怎样在 Akka Persistence 中实现分页查询

在 Akka Persistence 中,数据都缓存在服务内存(状态),后端存储的都是一些持久化的事件日志,没法使用类似 SQL 一样的 DSL 来进行分页查询。利用 Akka Streams 和 Actor 我们可以通过编码的方式来实现分页查询的效果,而且这个分页查询还是分步式并行的……

EventSourcedBehavior

Akka Persistence的EventSourcedBehavior里实现了CQRS模型,通过commandHandlereventHandler解耦了命令处理与事件处理。commandHandler处理传入的命令并返回一个事件,并可选择将这个事件持久化;若事件需要持久化,则事件将被传给eventHandler处理,eventHandler处理完事件后将返回一个“新的”状态(也可以不更新,直接返回原状态)。

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def apply[Command, Event, State](
persistenceId: PersistenceId,
emptyState: State,
commandHandler: (State, Command) => Effect[Event, State],
eventHandler: (State, Event) => State): EventSourcedBehavior[Command, Event, State]

建模

以我们习惯的数据库表建模来说,我们会有以下一张表:

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create table t_config
(
data_id varchar(64),
namespace varchar(64) not null,
config_type varchar(32) not null,
content text not null,
constraint t_config_pk primary key (namespace, data_id)
);
create index t_config_idx_data_id on t_config (data_id);

ConfigManager actor 可以看作 t_config 表,它的 entityId 就是 namespaceState 里保存了所有记录的主键值(ConfigManagerState),这就相当于 t_config 表的 t_config_idx_data_id 索引。

ConfigEntity actor 可看作 t_config 表里存储的记录,每个 actor 实例就是一行记录。它的 entityIdnamespace + data_id 组成,这就相当于 t_config 表的 t_config_pk 复合主键。
这里我们定义两个 EventSourcedBehavior

  • ConfigManager:拥有所有配置ID列表,并作为 State 保存在 EventSourcedBehavior
  • ConfigEntity: 拥有每个配置数据,并作为 State 保存在 EventSourcedBehavior

实现

这里先贴出 ConfigManagerConfigEntity 的部分代码,接下来再详解怎样实现分页查询。

ConfigManager

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object ConfigManager {
sealed trait Command extends CborSerializable
sealed trait Event extends CborSerializable
sealed trait Response extends CborSerializable

final case class Query(dataId: Option[String], configType: Option[String], page: Int, size: Int) extends Command
final case class ReplyCommand(in: AnyRef, replyTo: ActorRef[Response]) extends Command
private final case class InternalResponse(replyTo: ActorRef[Response], response: Response) extends Command

case class ConfigResponse(status: Int, message: String = "", data: Option[AnyRef] = None) extends Response

final case class ConfigManagerState(dataIds: Vector[String] = Vector()) extends CborSerializable

val TypeKey: EntityTypeKey[Command] = EntityTypeKey("ConfigManager")
}

import ConfigManager._
class ConfigManager private (namespace: String, context: ActorContext[Command]) {
private implicit val system = context.system
private implicit val timeout: Timeout = 5.seconds
import context.executionContext
private val configEntity = ConfigEntity.init(context.system)

def eventSourcedBehavior(): EventSourcedBehavior[Command, Event, ConfigManagerState] =
EventSourcedBehavior(
PersistenceId.of(TypeKey.name, namespace),
ConfigManagerState(), {
case (state, ReplyCommand(in, replyTo)) =>
replyCommandHandler(state, replyTo, in)
case (_, InternalResponse(replyTo, response)) =>
Effect.reply(replyTo)(response)
},
eventHandler)

private def processPageQuery(
state: ConfigManagerState,
replyTo: ActorRef[Response],
in: Query): Effect[Event, ConfigManagerState] = {
val offset = if (in.page > 0) (in.page - 1) * in.size else 0
val responseF = if (offset < state.dataIds.size) {
Source(state.dataIds)
.filter(dataId => in.dataId.forall(v => v.contains(dataId)))
.mapAsync(20) { dataId =>
configEntity.ask[Option[ConfigState]](replyTo =>
ShardingEnvelope(dataId, ConfigEntity.Query(in.configType, replyTo)))
}
.collect { case Some(value) => value }
.drop(offset)
.take(in.size)
.runWith(Sink.seq)
.map(items => ConfigResponse(IntStatus.OK, data = Some(items)))
} else {
Future.successful(ConfigResponse(IntStatus.NOT_FOUND, data = Some(Nil)))
}
context.pipeToSelf(responseF) {
case Success(value) => InternalResponse(replyTo, value)
case Failure(e) => InternalResponse(replyTo, ConfigResponse(IntStatus.INTERNAL_ERROR, e.getLocalizedMessage))
}
Effect.none
}
}

ConfigEntity

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object ConfigEntity {
case class ConfigState(namespace: String, dataId: String, configType: String, content: String)

sealed trait Command extends CborSerializable
sealed trait Event extends CborSerializable

final case class Query(configType: Option[String], replyTo: ActorRef[Option[ConfigState]]) extends Command

final case class ConfigEntityState(config: Option[ConfigState] = None) extends CborSerializable

val TypeKey: EntityTypeKey[Command] = EntityTypeKey("ConfigEntity")
}

import ConfigEntity._
class ConfigEntity private (namespace: String, dataId: String, context: ActorContext[Command]) {
def eventSourcedBehavior(): EventSourcedBehavior[Command, Event, ConfigEntityState] =
EventSourcedBehavior(PersistenceId.of(TypeKey.name, dataId), ConfigEntityState(), commandHandler, eventHandler)

def commandHandler(state: ConfigEntityState, command: Command): Effect[Event, ConfigEntityState] = command match {
case Query(configType, replyTo) =>
state.config match {
case None =>
Effect.reply(replyTo)(None)
case Some(config) =>
val resp = if (configType.forall(v => config.configType.contains(v))) Some(config) else None
Effect.reply(replyTo)(resp)
}
}
}

ConfigManager#processPageQuery 函数实现了大部分的分页查询逻辑(有部分逻辑需要由 ConfigEntity 处理)。

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val offset = if (in.page > 0) (in.page - 1) * in.size else 0
val responseF = if (offset < state.dataIds.size) {
// process paging
} else {
Future.successful(ConfigResponse(IntStatus.OK, data = Some(Nil)))
}

这里首先获取实际的分页数据偏移量 offset ,再于 ConfigManager 状态里保存的 dataIds 的大小进行判断,若 offset < state.dataIds.size 则我们进行分页逻辑,否则直接返回一个空列表给前端。

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Source(state.dataIds)
.filter(dataId => in.dataId.forall(v => v.contains(dataId)))
.mapAsync(20) { dataId =>
configEntity.ask[Option[ConfigState]](replyTo =>
ShardingEnvelope(s"$namespace@$dataId", ConfigEntity.Query(in.configType, replyTo)))
}
.collect { case Some(value) => value }
.drop(offset)
.take(in.size)
.runWith(Sink.seq)
.map(items => ConfigResponse(IntStatus.OK, data = Some(items)))

这个 Akka Streams 流即是分页处理的主要实现,若是SQL的话,它类似:

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select * from t_config where data_id like '%"in.dataId"%' offset "offset" limit "in.size"

.mapAsync 在流执行流程中起了20个并发的异步操作,将委托每个匹配的 ConfigEntity (由s"$namespace@$dataId"生成entityId)执行 config_type 字段的查询。这样,完整的SQL语句类似:

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select * from t_config where data_id like '%"in.dataId"%' and config_type = "in.configType" offset "offset" limit "in.size"
```

`ConfigEntity` 对 `config_type` 部分的查询逻辑实现如下:

```scala
case Query(configType, replyTo) =>
state.config match {
case None =>
Effect.reply(replyTo)(None)
case Some(config) =>
val resp = if (configType.forall(v => config.configType.contains(v))) Some(config) else None
Effect.reply(replyTo)(resp)
}

in.configType为空,既不需要判断 config_type 这个字段,直接返回 Some(config) 即可,而这时的SQL语句类似:

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select * from t_config where data_id like '%"in.dataId"%' and true offset "offset" limit "in.size"

Tip这里有个小技巧,对于 Option[T] 字段的判断,直接使用了 .forall 方法,它等价于:

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option match {
case Some(x) => p(x)
case None => true
}

小结

完整代码可在此 https://github.com/yangbajing/yangbajing-blog/tree/master/src/main/scala/blog/persistence/config 找到。