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A novel causally consistent replication protocol with partial geo-replication
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Resumo(s)
Distributed storage systems are a fundamental component of large-scale Internet services.
To keep up with the increasing expectations of users regarding availability and latency,
the design of data storage systems has evolved to achieve these properties, by exploiting
techniques such as partial replication, geo-replication and weaker consistency models.
While systems with these characteristics exist, they usually do not provide all these
properties or do so in an inefficient manner, not taking full advantage of them. Additionally,
weak consistency models, such as eventual consistency, put an excessively high
burden on application programmers for writing correct applications, and hence, multiple
systems have moved towards providing additional consistency guarantees such as
implementing the causal (and causal+) consistency models.
In this thesis we approach the existing challenges in designing a causally consistent
replication protocol, with a focus on the use of geo and partial data replication. To this
end, we present a novel replication protocol, capable of enriching an existing geo and
partially replicated datastore with the causal+ consistency model.
In addition, this thesis also presents a concrete implementation of the proposed protocol
over the popular Cassandra datastore system. This implementation is complemented
with experimental results obtained in a realistic scenario, in which we compare our proposal
withmultiple configurations of the Cassandra datastore (without causal consistency
guarantees) and with other existing alternatives. The results show that our proposed solution
is able to achieve a balanced performance, with low data visibility delays and without
significant performance penalties.
Descrição
Palavras-chave
Distributed datastore systems causal+ consistency geo-replication partial replication