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akka-docs/src/main/paradox/scala/cluster-sharding.md
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akka-docs/src/main/paradox/scala/cluster-sharding.md
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.. _cluster_sharding_scala:
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Cluster Sharding
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================
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Cluster sharding is useful when you need to distribute actors across several nodes in the cluster and want to
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be able to interact with them using their logical identifier, but without having to care about
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their physical location in the cluster, which might also change over time.
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It could for example be actors representing Aggregate Roots in Domain-Driven Design terminology.
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Here we call these actors "entities". These actors typically have persistent (durable) state,
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but this feature is not limited to actors with persistent state.
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Cluster sharding is typically used when you have many stateful actors that together consume
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more resources (e.g. memory) than fit on one machine. If you only have a few stateful actors
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it might be easier to run them on a :ref:`cluster-singleton-scala` node.
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In this context sharding means that actors with an identifier, so called entities,
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can be automatically distributed across multiple nodes in the cluster. Each entity
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actor runs only at one place, and messages can be sent to the entity without requiring
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the sender to know the location of the destination actor. This is achieved by sending
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the messages via a ``ShardRegion`` actor provided by this extension, which knows how
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to route the message with the entity id to the final destination.
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Cluster sharding will not be active on members with status :ref:`WeaklyUp <weakly_up_scala>`
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if that feature is enabled.
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.. warning::
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**Don't use Cluster Sharding together with Automatic Downing**,
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since it allows the cluster to split up into two separate clusters, which in turn will result
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in *multiple shards and entities* being started, one in each separate cluster!
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See :ref:`automatic-vs-manual-downing-java`.
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An Example
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----------
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This is how an entity actor may look like:
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.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#counter-actor
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The above actor uses event sourcing and the support provided in ``PersistentActor`` to store its state.
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It does not have to be a persistent actor, but in case of failure or migration of entities between nodes it must be able to recover
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its state if it is valuable.
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Note how the ``persistenceId`` is defined. The name of the actor is the entity identifier (utf-8 URL-encoded).
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You may define it another way, but it must be unique.
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When using the sharding extension you are first, typically at system startup on each node
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in the cluster, supposed to register the supported entity types with the ``ClusterSharding.start``
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method. ``ClusterSharding.start`` gives you the reference which you can pass along.
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.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#counter-start
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The ``extractEntityId`` and ``extractShardId`` are two application specific functions to extract the entity
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identifier and the shard identifier from incoming messages.
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.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#counter-extractor
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This example illustrates two different ways to define the entity identifier in the messages:
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* The ``Get`` message includes the identifier itself.
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* The ``EntityEnvelope`` holds the identifier, and the actual message that is
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sent to the entity actor is wrapped in the envelope.
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Note how these two messages types are handled in the ``extractEntityId`` function shown above.
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The message sent to the entity actor is the second part of the tuple return by the ``extractEntityId`` and that makes it
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possible to unwrap envelopes if needed.
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A shard is a group of entities that will be managed together. The grouping is defined by the
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``extractShardId`` function shown above. For a specific entity identifier the shard identifier must always
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be the same.
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Creating a good sharding algorithm is an interesting challenge in itself. Try to produce a uniform distribution,
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i.e. same amount of entities in each shard. As a rule of thumb, the number of shards should be a factor ten greater
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than the planned maximum number of cluster nodes. Less shards than number of nodes will result in that some nodes
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will not host any shards. Too many shards will result in less efficient management of the shards, e.g. rebalancing
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overhead, and increased latency because the coordinator is involved in the routing of the first message for each
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shard. The sharding algorithm must be the same on all nodes in a running cluster. It can be changed after stopping
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all nodes in the cluster.
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A simple sharding algorithm that works fine in most cases is to take the absolute value of the ``hashCode`` of
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the entity identifier modulo number of shards. As a convenience this is provided by the
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``ShardRegion.HashCodeMessageExtractor``.
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Messages to the entities are always sent via the local ``ShardRegion``. The ``ShardRegion`` actor reference for a
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named entity type is returned by ``ClusterSharding.start`` and it can also be retrieved with ``ClusterSharding.shardRegion``.
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The ``ShardRegion`` will lookup the location of the shard for the entity if it does not already know its location. It will
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delegate the message to the right node and it will create the entity actor on demand, i.e. when the
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first message for a specific entity is delivered.
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.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#counter-usage
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A more comprehensive sample is available in the
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tutorial named `Akka Cluster Sharding with Scala! <https://github.com/typesafehub/activator-akka-cluster-sharding-scala>`_.
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How it works
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------------
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The ``ShardRegion`` actor is started on each node in the cluster, or group of nodes
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tagged with a specific role. The ``ShardRegion`` is created with two application specific
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functions to extract the entity identifier and the shard identifier from incoming messages.
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A shard is a group of entities that will be managed together. For the first message in a
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specific shard the ``ShardRegion`` request the location of the shard from a central coordinator,
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the ``ShardCoordinator``.
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The ``ShardCoordinator`` decides which ``ShardRegion`` shall own the ``Shard`` and informs
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that ``ShardRegion``. The region will confirm this request and create the ``Shard`` supervisor
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as a child actor. The individual ``Entities`` will then be created when needed by the ``Shard``
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actor. Incoming messages thus travel via the ``ShardRegion`` and the ``Shard`` to the target
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``Entity``.
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If the shard home is another ``ShardRegion`` instance messages will be forwarded
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to that ``ShardRegion`` instance instead. While resolving the location of a
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shard incoming messages for that shard are buffered and later delivered when the
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shard home is known. Subsequent messages to the resolved shard can be delivered
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to the target destination immediately without involving the ``ShardCoordinator``.
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Scenario 1:
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#. Incoming message M1 to ``ShardRegion`` instance R1.
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#. M1 is mapped to shard S1. R1 doesn't know about S1, so it asks the coordinator C for the location of S1.
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#. C answers that the home of S1 is R1.
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#. R1 creates child actor for the entity E1 and sends buffered messages for S1 to E1 child
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#. All incoming messages for S1 which arrive at R1 can be handled by R1 without C. It creates entity children as needed, and forwards messages to them.
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Scenario 2:
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#. Incoming message M2 to R1.
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#. M2 is mapped to S2. R1 doesn't know about S2, so it asks C for the location of S2.
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#. C answers that the home of S2 is R2.
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#. R1 sends buffered messages for S2 to R2
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#. All incoming messages for S2 which arrive at R1 can be handled by R1 without C. It forwards messages to R2.
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#. R2 receives message for S2, ask C, which answers that the home of S2 is R2, and we are in Scenario 1 (but for R2).
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To make sure that at most one instance of a specific entity actor is running somewhere
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in the cluster it is important that all nodes have the same view of where the shards
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are located. Therefore the shard allocation decisions are taken by the central
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``ShardCoordinator``, which is running as a cluster singleton, i.e. one instance on
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the oldest member among all cluster nodes or a group of nodes tagged with a specific
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role.
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The logic that decides where a shard is to be located is defined in a pluggable shard
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allocation strategy. The default implementation ``ShardCoordinator.LeastShardAllocationStrategy``
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allocates new shards to the ``ShardRegion`` with least number of previously allocated shards.
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This strategy can be replaced by an application specific implementation.
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To be able to use newly added members in the cluster the coordinator facilitates rebalancing
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of shards, i.e. migrate entities from one node to another. In the rebalance process the
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coordinator first notifies all ``ShardRegion`` actors that a handoff for a shard has started.
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That means they will start buffering incoming messages for that shard, in the same way as if the
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shard location is unknown. During the rebalance process the coordinator will not answer any
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requests for the location of shards that are being rebalanced, i.e. local buffering will
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continue until the handoff is completed. The ``ShardRegion`` responsible for the rebalanced shard
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will stop all entities in that shard by sending the specified ``handOffStopMessage``
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(default ``PoisonPill``) to them. When all entities have been terminated the ``ShardRegion``
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owning the entities will acknowledge the handoff as completed to the coordinator.
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Thereafter the coordinator will reply to requests for the location of
|
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the shard and thereby allocate a new home for the shard and then buffered messages in the
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``ShardRegion`` actors are delivered to the new location. This means that the state of the entities
|
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are not transferred or migrated. If the state of the entities are of importance it should be
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persistent (durable), e.g. with :ref:`persistence-scala`, so that it can be recovered at the new
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location.
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|
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The logic that decides which shards to rebalance is defined in a pluggable shard
|
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allocation strategy. The default implementation ``ShardCoordinator.LeastShardAllocationStrategy``
|
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picks shards for handoff from the ``ShardRegion`` with most number of previously allocated shards.
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They will then be allocated to the ``ShardRegion`` with least number of previously allocated shards,
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i.e. new members in the cluster. There is a configurable threshold of how large the difference
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must be to begin the rebalancing. This strategy can be replaced by an application specific
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implementation.
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The state of shard locations in the ``ShardCoordinator`` is persistent (durable) with
|
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:ref:`distributed_data_scala` or :ref:`persistence-scala` to survive failures. When a crashed or
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unreachable coordinator node has been removed (via down) from the cluster a new ``ShardCoordinator`` singleton
|
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actor will take over and the state is recovered. During such a failure period shards
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with known location are still available, while messages for new (unknown) shards
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are buffered until the new ``ShardCoordinator`` becomes available.
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As long as a sender uses the same ``ShardRegion`` actor to deliver messages to an entity
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actor the order of the messages is preserved. As long as the buffer limit is not reached
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messages are delivered on a best effort basis, with at-most once delivery semantics,
|
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in the same way as ordinary message sending. Reliable end-to-end messaging, with
|
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at-least-once semantics can be added by using ``AtLeastOnceDelivery`` in :ref:`persistence-scala`.
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Some additional latency is introduced for messages targeted to new or previously
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unused shards due to the round-trip to the coordinator. Rebalancing of shards may
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also add latency. This should be considered when designing the application specific
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shard resolution, e.g. to avoid too fine grained shards.
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.. _cluster_sharding_mode_scala:
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Distributed Data vs. Persistence Mode
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-------------------------------------
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The state of the coordinator and the state of :ref:`cluster_sharding_remembering_scala` of the shards
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are persistent (durable) to survive failures. :ref:`distributed_data_scala` or :ref:`persistence-scala`
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can be used for the storage. Distributed Data is used by default.
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The functionality when using the two modes is the same. If your sharded entities are not using Akka Persistence
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themselves it is more convenient to use the Distributed Data mode, since then you don't have to
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setup and operate a separate data store (e.g. Cassandra) for persistence. Aside from that, there are
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no major reasons for using one mode over the the other.
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It's important to use the same mode on all nodes in the cluster, i.e. it's not possible to perform
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a rolling upgrade to change this setting.
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Distributed Data Mode
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^^^^^^^^^^^^^^^^^^^^^
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This mode is enabled with configuration (enabled by default)::
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akka.cluster.sharding.state-store-mode = ddata
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The state of the ``ShardCoordinator`` will be replicated inside a cluster by the
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:ref:`distributed_data_scala` module with ``WriteMajority``/``ReadMajority`` consistency.
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The state of the coordinator is not durable, it's not stored to disk. When all nodes in
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the cluster have been stopped the state is lost and not needed any more.
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The state of :ref:`cluster_sharding_remembering_scala` is also durable, i.e. it is stored to
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disk. The stored entities are started also after a complete cluster restart.
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Cluster Sharding is using its own Distributed Data ``Replicator`` per node role. In this way you can use a subset of
|
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all nodes for some entity types and another subset for other entity types. Each such replicator has a name
|
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that contains the node role and therefore the role configuration must be the same on all nodes in the
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cluster, i.e. you can't change the roles when performing a rolling upgrade.
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|
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The settings for Distributed Data is configured in the the section
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``akka.cluster.sharding.distributed-data``. It's not possible to have different
|
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``distributed-data`` settings for different sharding entity types.
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|
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Persistence Mode
|
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^^^^^^^^^^^^^^^^
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|
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This mode is enabled with configuration::
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akka.cluster.sharding.state-store-mode = persistence
|
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|
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Since it is running in a cluster :ref:`persistence-scala` must be configured with a distributed journal.
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|
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Startup after minimum number of members
|
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---------------------------------------
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|
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It's good to use Cluster Sharding with the Cluster setting ``akka.cluster.min-nr-of-members`` or
|
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``akka.cluster.role.<role-name>.min-nr-of-members``. That will defer the allocation of the shards
|
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until at least that number of regions have been started and registered to the coordinator. This
|
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avoids that many shards are allocated to the first region that registers and only later are
|
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rebalanced to other nodes.
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|
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See :ref:`min-members_scala` for more information about ``min-nr-of-members``.
|
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|
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Proxy Only Mode
|
||||
---------------
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|
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The ``ShardRegion`` actor can also be started in proxy only mode, i.e. it will not
|
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host any entities itself, but knows how to delegate messages to the right location.
|
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A ``ShardRegion`` is started in proxy only mode with the method ``ClusterSharding.startProxy``
|
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method.
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Passivation
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-----------
|
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|
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If the state of the entities are persistent you may stop entities that are not used to
|
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reduce memory consumption. This is done by the application specific implementation of
|
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the entity actors for example by defining receive timeout (``context.setReceiveTimeout``).
|
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If a message is already enqueued to the entity when it stops itself the enqueued message
|
||||
in the mailbox will be dropped. To support graceful passivation without losing such
|
||||
messages the entity actor can send ``ShardRegion.Passivate`` to its parent ``Shard``.
|
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The specified wrapped message in ``Passivate`` will be sent back to the entity, which is
|
||||
then supposed to stop itself. Incoming messages will be buffered by the ``Shard``
|
||||
between reception of ``Passivate`` and termination of the entity. Such buffered messages
|
||||
are thereafter delivered to a new incarnation of the entity.
|
||||
|
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.. _cluster_sharding_remembering_scala:
|
||||
|
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Remembering Entities
|
||||
--------------------
|
||||
|
||||
The list of entities in each ``Shard`` can be made persistent (durable) by setting
|
||||
the ``rememberEntities`` flag to true in ``ClusterShardingSettings`` when calling
|
||||
``ClusterSharding.start``. When configured to remember entities, whenever a ``Shard``
|
||||
is rebalanced onto another node or recovers after a crash it will recreate all the
|
||||
entities which were previously running in that ``Shard``. To permanently stop entities,
|
||||
a ``Passivate`` message must be sent to the parent of the entity actor, otherwise the
|
||||
entity will be automatically restarted after the entity restart backoff specified in
|
||||
the configuration.
|
||||
|
||||
When :ref:`Distributed Data mode <cluster_sharding_mode_scala>` is used the identifiers of the entities are
|
||||
stored in :ref:`ddata_durable_scala` of Distributed Data. You may want to change the
|
||||
configuration of the akka.cluster.sharding.distributed-data.durable.lmdb.dir`, since
|
||||
the default directory contains the remote port of the actor system. If using a dynamically
|
||||
assigned port (0) it will be different each time and the previously stored data will not
|
||||
be loaded.
|
||||
|
||||
When ``rememberEntities`` is set to false, a ``Shard`` will not automatically restart any entities
|
||||
after a rebalance or recovering from a crash. Entities will only be started once the first message
|
||||
for that entity has been received in the ``Shard``. Entities will not be restarted if they stop without
|
||||
using a ``Passivate``.
|
||||
|
||||
Note that the state of the entities themselves will not be restored unless they have been made persistent,
|
||||
e.g. with :ref:`persistence-scala`.
|
||||
|
||||
The performance cost of ``rememberEntities`` is rather high when starting/stopping entities and when
|
||||
shards are rebalanced. This cost increases with number of entities per shard and we currently don't
|
||||
recommend using it with more than 10000 entities per shard.
|
||||
|
||||
Supervision
|
||||
-----------
|
||||
|
||||
If you need to use another ``supervisorStrategy`` for the entity actors than the default (restarting) strategy
|
||||
you need to create an intermediate parent actor that defines the ``supervisorStrategy`` to the
|
||||
child entity actor.
|
||||
|
||||
.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#supervisor
|
||||
|
||||
You start such a supervisor in the same way as if it was the entity actor.
|
||||
|
||||
.. includecode:: ../../../akka-cluster-sharding/src/multi-jvm/scala/akka/cluster/sharding/ClusterShardingSpec.scala#counter-supervisor-start
|
||||
|
||||
Note that stopped entities will be started again when a new message is targeted to the entity.
|
||||
|
||||
Graceful Shutdown
|
||||
-----------------
|
||||
|
||||
You can send the message ``ShardRegion.GracefulShutdown`` message to the ``ShardRegion`` actor to handoff all shards that are hosted by that ``ShardRegion`` and then the
|
||||
``ShardRegion`` actor will be stopped. You can ``watch`` the ``ShardRegion`` actor to know when it is completed.
|
||||
During this period other regions will buffer messages for those shards in the same way as when a rebalance is
|
||||
triggered by the coordinator. When the shards have been stopped the coordinator will allocate these shards elsewhere.
|
||||
|
||||
This is performed automatically by the :ref:`coordinated-shutdown-scala` and is therefore part of the
|
||||
graceful leaving process of a cluster member.
|
||||
|
||||
.. _RemoveInternalClusterShardingData-scala:
|
||||
|
||||
Removal of Internal Cluster Sharding Data
|
||||
-----------------------------------------
|
||||
|
||||
The Cluster Sharding coordinator stores the locations of the shards using Akka Persistence.
|
||||
This data can safely be removed when restarting the whole Akka Cluster.
|
||||
Note that this is not application data.
|
||||
|
||||
There is a utility program ``akka.cluster.sharding.RemoveInternalClusterShardingData``
|
||||
that removes this data.
|
||||
|
||||
.. warning::
|
||||
|
||||
Never use this program while there are running Akka Cluster nodes that are
|
||||
using Cluster Sharding. Stop all Cluster nodes before using this program.
|
||||
|
||||
It can be needed to remove the data if the Cluster Sharding coordinator
|
||||
cannot startup because of corrupt data, which may happen if accidentally
|
||||
two clusters were running at the same time, e.g. caused by using auto-down
|
||||
and there was a network partition.
|
||||
|
||||
.. warning::
|
||||
**Don't use Cluster Sharding together with Automatic Downing**,
|
||||
since it allows the cluster to split up into two separate clusters, which in turn will result
|
||||
in *multiple shards and entities* being started, one in each separate cluster!
|
||||
See :ref:`automatic-vs-manual-downing-scala`.
|
||||
|
||||
Use this program as a standalone Java main program::
|
||||
|
||||
java -classpath <jar files, including akka-cluster-sharding>
|
||||
akka.cluster.sharding.RemoveInternalClusterShardingData
|
||||
-2.3 entityType1 entityType2 entityType3
|
||||
|
||||
The program is included in the ``akka-cluster-sharding`` jar file. It
|
||||
is easiest to run it with same classpath and configuration as your ordinary
|
||||
application. It can be run from sbt or maven in similar way.
|
||||
|
||||
Specify the entity type names (same as you use in the ``start`` method
|
||||
of ``ClusterSharding``) as program arguments.
|
||||
|
||||
If you specify ``-2.3`` as the first program argument it will also try
|
||||
to remove data that was stored by Cluster Sharding in Akka 2.3.x using
|
||||
different persistenceId.
|
||||
|
||||
Dependencies
|
||||
------------
|
||||
|
||||
To use the Cluster Sharding you must add the following dependency in your project.
|
||||
|
||||
sbt::
|
||||
|
||||
"com.typesafe.akka" %% "akka-cluster-sharding" % "@version@" @crossString@
|
||||
|
||||
maven::
|
||||
|
||||
<dependency>
|
||||
<groupId>com.typesafe.akka</groupId>
|
||||
<artifactId>akka-cluster-sharding_@binVersion@</artifactId>
|
||||
<version>@version@</version>
|
||||
</dependency>
|
||||
|
||||
Configuration
|
||||
-------------
|
||||
|
||||
The ``ClusterSharding`` extension can be configured with the following properties. These configuration
|
||||
properties are read by the ``ClusterShardingSettings`` when created with a ``ActorSystem`` parameter.
|
||||
It is also possible to amend the ``ClusterShardingSettings`` or create it from another config section
|
||||
with the same layout as below. ``ClusterShardingSettings`` is a parameter to the ``start`` method of
|
||||
the ``ClusterSharding`` extension, i.e. each each entity type can be configured with different settings
|
||||
if needed.
|
||||
|
||||
.. includecode:: ../../../akka-cluster-sharding/src/main/resources/reference.conf#sharding-ext-config
|
||||
|
||||
Custom shard allocation strategy can be defined in an optional parameter to
|
||||
``ClusterSharding.start``. See the API documentation of ``ShardAllocationStrategy`` for details of
|
||||
how to implement a custom shard allocation strategy.
|
||||
|
||||
|
||||
Inspecting cluster sharding state
|
||||
---------------------------------
|
||||
Two requests to inspect the cluster state are available:
|
||||
|
||||
``ShardRegion.GetShardRegionState`` which will return a ``ShardRegion.CurrentShardRegionState`` that contains
|
||||
the identifiers of the shards running in a Region and what entities are alive for each of them.
|
||||
|
||||
``ShardRegion.GetClusterShardingStats`` which will query all the regions in the cluster and return
|
||||
a ``ShardRegion.ClusterShardingStats`` containing the identifiers of the shards running in each region and a count
|
||||
of entities that are alive in each shard.
|
||||
|
||||
The purpose of these messages is testing and monitoring, they are not provided to give access to
|
||||
directly sending messages to the individual entities.
|
||||
Loading…
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Reference in a new issue