将此表用作分页数据源。 clearAll()
方法,用于删除表中的所有数据。
Kotlin
@Dao interface UserDao { @Insert(onConflict = OnConflictStrategy.REPLACE) suspend fun insertAll(users: List<User>) @Query("SELECT * FROM users WHERE label LIKE :query") fun pagingSource(query: String): PagingSource<Int, User> @Query("DELETE FROM users") suspend fun clearAll() }
Java
@Dao interface UserDao { @Insert(onConflict = OnConflictStrategy.REPLACE) void insertAll(List<User> users); @Query("SELECT * FROM users WHERE mLabel LIKE :query") PagingSource<Integer, User> pagingSource(String query); @Query("DELETE FROM users") int clearAll(); }
Java
@Dao interface UserDao { @Insert(onConflict = OnConflictStrategy.REPLACE) void insertAll(List<User> users); @Query("SELECT * FROM users WHERE mLabel LIKE :query") PagingSource<Integer, User> pagingSource(String query); @Query("DELETE FROM users") int clearAll(); }
实现 RemoteMediator
RemoteMediator
的主要作用是:在 Pager
耗尽数据或现有数据失效时,从网络加载更多数据。它包含 load()
方法,您必须替换该方法才能定义加载行为。
典型的 RemoteMediator
实现包括以下参数:
query
:用于定义要从后端服务检索哪些数据的查询字符串。database
:充当本地缓存的 Room 数据库。networkService
:后端服务的 API 实例。
创建 RemoteMediator<Key, Value>
实现。Key
类型和 Value
类型应与针对同一网络数据源定义 PagingSource
时相同。如需详细了解如何选择类型参数,请参阅选择键和值类型。
Kotlin
@OptIn(ExperimentalPagingApi::class) class ExampleRemoteMediator( private val query: String, private val database: RoomDb, private val networkService: ExampleBackendService ) : RemoteMediator<Int, User>() { val userDao = database.userDao() override suspend fun load( loadType: LoadType, state: PagingState<Int, User> ): MediatorResult { // ... } }
Java
@UseExperimental(markerClass = ExperimentalPagingApi.class) class ExampleRemoteMediator extends RxRemoteMediator<Integer, User> { private String query; private ExampleBackendService networkService; private RoomDb database; private UserDao userDao; ExampleRemoteMediator( String query, ExampleBackendService networkService, RoomDb database ) { query = query; networkService = networkService; database = database; userDao = database.userDao(); } @NotNull @Override public Single<MediatorResult> loadSingle( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { ... } }
Java
class ExampleRemoteMediator extends ListenableFutureRemoteMediator<Integer, User> { private String query; private ExampleBackendService networkService; private RoomDb database; private UserDao userDao; private Executor bgExecutor; ExampleRemoteMediator( String query, ExampleBackendService networkService, RoomDb database, Executor bgExecutor ) { this.query = query; this.networkService = networkService; this.database = database; this.userDao = database.userDao(); this.bgExecutor = bgExecutor; } @NotNull @Override public ListenableFuture<MediatorResult> loadFuture( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { ... } }
load()
方法负责更新后备数据集以及使 PagingSource
失效。某些支持分页的库(例如 Room)会自动处理使其实现的 PagingSource
对象失效的过程。
load()
方法接受以下两个参数:
PagingState
:包含到目前为止已加载的页面、最近访问的索引以及用于初始化分页数据流的PagingConfig
对象的相关信息。LoadType
:指示加载的类型:REFRESH
、APPEND
或PREPEND
。
load()
方法的返回值是 MediatorResult
对象。MediatorResult
可以是 MediatorResult.Error
(包含错误说明)或 MediatorResult.Success
(包含指示是否有更多数据要加载的信号)。
load()
方法必须执行以下步骤:
- 根据加载类型和到目前为止已加载的数据,确定要从网络中加载哪个页面。
- 触发网络请求。
- 根据加载操作的结果执行操作:
- 如果加载成功且收到的项列表不是空的,则将相应的列表项存储到数据库中并返回
MediatorResult.Success(endOfPaginationReached = false)
。存储数据后,使数据源失效,以通知 Paging 库新数据的存在。 - 如果加载成功并且接收到的项列表为空或为最后一页索引,则返回
MediatorResult.Success(endOfPaginationReached = true)
。存储数据后,使数据源失效,以通知 Paging 库新数据的存在。 - 如果请求导致错误,则返回
MediatorResult.Error
。
- 如果加载成功且收到的项列表不是空的,则将相应的列表项存储到数据库中并返回
Kotlin
override suspend fun load( loadType: LoadType, state: PagingState<Int, User> ): MediatorResult { return try { // The network load method takes an optional after=<user.id> // parameter. For every page after the first, pass the last user // ID to let it continue from where it left off. For REFRESH, // pass null to load the first page. val loadKey = when (loadType) { LoadType.REFRESH -> null // In this example, you never need to prepend, since REFRESH // will always load the first page in the list. Immediately // return, reporting end of pagination. LoadType.PREPEND -> return MediatorResult.Success(endOfPaginationReached = true) LoadType.APPEND -> { val lastItem = state.lastItemOrNull() // You must explicitly check if the last item is null when // appending, since passing null to networkService is only // valid for initial load. If lastItem is null it means no // items were loaded after the initial REFRESH and there are // no more items to load. if (lastItem == null) { return MediatorResult.Success( endOfPaginationReached = true ) } lastItem.id } } // Suspending network load via Retrofit. This doesn't need to be // wrapped in a withContext(Dispatcher.IO) { ... } block since // Retrofit's Coroutine CallAdapter dispatches on a worker // thread. val response = networkService.searchUsers( query = query, after = loadKey ) database.withTransaction { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query) } // Insert new users into database, which invalidates the // current PagingData, allowing Paging to present the updates // in the DB. userDao.insertAll(response.users) } MediatorResult.Success( endOfPaginationReached = response.nextKey == null ) } catch (e: IOException) { MediatorResult.Error(e) } catch (e: HttpException) { MediatorResult.Error(e) } }
Java
@NotNull @Override public Single<MediatorResult> loadSingle( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { // The network load method takes an optional after=<user.id> parameter. For // every page after the first, pass the last user ID to let it continue from // where it left off. For REFRESH, pass null to load the first page. String loadKey = null; switch (loadType) { case REFRESH: break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Single.just(new MediatorResult.Success(true)); case APPEND: User lastItem = state.lastItemOrNull(); // You must explicitly check if the last item is null when appending, // since passing null to networkService is only valid for initial load. // If lastItem is null it means no items were loaded after the initial // REFRESH and there are no more items to load. if (lastItem == null) { return Single.just(new MediatorResult.Success(true)); } loadKey = lastItem.getId(); break; } return networkService.searchUsers(query, loadKey) .subscribeOn(Schedulers.io()) .map((Function<SearchUserResponse, MediatorResult>) response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); } // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getNextKey() == null); }) .onErrorResumeNext(e -> { if (e instanceof IOException || e instanceof HttpException) { return Single.just(new MediatorResult.Error(e)); } return Single.error(e); }); }
Java
@NotNull @Override public ListenableFuture<MediatorResult> loadFuture( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { // The network load method takes an optional after=<user.id> parameter. For // every page after the first, pass the last user ID to let it continue from // where it left off. For REFRESH, pass null to load the first page. String loadKey = null; switch (loadType) { case REFRESH: break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Futures.immediateFuture(new MediatorResult.Success(true)); case APPEND: User lastItem = state.lastItemOrNull(); // You must explicitly check if the last item is null when appending, // since passing null to networkService is only valid for initial load. // If lastItem is null it means no items were loaded after the initial // REFRESH and there are no more items to load. if (lastItem == null) { return Futures.immediateFuture(new MediatorResult.Success(true)); } loadKey = lastItem.getId(); break; } ListenableFuture<MediatorResult> networkResult = Futures.transform( networkService.searchUsers(query, loadKey), response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); } // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getNextKey() == null); }, bgExecutor); ListenableFuture<MediatorResult> ioCatchingNetworkResult = Futures.catching( networkResult, IOException.class, MediatorResult.Error::new, bgExecutor ); return Futures.catching( ioCatchingNetworkResult, HttpException.class, MediatorResult.Error::new, bgExecutor ); }
定义 initialize 方法
RemoteMediator
实现还可以替换 initialize()
方法,以检查缓存的数据是否已过期,并决定是否触发远程刷新。此方法在执行任何加载之前运行,因此您可以在触发任何本地或远程加载之前操控数据库(例如,清除旧数据)。
由于 initialize()
是一个异步函数,因此您可以加载数据来确定数据库中现有数据的相关性。最常见的情况是缓存的数据仅在特定时间段内有效。RemoteMediator
可以检查此到期时间是否已失效,在这种情况下,Paging 库需要完全刷新数据。initialize()
实现应返回一个 InitializeAction
,如下所示:
- 如果需要完全刷新本地数据,
initialize()
应返回InitializeAction.LAUNCH_INITIAL_REFRESH
。这会使RemoteMediator
执行远程刷新以完全重新加载数据。任何远程APPEND
或PREPEND
加载都会等待REFRESH
加载成功,然后再继续。 - 如果本地数据不需要刷新,
initialize()
应返回InitializeAction.SKIP_INITIAL_REFRESH
。这会使RemoteMediator
跳过远程刷新并加载缓存的数据。
Kotlin
override suspend fun initialize(): InitializeAction { val cacheTimeout = TimeUnit.MILLISECONDS.convert(1, TimeUnit.HOURS) return if (System.currentTimeMillis() - db.lastUpdated() <= cacheTimeout) { // Cached data is up-to-date, so there is no need to re-fetch // from the network. InitializeAction.SKIP_INITIAL_REFRESH } else { // Need to refresh cached data from network; returning // LAUNCH_INITIAL_REFRESH here will also block RemoteMediator's // APPEND and PREPEND from running until REFRESH succeeds. InitializeAction.LAUNCH_INITIAL_REFRESH } }
Java
@NotNull @Override public Single<InitializeAction> initializeSingle() { long cacheTimeout = TimeUnit.MILLISECONDS.convert(1, TimeUnit.HOURS); return mUserDao.lastUpdatedSingle() .map(lastUpdatedMillis -> { if (System.currentTimeMillis() - lastUpdatedMillis <= cacheTimeout) { // Cached data is up-to-date, so there is no need to re-fetch // from the network. return InitializeAction.SKIP_INITIAL_REFRESH; } else { // Need to refresh cached data from network; returning // LAUNCH_INITIAL_REFRESH here will also block RemoteMediator's // APPEND and PREPEND from running until REFRESH succeeds. return InitializeAction.LAUNCH_INITIAL_REFRESH; } }); }
Java
@NotNull @Override public ListenableFuture<InitializeAction> initializeFuture() { long cacheTimeout = TimeUnit.MILLISECONDS.convert(1, TimeUnit.HOURS); return Futures.transform( mUserDao.lastUpdated(), lastUpdatedMillis -> { if (System.currentTimeMillis() - lastUpdatedMillis <= cacheTimeout) { // Cached data is up-to-date, so there is no need to re-fetch // from the network. return InitializeAction.SKIP_INITIAL_REFRESH; } else { // Need to refresh cached data from network; returning // LAUNCH_INITIAL_REFRESH here will also block RemoteMediator's // APPEND and PREPEND from running until REFRESH succeeds. return InitializeAction.LAUNCH_INITIAL_REFRESH; } }, mBgExecutor); }
创建分页器
最后,您必须创建一个 Pager
实例来设置分页数据流。此过程与从简单的网络数据源创建 Pager
类似,但在以下两个方面不同:
- 您不能直接传递
PagingSource
构造函数,而必须提供从 DAO 返回PagingSource
对象的查询方法。 - 您必须提供
RemoteMediator
实现的实例作为remoteMediator
参数。
Kotlin
val userDao = database.userDao() val pager = Pager( config = PagingConfig(pageSize = 50) remoteMediator = ExampleRemoteMediator(query, database, networkService) ) { userDao.pagingSource(query) }
Java
UserDao userDao = database.userDao(); Pager<Integer, User> pager = Pager( new PagingConfig(/* pageSize = */ 20), null, // initialKey, new ExampleRemoteMediator(query, database, networkService) () -> userDao.pagingSource(query));
Java
UserDao userDao = database.userDao(); Pager<Integer, User> pager = Pager( new PagingConfig(/* pageSize = */ 20), null, // initialKey new ExampleRemoteMediator(query, database, networkService, bgExecutor), () -> userDao.pagingSource(query));
处理竞态条件
您的应用从多个来源加载数据时,需要应对以下这种情况:本地已缓存的数据与远程数据源不同步。
当 RemoteMediator
实现中的 initialize()
方法返回 LAUNCH_INITIAL_REFRESH
时,数据会过时,必须替换为新数据。系统会强制任何 PREPEND
或 APPEND
加载请求等待远程 REFRESH
加载成功完成。由于 PREPEND
或 APPEND
请求在 REFRESH
请求之前排入队列,因此传递给这些加载调用的 PagingState
在运行时可能已经过期。
如果对已缓存数据的更改导致失效和提取新数据,您的应用可能会忽略冗余请求,具体取决于本地存储数据的方式。
例如,Room 会在插入任何数据时使查询失效。这意味着,将新数据插入数据库时,系统将向待处理的加载请求提供包含已刷新数据的新 PagingSource
对象。
解决此数据同步问题是确保用户看到最相关、最新的数据的关键所在。最佳解决方案主要取决于网络数据源对数据进行分页的方式。在任何情况下,您都可以使用远程键保存从服务器请求的最新页面的相关信息。您的应用可以使用此信息来识别和请求接下来要加载的正确数据页面。
管理远程键
远程键供 RemoteMediator
实现用来告知后端服务下一步要加载哪些数据。在最简单的场景下,每一项分页数据都包含一个可供您轻松引用的远程键。不过,如果远程键不与单个项对应,则必须单独存储它们,并通过 load()
方法管理它们。
本部分介绍如何收集、存储和更新未存储在各个项中的远程键。
项键
本部分介绍如何使用与各个项相对应的远程键。通常情况下,当 API 密钥脱离单个项时,项 ID 会作为查询参数传递。参数名称指示服务器应该在提供的 ID 之前还是之后响应项目。在 User
模型类的示例中,来自服务器的 id
字段在请求其他数据时被用作远程键。
当您的 load()
方法需要管理项专用的远程键时,这些键通常是从服务器提取的数据的 ID。刷新操作不需要加载键,因为它们只检索最近的数据。
同样,前置操作不需要提取任何其他数据,因为刷新总是从服务器提取最新数据。
但是,附加操作确实需要 ID。为此,您需要从数据库中加载最后一项,并使用其 ID 加载下一页数据。如果数据库中没有任何项目,则 endOfPaginationReached
设为 true,指示需要刷新数据。
Kotlin
@OptIn(ExperimentalPagingApi::class) class ExampleRemoteMediator( private val query: String, private val database: RoomDb, private val networkService: ExampleBackendService ) : RemoteMediator<Int, User>() { val userDao = database.userDao() override suspend fun load( loadType: LoadType, state: PagingState<Int, User> ): MediatorResult { return try { // The network load method takes an optional String // parameter. For every page after the first, pass the String // token returned from the previous page to let it continue // from where it left off. For REFRESH, pass null to load the // first page. val loadKey = when (loadType) { LoadType.REFRESH -> null // In this example, you never need to prepend, since REFRESH // will always load the first page in the list. Immediately // return, reporting end of pagination. LoadType.PREPEND -> return MediatorResult.Success( endOfPaginationReached = true ) // Get the last User object id for the next RemoteKey. LoadType.APPEND -> { val lastItem = state.lastItemOrNull() // You must explicitly check if the last item is null when // appending, since passing null to networkService is only // valid for initial load. If lastItem is null it means no // items were loaded after the initial REFRESH and there are // no more items to load. if (lastItem == null) { return MediatorResult.Success( endOfPaginationReached = true ) } lastItem.id } } // Suspending network load via Retrofit. This doesn't need to // be wrapped in a withContext(Dispatcher.IO) { ... } block // since Retrofit's Coroutine CallAdapter dispatches on a // worker thread. val response = networkService.searchUsers(query, loadKey) // Store loaded data, and next key in transaction, so that // they're always consistent. database.withTransaction { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query) } // Insert new users into database, which invalidates the // current PagingData, allowing Paging to present the updates // in the DB. userDao.insertAll(response.users) } // End of pagination has been reached if no users are returned from the // service MediatorResult.Success( endOfPaginationReached = response.users.isEmpty() ) } catch (e: IOException) { MediatorResult.Error(e) } catch (e: HttpException) { MediatorResult.Error(e) } } }
Java
@NotNull @Override public Single>MediatorResult< loadSingle( @NotNull LoadType loadType, @NotNull PagingState>Integer, User< state ) { // The network load method takes an optional String parameter. For every page // after the first, pass the String token returned from the previous page to // let it continue from where it left off. For REFRESH, pass null to load the // first page. Single>String< remoteKeySingle = null; switch (loadType) { case REFRESH: // Initial load should use null as the page key, so you can return null // directly. remoteKeySingle = Single.just(null); break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Single.just(new MediatorResult.Success(true)); case APPEND: User lastItem = state.lastItemOrNull(); // You must explicitly check if the last item is null when // appending, since passing null to networkService is only // valid for initial load. If lastItem is null it means no // items were loaded after the initial REFRESH and there are // no more items to load. if (lastItem == null) { return Single.just(new MediatorResult.Success(true)); } remoteKeySingle = Single.just(lastItem.getId()); break; } return remoteKeySingle .subscribeOn(Schedulers.io()) .flatMap((Function<String, Single<MediatorResult>>) remoteKey -> { return networkService.searchUsers(query, remoteKey) .map(response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); } // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getUsers().isEmpty()); }); }) .onErrorResumeNext(e -> { if (e instanceof IOException || e instanceof HttpException) { return Single.just(new MediatorResult.Error(e)); } return Single.error(e); }); }
Java
@NotNull @Override public ListenableFuture<MediatorResult> loadFuture( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { // The network load method takes an optional after=<user.id> parameter. // For every page after the first, pass the last user ID to let it continue // from where it left off. For REFRESH, pass null to load the first page. ResolvableFuture<String> remoteKeyFuture = ResolvableFuture.create(); switch (loadType) { case REFRESH: remoteKeyFuture.set(null); break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Futures.immediateFuture(new MediatorResult.Success(true)); case APPEND: User lastItem = state.lastItemOrNull(); // You must explicitly check if the last item is null when appending, // since passing null to networkService is only valid for initial load. // If lastItem is null it means no items were loaded after the initial // REFRESH and there are no more items to load. if (lastItem == null) { return Futures.immediateFuture(new MediatorResult.Success(true)); } remoteKeyFuture.set(lastItem.getId()); break; } return Futures.transformAsync(remoteKeyFuture, remoteKey -> { ListenableFuture<MediatorResult> networkResult = Futures.transform( networkService.searchUsers(query, remoteKey), response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); } // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getUsers().isEmpty()); }, bgExecutor); ListenableFuture<MediatorResult> ioCatchingNetworkResult = Futures.catching( networkResult, IOException.class, MediatorResult.Error::new, bgExecutor ); return Futures.catching( ioCatchingNetworkResult, HttpException.class, MediatorResult.Error::new, bgExecutor ); }, bgExecutor); }
页面键
本部分介绍如何使用与单个项不相对应的远程键。
添加远程键表
如果远程键未与列表项直接关联,最好将其存储在本地数据库内的单独表中。定义一个代表远程键表的 Room 实体:
Kotlin
@Entity(tableName = "remote_keys") data class RemoteKey(val label: String, val nextKey: String?)
Java
@Entity(tableName = "remote_keys") public class RemoteKey { public String label; public String nextKey; }
Java
@Entity(tableName = "remote_keys") public class RemoteKey { public String label; public String nextKey; }
您还必须为该 RemoteKey
实体定义一个 DAO:
Kotlin
@Dao interface RemoteKeyDao { @Insert(onConflict = OnConflictStrategy.REPLACE) suspend fun insertOrReplace(remoteKey: RemoteKey) @Query("SELECT * FROM remote_keys WHERE label = :query") suspend fun remoteKeyByQuery(query: String): RemoteKey @Query("DELETE FROM remote_keys WHERE label = :query") suspend fun deleteByQuery(query: String) }
Java
@Dao interface RemoteKeyDao { @Insert(onConflict = OnConflictStrategy.REPLACE) void insertOrReplace(RemoteKey remoteKey); @Query("SELECT * FROM remote_keys WHERE label = :query") Single<RemoteKey> remoteKeyByQuerySingle(String query); @Query("DELETE FROM remote_keys WHERE label = :query") void deleteByQuery(String query); }
Java
@Dao interface RemoteKeyDao { @Insert(onConflict = OnConflictStrategy.REPLACE) void insertOrReplace(RemoteKey remoteKey); @Query("SELECT * FROM remote_keys WHERE label = :query") ListenableFuture<RemoteKey> remoteKeyByQueryFuture(String query); @Query("DELETE FROM remote_keys WHERE label = :query") void deleteByQuery(String query); }
使用远程键加载
当 load()
方法需要管理远程页面键时,您必须使用与 RemoteMediator
的基本用法不同的以下方式来定义它。
- 额外添加一个属性,用于存放对远程键表的 DAO 的引用。
- 通过查询远程键表(而不是使用
PagingState
)确定下一步要加载哪个键。 - 除分页数据本身外,还要从网络数据源插入或存储返回的远程键。
Kotlin
@OptIn(ExperimentalPagingApi::class) class ExampleRemoteMediator( private val query: String, private val database: RoomDb, private val networkService: ExampleBackendService ) : RemoteMediator<Int, User>() { val userDao = database.userDao() val remoteKeyDao = database.remoteKeyDao() override suspend fun load( loadType: LoadType, state: PagingState<Int, User> ): MediatorResult { return try { // The network load method takes an optional String // parameter. For every page after the first, pass the String // token returned from the previous page to let it continue // from where it left off. For REFRESH, pass null to load the // first page. val loadKey = when (loadType) { LoadType.REFRESH -> null // In this example, you never need to prepend, since REFRESH // will always load the first page in the list. Immediately // return, reporting end of pagination. LoadType.PREPEND -> return MediatorResult.Success( endOfPaginationReached = true ) // Query remoteKeyDao for the next RemoteKey. LoadType.APPEND -> { val remoteKey = database.withTransaction { remoteKeyDao.remoteKeyByQuery(query) } // You must explicitly check if the page key is null when // appending, since null is only valid for initial load. // If you receive null for APPEND, that means you have // reached the end of pagination and there are no more // items to load. if (remoteKey.nextKey == null) { return MediatorResult.Success( endOfPaginationReached = true ) } remoteKey.nextKey } } // Suspending network load via Retrofit. This doesn't need to // be wrapped in a withContext(Dispatcher.IO) { ... } block // since Retrofit's Coroutine CallAdapter dispatches on a // worker thread. val response = networkService.searchUsers(query, loadKey) // Store loaded data, and next key in transaction, so that // they're always consistent. database.withTransaction { if (loadType == LoadType.REFRESH) { remoteKeyDao.deleteByQuery(query) userDao.deleteByQuery(query) } // Update RemoteKey for this query. remoteKeyDao.insertOrReplace( RemoteKey(query, response.nextKey) ) // Insert new users into database, which invalidates the // current PagingData, allowing Paging to present the updates // in the DB. userDao.insertAll(response.users) } MediatorResult.Success( endOfPaginationReached = response.nextKey == null ) } catch (e: IOException) { MediatorResult.Error(e) } catch (e: HttpException) { MediatorResult.Error(e) } } }
Java
@NotNull @Override public Single<MediatorResult> loadSingle( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { // The network load method takes an optional String parameter. For every page // after the first, pass the String token returned from the previous page to // let it continue from where it left off. For REFRESH, pass null to load the // first page. Single<RemoteKey> remoteKeySingle = null; switch (loadType) { case REFRESH: // Initial load should use null as the page key, so you can return null // directly. remoteKeySingle = Single.just(new RemoteKey(mQuery, null)); break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Single.just(new MediatorResult.Success(true)); case APPEND: // Query remoteKeyDao for the next RemoteKey. remoteKeySingle = mRemoteKeyDao.remoteKeyByQuerySingle(mQuery); break; } return remoteKeySingle .subscribeOn(Schedulers.io()) .flatMap((Function<RemoteKey, Single<MediatorResult>>) remoteKey -> { // You must explicitly check if the page key is null when appending, // since null is only valid for initial load. If you receive null // for APPEND, that means you have reached the end of pagination and // there are no more items to load. if (loadType != REFRESH && remoteKey.getNextKey() == null) { return Single.just(new MediatorResult.Success(true)); } return networkService.searchUsers(query, remoteKey.getNextKey()) .map(response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); remoteKeyDao.deleteByQuery(query); } // Update RemoteKey for this query. remoteKeyDao.insertOrReplace(new RemoteKey(query, response.getNextKey())); // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getNextKey() == null); }); }) .onErrorResumeNext(e -> { if (e instanceof IOException || e instanceof HttpException) { return Single.just(new MediatorResult.Error(e)); } return Single.error(e); }); }
Java
@NotNull @Override public ListenableFuture<MediatorResult> loadFuture( @NotNull LoadType loadType, @NotNull PagingState<Integer, User> state ) { // The network load method takes an optional after=<user.id> parameter. For // every page after the first, pass the last user ID to let it continue from // where it left off. For REFRESH, pass null to load the first page. ResolvableFuture<RemoteKey> remoteKeyFuture = ResolvableFuture.create(); switch (loadType) { case REFRESH: remoteKeyFuture.set(new RemoteKey(query, null)); break; case PREPEND: // In this example, you never need to prepend, since REFRESH will always // load the first page in the list. Immediately return, reporting end of // pagination. return Futures.immediateFuture(new MediatorResult.Success(true)); case APPEND: User lastItem = state.lastItemOrNull(); // You must explicitly check if the last item is null when appending, // since passing null to networkService is only valid for initial load. // If lastItem is null it means no items were loaded after the initial // REFRESH and there are no more items to load. if (lastItem == null) { return Futures.immediateFuture(new MediatorResult.Success(true)); } // Query remoteKeyDao for the next RemoteKey. remoteKeyFuture.setFuture( remoteKeyDao.remoteKeyByQueryFuture(query)); break; } return Futures.transformAsync(remoteKeyFuture, remoteKey -> { // You must explicitly check if the page key is null when appending, // since null is only valid for initial load. If you receive null // for APPEND, that means you have reached the end of pagination and // there are no more items to load. if (loadType != LoadType.REFRESH && remoteKey.getNextKey() == null) { return Futures.immediateFuture(new MediatorResult.Success(true)); } ListenableFuture<MediatorResult> networkResult = Futures.transform( networkService.searchUsers(query, remoteKey.getNextKey()), response -> { database.runInTransaction(() -> { if (loadType == LoadType.REFRESH) { userDao.deleteByQuery(query); remoteKeyDao.deleteByQuery(query); } // Update RemoteKey for this query. remoteKeyDao.insertOrReplace(new RemoteKey(query, response.getNextKey())); // Insert new users into database, which invalidates the current // PagingData, allowing Paging to present the updates in the DB. userDao.insertAll(response.getUsers()); }); return new MediatorResult.Success(response.getNextKey() == null); }, bgExecutor); ListenableFuture<MediatorResult> ioCatchingNetworkResult = Futures.catching( networkResult, IOException.class, MediatorResult.Error::new, bgExecutor ); return Futures.catching( ioCatchingNetworkResult, HttpException.class, MediatorResult.Error::new, bgExecutor ); }, bgExecutor); }
就地刷新
如果您的应用只需要像前面的示例那样支持自列表顶部的网络刷新,您的 RemoteMediator
就不需要定义前置加载行为。
但是,如果您的应用需要支持将数据从网络逐步加载到本地数据库,您就必须支持从锚点(即用户的滚动位置)开始恢复分页。Room 的 PagingSource
实现会为您处理此情况,但如果您未使用 Room,也可以通过替换 PagingSource.getRefreshKey()
来实现此目的。
如需查看 getRefreshKey()
的实现示例,请参阅定义 PagingSource。
图 4 说明了先从本地数据库加载数据,然后在数据库中不再有数据后从网络加载数据的过程。
其他资源
如需详细了解 Paging 库,请参阅下列其他资源:
Codelab
示例
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- 注意:当 JavaScript 处于关闭状态时,系统会显示链接文字
- 加载并显示分页数据
- 测试 Paging 实现
- 迁移到 Paging 3