final class Replicator extends Actor with ActorLogging
- Alphabetic
- By Inheritance
- Replicator
- ActorLogging
- Actor
- AnyRef
- Any
- by any2stringadd
- by StringFormat
- by Ensuring
- by ArrowAssoc
- Hide All
- Show All
- Public
- Protected
Instance Constructors
- new Replicator(settings: ReplicatorSettings)
Value Members
- var allReachableClockTime: Long
- var changed: [KeyId]
- val clockTask: Cancellable
- val cluster: Cluster
- def collectRemovedNodes(): Unit
- implicit val context: ActorContext
Scala API: Stores the context for this actor, including self, and sender.
Scala API: Stores the context for this actor, including self, and sender. It is implicit to support operations such as
forward
.WARNING: Only valid within the Actor itself, so do not close over it and publish it to other threads!
akka.actor.ActorContext is the Scala API.
getContext
returns a akka.actor.AbstractActor.ActorContext, which is the Java API of the actor context.- Definition Classes
- Actor
- var dataEntries: [KeyId, (DataEnvelope, Digest, Timestamp)]
- def deleteObsoletePruningPerformed(): Unit
- val deltaPropagationSelector: DeltaPropagationSelector { val gossipIntervalDivisor: Int }
- val deltaPropagationTask: [Cancellable]
- def digest(envelope: DataEnvelope): (Digest, Int)
- returns
SHA-1 digest of the serialized data, and the size of the serialized data
- val durable: [KeyId]
- val durableStore: ActorRef
- val durableWildcards: [KeyId]
- var exitingNodes: [UniqueAddress]
- val expiryEnabled: Boolean
- val expiryWildcards: [, FiniteDuration]
- var fullStateGossipEnabled: Boolean
- def getData(key: KeyId): Option[DataEnvelope]
- def getDeltaSeqNr(key: KeyId, fromNode: UniqueAddress): Long
- def getDigest(key: KeyId): Digest
- def getExpiryDuration(key: KeyId): FiniteDuration
- def getUsedTimestamp(key: KeyId): Timestamp
- val gossipTask: Cancellable
- def gossipTo(address: UniqueAddress): Unit
- val hasDurableKeys: Boolean
- def hasSubscriber(subscriber: ActorRef): Boolean
- def initRemovedNodePruning(): Unit
- def isDurable(key: KeyId): Boolean
- def isExpired(key: KeyId, timestamp: Timestamp): Boolean
- def isExpired(key: KeyId): Boolean
- def isLeader: Boolean
- def isLocalGet(readConsistency: ReadConsistency): Boolean
- def isLocalSender(): Boolean
- def isLocalUpdate(writeConsistency: WriteConsistency): Boolean
- def isNodeRemoved(node: UniqueAddress, keys: Iterable[KeyId]): Boolean
- var joiningNodes: [UniqueAddress]
- var leader: [Member]
- val load: Receive
- def log: LoggingAdapter
- Definition Classes
- ActorLogging
- def matchingRole(m: Member): Boolean
- val maxPruningDisseminationNanos: Long
- var membersByAge: [Member]
- val newSubscribers: [, []] with [, ActorRef]
- var nodes: [UniqueAddress]
- val normalReceive: Receive
- val notifyTask: Cancellable
- def performRemovedNodePruning(): Unit
- def postRestart(reason: Throwable): Unit
User overridable callback: By default it calls
preStart()
.User overridable callback: By default it calls
preStart()
.- reason
the Throwable that caused the restart to happen Is called right AFTER restart on the newly created Actor to allow reinitialization after an Actor crash.
- Definition Classes
- Actor
- Annotations
- @throws(classOf[Exception])
- def postStop(): Unit
User overridable callback.
User overridable callback.
Is called asynchronously after 'actor.stop()' is invoked. Empty default implementation.
- Definition Classes
- → Actor
- def preRestart(reason: Throwable, message: [Any]): Unit
Scala API: User overridable callback: By default it disposes of all children and then calls
postStop()
.Scala API: User overridable callback: By default it disposes of all children and then calls
postStop()
.- reason
the Throwable that caused the restart to happen
- message
optionally the current message the actor processed when failing, if applicable Is called on a crashed Actor right BEFORE it is restarted to allow clean up of resources before Actor is terminated.
- Definition Classes
- Actor
- Annotations
- @throws(classOf[Exception])
- def preStart(): Unit
User overridable callback.
User overridable callback.
Is called when an Actor is started. Actors are automatically started asynchronously when created. Empty default implementation.
- Definition Classes
- → Actor
- var previousClockTime: Long
- val pruningTask: [Cancellable]
- def receive: actor.Actor.Receive
Scala API: This defines the initial actor behavior, it must return a partial function with the actor logic.
Scala API: This defines the initial actor behavior, it must return a partial function with the actor logic.
- Definition Classes
- → Actor
- def receiveClockTick(): Unit
- def receiveDelete(key: KeyR, consistency: WriteConsistency, req: [Any]): Unit
- def receiveDeltaPropagation(fromNode: UniqueAddress, reply: Boolean, deltas: Map[KeyId, Delta]): Unit
- def receiveDeltaPropagationTick(): Unit
- def receiveFlushChanges(): Unit
- def receiveGet(key: KeyR, consistency: ReadConsistency, req: [Any]): Unit
- def receiveGetKeyIds(): Unit
- def receiveGetReplicaCount(): Unit
- def receiveGossip(updatedData: Map[KeyId, (DataEnvelope, Timestamp)], sendBack: Boolean, fromSystemUid: [Long]): Unit
- def receiveGossipTick(): Unit
- def receiveMemberExiting(m: Member): Unit
- def receiveMemberJoining(m: Member): Unit
- def receiveMemberRemoved(m: Member): Unit
- def receiveMemberUp(m: Member): Unit
- def receiveMemberWeaklyUp(m: Member): Unit
- def receiveOtherMemberEvent(m: Member): Unit
- def receiveReachable(m: Member): Unit
- def receiveRead(key: KeyId): Unit
- def receiveReadRepair(key: KeyId, writeEnvelope: DataEnvelope): Unit
- def receiveRemovedNodePruningTick(): Unit
- def receiveStatus(otherDigests: Map[KeyId, (Digest, Timestamp)], chunk: Int, totChunks: Int, fromSystemUid: [Long]): Unit
- def receiveSubscribe(key: KeyR, subscriber: ActorRef): Unit
- def receiveTerminated(ref: ActorRef): Unit
- def receiveUnreachable(m: Member): Unit
- def receiveUnsubscribe(key: KeyR, subscriber: ActorRef): Unit
- def receiveUpdate[A <: ReplicatedData](key: KeyR, modify: (Option[A]) => A, writeConsistency: WriteConsistency, req: [Any]): Unit
- def receiveWrite(key: KeyId, envelope: DataEnvelope): Unit
- var removedNodes: Map[, Long]
- def replica(node: UniqueAddress): ActorSelection
- var replyTo: ActorRef
- def selectRandomNode(addresses: [UniqueAddress]): [UniqueAddress]
- implicit final val self: ActorRef
The 'self' field holds the ActorRef for this actor.
The 'self' field holds the ActorRef for this actor.
Can be used to send messages to itself:
self ! message
- Definition Classes
- Actor
- val selfAddress: Address
- val selfFromSystemUid: [Long]
- val selfUniqueAddress: UniqueAddress
- final def sender(): ActorRef
The reference sender Actor of the last received message.
The reference sender Actor of the last received message. Is defined if the message was sent from another Actor, else
deadLetters
in akka.actor.ActorSystem.WARNING: Only valid within the Actor itself, so do not close over it and publish it to other threads!
- Definition Classes
- Actor
- val serializer: Serializer
- def setData(key: KeyId, envelope: DataEnvelope): DataEnvelope
- var statusCount: Long
- var statusTotChunks: Int
- val subscribers: [, []] with [, ActorRef]
- var subscriptionKeys: [KeyId, KeyR]
- val supervisorStrategy: OneForOneStrategy
User overridable definition the strategy to use for supervising child actors.
User overridable definition the strategy to use for supervising child actors.
- Definition Classes
- → Actor
- def unhandled(message: Any): Unit
User overridable callback.
User overridable callback.
Is called when a message isn't handled by the current behavior of the actor by default it fails with either a (in case of an unhandled message) or publishes an to the actor's system's akka.event.EventStream
- Definition Classes
- Actor
- var unreachable: [UniqueAddress]
- def updateUsedTimestamp(key: KeyId, timestamp: Timestamp): Unit
- var weaklyUpNodes: [UniqueAddress]
- val wildcardSubscribers: [, []] with [, ActorRef]
- def write(key: KeyId, writeEnvelope: DataEnvelope): Option[DataEnvelope]
- def writeAndStore(key: KeyId, writeEnvelope: DataEnvelope, reply: Boolean): Unit
A replicated in-memory data store supporting low latency and high availability requirements.
The
Replicator
actor takes care of direct replication and gossip based dissemination of Conflict Free Replicated Data Types (CRDTs) to replicas in the the cluster. The data types must be convergent CRDTs and implement ReplicatedData, i.e. they provide a monotonic merge function and the state changes always converge.You can use your own custom ReplicatedData or DeltaReplicatedData types, and several types are provided by this package, such as:
For good introduction to the CRDT subject watch the Eventually Consistent Data Structures talk by Sean Cribbs and and the talk by Mark Shapiro and read the excellent paper A comprehensive study of Convergent and Commutative Replicated Data Types by Mark Shapiro et. al.
The
Replicator
actor must be started on each node in the cluster, or group of nodes tagged with a specific role. It communicates with otherReplicator
instances with the same path (without address) that are running on other nodes . For convenience it can be used with the DistributedData extension but it can also be started as an ordinary actor using theReplicator.props
. If it is started as an ordinary actor it is important that it is given the same name, started on same path, on all nodes.Delta State Replicated Data Types are supported. delta-CRDT is a way to reduce the need for sending the full state for updates. For example adding element 'c' and 'd' to set {'a', 'b'} would result in sending the delta {'c', 'd'} and merge that with the state on the receiving side, resulting in set {'a', 'b', 'c', 'd'}.
The protocol for replicating the deltas supports causal consistency if the data type is marked with RequiresCausalDeliveryOfDeltas. Otherwise it is only eventually consistent. Without causal consistency it means that if elements 'c' and 'd' are added in two separate
Update
operations these deltas may occasionally be propagated to nodes in different order than the causal order of the updates. For this example it can result in that set {'a', 'b', 'd'} can be seen before element 'c' is seen. Eventually it will be {'a', 'b', 'c', 'd'}.Update
To modify and replicate a ReplicatedData value you send a Replicator.Update message to the local
Replicator
. The current data value for thekey
of theUpdate
is passed as parameter to themodify
function of theUpdate
. The function is supposed to return the new value of the data, which will then be replicated according to the given consistency level.The
modify
function is called by theReplicator
actor and must therefore be a pure function that only uses the data parameter and stable fields from enclosing scope. It must for example not accesssender()
reference of an enclosing actor.Update
is intended to only be sent from an actor running in same localActorSystem
as theReplicator
, because themodify
function is typically not serializable.You supply a write consistency level which has the following meaning:
WriteLocal
the value will immediately only be written to the local replica, and later disseminated with gossipWriteTo(n)
the value will immediately be written to at leastn
replicas, including the local replicaWriteMajority
the value will immediately be written to a majority of replicas, i.e. at leastN/2 + 1
replicas, where N is the number of nodes in the cluster (or cluster role group)WriteAll
the value will immediately be written to all nodes in the cluster (or all nodes in the cluster role group)As reply of the
Update
a Replicator.UpdateSuccess is sent to the sender of theUpdate
if the value was successfully replicated according to the supplied consistency level within the supplied timeout. Otherwise a Replicator.UpdateFailure subclass is sent back. Note that a Replicator.UpdateTimeout reply does not mean that the update completely failed or was rolled back. It may still have been replicated to some nodes, and will eventually be replicated to all nodes with the gossip protocol.You will always see your own writes. For example if you send two
Update
messages changing the value of the samekey
, themodify
function of the second message will see the change that was performed by the firstUpdate
message.In the
Update
message you can pass an optional request context, which theReplicator
does not care about, but is included in the reply messages. This is a convenient way to pass contextual information (e.g. original sender) without having to useask
or local correlation data structures.Get
To retrieve the current value of a data you send Replicator.Get message to the
Replicator
. You supply a consistency level which has the following meaning:ReadLocal
the value will only be read from the local replicaReadFrom(n)
the value will be read and merged fromn
replicas, including the local replicaReadMajority
the value will be read and merged from a majority of replicas, i.e. at leastN/2 + 1
replicas, where N is the number of nodes in the cluster (or cluster role group)ReadAll
the value will be read and merged from all nodes in the cluster (or all nodes in the cluster role group)As reply of the
Get
a Replicator.GetSuccess is sent to the sender of theGet
if the value was successfully retrieved according to the supplied consistency level within the supplied timeout. Otherwise a Replicator.GetFailure is sent. If the key does not exist the reply will be Replicator.NotFound.You will always read your own writes. For example if you send a
Update
message followed by aGet
of the samekey
theGet
will retrieve the change that was performed by the precedingUpdate
message. However, the order of the reply messages are not defined, i.e. in the previous example you may receive theGetSuccess
before theUpdateSuccess
.In the
Get
message you can pass an optional request context in the same way as for theUpdate
message, described above. For example the original sender can be passed and replied to after receiving and transformingGetSuccess
.Subscribe
You may also register interest in change notifications by sending Replicator.Subscribe message to the
Replicator
. It will send Replicator.Changed messages to the registered subscriber when the data for the subscribed key is updated. Subscribers will be notified periodically with the configurednotify-subscribers-interval
, and it is also possible to send an explicitReplicator.FlushChanges
message to theReplicator
to notify the subscribers immediately.The subscriber is automatically removed if the subscriber is terminated. A subscriber can also be deregistered with the Replicator.Unsubscribe message.
Delete
A data entry can be deleted by sending a Replicator.Delete message to the local local
Replicator
. As reply of theDelete
a Replicator.DeleteSuccess is sent to the sender of theDelete
if the value was successfully deleted according to the supplied consistency level within the supplied timeout. Otherwise a Replicator.ReplicationDeleteFailure is sent. Note thatReplicationDeleteFailure
does not mean that the delete completely failed or was rolled back. It may still have been replicated to some nodes, and may eventually be replicated to all nodes.A deleted key cannot be reused again, but it is still recommended to delete unused data entries because that reduces the replication overhead when new nodes join the cluster. Subsequent
Delete
,Update
andGet
requests will be replied with Replicator.DataDeleted, Replicator.UpdateDataDeleted and Replicator.GetDataDeleted respectively. Subscribers will receive Replicator.Deleted.In the
Delete
message you can pass an optional request context in the same way as for theUpdate
message, described above. For example the original sender can be passed and replied to after receiving and transformingDeleteSuccess
.CRDT Garbage
One thing that can be problematic with CRDTs is that some data types accumulate history (garbage). For example a
GCounter
keeps track of one counter per node. If aGCounter
has been updated from one node it will associate the identifier of that node forever. That can become a problem for long running systems with many cluster nodes being added and removed. To solve this problem theReplicator
performs pruning of data associated with nodes that have been removed from the cluster. Data types that need pruning have to implement RemovedNodePruning. The pruning consists of several steps:maxPruningDissemination
duration has elapsed. The time measurement is stopped when any replica is unreachable, but it's still recommended to configure this with certain margin. It should be in the magnitude of minutes.PruningInitialized
marker in the data envelope. This is gossiped to all other nodes and they mark it as seen when they receive it.PruningInitialized
marker the leader performs the pruning and changes the marker toPruningPerformed
so that nobody else will redo the pruning. The data envelope with this pruning state is a CRDT itself. The pruning is typically performed by "moving" the part of the data associated with the removed node to the leader node. For example, aGCounter
is aMap
with the node as key and the counts done by that node as value. When pruning the value of the removed node is moved to the entry owned by the leader node. See RemovedNodePruning#prune.maxPruningDissemination
duration after pruning the last entry from the removed node thePruningPerformed
markers in the data envelope are collapsed into a single tombstone entry, for efficiency. Clients may continue to use old data and therefore all data are always cleared from parts associated with tombstoned nodes.