During a cache’s lifecycle it is possible for inconsistencies to appear between replicas of a cache entry  due to a variety of reasons (e.g replication failures, incorrect use of flags etc).  The conflict manager is a tool that allows users to retrieve all stored replica values for a cache entry. In addition to allowing users to process a stream of cache entries whose stored replicas have conflicting values. Furthermore, by utilising implementations of the EntryMergePolicy interface it is possible for said conflicts to be resolved deterministically.

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In 9.1.0.Final the partition handling enabled/disabled option has been deprecated and users must now configure an appropriate PartitionHandling strategy for their application. A partition handling strategy determines what operations can be performed on a cache when a split brain event has occurred. Ultimately, in terms of Brewer’s CAP theorem, the configured strategy determines whether the cache’s availability or consistency is sacrificed in the presence of partition(s). Below is a table of the provided strategies and their characteristics:

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You are happily running a 10-node cluster. You want failover and speed and are using distributed mode with 2 copies of data for each key (numOwners=2). But disaster strikes: a switch in your network crashes and 5 of your nodes can’t reach the other 5 anymore ! Now there are two independent clusters, each containing 5 nodes, which we are smartly going to name P1 and P2. Both P1 and P2 continue to serve user requests (puts and gets) as usual.

This cluster split in two or more parts is called partitioning or split brain. And it’s bad for business, as in really bad ! Bob and Alice share a bank account stored in the cache. Bob updates his account on P1, then Alice reads it from P2: she sees a stale value of Bob’s account (or even no value for Bob’s account, depending on how the split looks like). This is a consistency issue, as there’s an inconsistent view of the data between the two partitions.

In Infinispan 7.0.0.Beta1 we added support for reacting to split brains: if nodes leave, Infinispan acknowledges that data might have been lost and denies user access to such data. We won’t deny access to all the data, but just the data that might have been affected by the partitioning. Or, more formally: Infinispan sacrifices data availability in order to offer consistency (PC in Brewer’s CAP theorem). For now partition handling is disabled by default, however we do intend to make it the default in an upcoming release: running with partition handling off is like running with scissors: do it at your own risk and only if you (don’t) know what you’re doing.

A partition is assumed to happen when numOwners or more nodes disappear at the same time. When this happen two (or more) partitions form which are not aware of each other. Each such partition does not start a rebalance, but enters in degraded mode:

To exemplify, consider the initial cluster C0=\{A,B,C,D}, A,B,C,D - nodes, configured in distributed mode with numOwners=2. Further on, the cluster contains k1, k2 and k3 keys such that owners(k1) = \{A,B}, owners(k2) = \{B,C} and owners(k3) = \{C,D}. Then a partition happens C1=\{A,B} and C2=\{C,D}, the degraded mode exhibits the following behavior:

A relevant aspect of the partition handling process is the fact that when a split brain happens, the resulting partitions rely on the original consistent hash function (the one that existed before the split brain) in order to calculate key ownership. So it doesn’t matter if k1, k2 or k3 already exists in the cluster or not, as the availability is strictly determined by the consistent hash and not by the key existence.

If at a further point in time the initial partition C0 forms again as a result of the network healing and C1 and C2 partitions being merged back together, then C0 exists the degraded mode becoming fully available again.