References of "Almeida, Eduardo Cunha de"
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See detailA PetriNet Mechanism for OLAP in NUMA
Dominico, Simone; Almeida, Eduardo Cunha de; Meira, Jorge Augusto UL

Poster (2017, May 15)

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See detailUnder Pressure Benchmark for DDBMS Availability
Fior, Alessandro Gustavo; Meira, Jorge Augusto UL; Almeida, Eduardo Cunha de et al

in Journal of Information and Data Management (2013)

The availability of Distributed Database Management Systems (DDBMS) is related to the probability of being up and running at a given point in time and to the management of failures. One well-known and ... [more ▼]

The availability of Distributed Database Management Systems (DDBMS) is related to the probability of being up and running at a given point in time and to the management of failures. One well-known and widely used mechanism to ensure availability is replication, which includes performance impact on maintaining data replicas across the DDBMS’s machine nodes. Benchmarking can be used to measure such impact. In this article, we present a benchmark that evaluates the performance of DDBMS, considering availability through replication, called Under Pressure Benchmark (UPB). The UPB measures performance with different degrees of replication upon a high-throughput distributed workload, combined with failures. The UPB methodology increases the evaluation complexity from a stable system scenario to a complex one with different load sizes and replicas. We validate our benchmark with three high-throughput in-memory DDBMS: VoltDB, NuoDB and Dbms-X. [less ▲]

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See detailStress Testing of Transactional Database Systems
Meira, Jorge Augusto UL; Almeida, Eduardo Cunha de; Sunyé, Gerson et al

in Journal of Information and Data Management (2013)

Transactional database management systems (DBMS) have been successful at supporting traditional transaction processing workloads. However, web-based applications that tend to generate huge numbers of ... [more ▼]

Transactional database management systems (DBMS) have been successful at supporting traditional transaction processing workloads. However, web-based applications that tend to generate huge numbers of concurrent business operations are pushing DBMS performance over their limits, thus threatening overall system availability. Then, a crucial question is how to test DBMS performance under heavy workload conditions. Answering this question requires a testing methodology to set up non-biased conditions for pushing a particular DBMS over its normal performance limits (i.e., to stress it). In this article, we present a stress testing methodology for DBMS to search for defects in supporting very heavy workloads. Our methodology leverages distributed testing techniques and takes into account the various biases that may affect the test results. It progressively increases the workload along with several tuning steps up to a stress condition. We validate our methodology with empirical studies on two popular DBMS (one proprietary, one open-source) and detail the defects that have been found. [less ▲]

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