JoinVision’s clustering technology for Matchpoint
Have we ever talked to you about the innovative clustering technology that we use for our HR-matching platform “Matchpoint”? Not until now? Then it is high time to catch up on this issue. Thanks to our clustering technology, our matching engine MatchPoint scales with an arbitrary number of job offers and CVs, providing, at the same time, a high degree of redundancy.
How is that realized? By means of an intelligent, parallelized algorithm which, while working in the background, permanently exchanges messages about the states of the particular instances as well as semantic objects via Message Oriented Middleware (MOM). Depending on the degree of utilization, this process allows to balance both the CPU and the memory and leads to an optimal distribution of the load
New instances can be either integrated or excluded on-the-fly and automatically optimize themselves, whereby high fail-safety is ensured. As soon as a new instance is started, it is integrated into a cluster and begins to manage a suitable part of the semantic objects of the overall system. In addition, and provided that the CPU has enough resources, import requests are being transferred to the new instance to enhance the overall performance of the system. If an instance is excluded or if it fails, other cluster nodes are automatically compensating the data loss. This is made possible by the redundant storage of all existing semantic objects, thus each semantic object has, at least on one other instance, a corresponding backup object.
Through the use of MOM with an embedded broker, i.e. the messaging server works in the same JVM as MatchPoint itself, installation and configuration efforts are reduced to a minimum. MatchPoint consequently remains completely maintenance-free and very efficient, even if it is part of a cluster network.
Having developed this breakthrough technology, JoinVision is the first provider worldwide to exceed the limits of semantic matching, paving the way for unlimited robot recruiting.
