Hot Rod Remote Events #4: Clustering and Failover
This blog post is the last in a series that looks at the forthcoming Hot Rod Remote Events functionality included in Infinispan 7.0. First article focused on how to get started receiving remote events from Hot Rod servers. The second article looked at how Hot Rod remote events can be filtered, and the third one showed how to customize contents of events.
In this last article, we’ll be focusing on how remote events are fired in a clustered environment and how failover situations are dealt with.
The most important thing to know about remote events in a clustered environment is that when a client adds a remote listener, this is installed in a single node in the cluster and that this node is in charge of sending events back to the client for all affected operations happening cluster wide.
As a result of this, when filtering or event customization is applied, the org.infinispan.notifications.cachelistener.filter.CacheEventFilter and/or org.infinispan.notifications.cachelistener.filter.CacheEventConverter instances must be somehow marshallable. This is necessary because when the client listener is installed in a cluster, the filter and/or converter instances are sent to other nodes in the cluster so that filtering and conversion can happen right where the event originates, hence improving efficiency. These classes can be made marshallable by making them extend Serializable, or providing and registering a custom Externalizer for them.
Under normal circumstances, the code and examples showed in previous blog posts work the same way in clustered environment. However, in a clustered environment, a decision needs to be made with regards to how to deal with situations where nodes go down: If a node goes down that does not have the client listener installed, nothing happens. However, when the node containing the client listener goes down, the Hot Rod client implementation transparently fails over the client listener registration to a different node. As a result of this failover, there could be a gap in the event consumption. This gap is solved using one of these solutions:
The @ClientListener annotation has an optional parameter called includeCurrentState. When this is enabled and the client listener is registered, before receiving any events for on-going operations, the server sends ClientCacheEntryCreatedEvent event instances (for methods annotated with @ClientCacheEntryCreated) for all existing cache entries to the client. This offers the client an opportunity to construct some state or computation based on the contents of the clustered cache. When the Hot Rod client transparently fails over registered listeners, it re-registers them in a different node and if includeCurrentState is enabled, clients can recompute their state or computation to reinstate it to what it was before the failover. The downside of includeCurrentState is that it’s performance is heavily dependant on the cache size, and hence it’s disabled by default.
Alternatively, instead of relying on receiving state, users can define a method with @ClientCacheFailover annotation that receives ClientCacheFailoverEvent as parameter inside the client listener implementation:
This method would be called back whenever the node that had this client listener has gone down. This can be handy for situations when the end users just wants to clear up some local state as a result of the failover, e.g. clear a near or L1 cache. When events are received again, the near or L1 cache could be repopulated again.
This callback method of dealing with client listener failover offers a simple, efficient solution to dealing with cluster topology changes affecting client listeners. Depending on the remote event use case, this method might be better suited that state delivery.
This post marks the end of the remote event series. In future Infinispan versions, we’ll continue improving the technology adding some extra features, and more importantly, we’ll start building higher level abstractions on top of remote events, such as Hot Rod client Near Caches.
Get it, Use it, Ask us!We’re hard at work on new features, improvements and fixes, so watch this space for more announcements!
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