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FMKe: A realistic benchmark for key-value stores
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| 4.91 MB | Adobe PDF |
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Resumo(s)
Standard benchmarks are essential tools to evaluate and compare database management
systems in terms of relevant semantic properties and performance. They provide the
means to evaluate a system with workloads that mimic real applications. Although a number
of realistic benchmarks already exist for relational database systems, the same cannot
be said for NoSQL databases. This latter class of data storage systems has become increasingly
relevant for geo-distributed systems, and this has led developers and researchers to
either rely on benchmarks that do not model realistic workloads or to adapt the aforementioned
benchmarks for relational databases to work for NoSQL databases, in a somewhat
ad-hoc fashion. Since these benchmarks assume an isolation and transactional model in
the database, they are inherently inadequate to evaluate NoSQL databases.
In this thesis, we propose a new benchmark that addresses the lack of realistic evaluation
tools for distributed key-value stores. We consider a workload that is based on
information we have acquired about a real world deployment of a large-scale application
that operates over a distributed key-value store, that is responsible for managing
patient prescriptions at a nation-wide level in Denmark. We design our benchmark to
be extensible to a wide range of distributed key-value storage systems and some relational
database systems with minimal effort for programmers, which only need to design
and implement specific data storage drivers to benchmark different alternatives. We further
present a study on the performance of multiple database management systems in
different deployment scenarios.
Descrição
Palavras-chave
Benchmark Key-Value Store