NoSQL databases such as Apache Cassandra have attracted large interest in recent years thanks to their high availability, scalability, flexibility and low latency. Still there is limited research work on performance engineering methods for NoSQL databases, which yet are needed since these systems are highly distributed and thus can incur significant cost/performance trade-offs. To address this need, we propose a novel queueing network model for the Cassandra NoSQL database aimed at supporting resource provisioning. The model defines explicitly key configuration parameters of Cassandra such as consistency levels and replication factor, allowing engineers to compare alternative system setups.Experimental results based on the YCSB benchmark indicate that, with a small amount of training for the estimation of its input parameters, the proposed model achieves good predictive accuracy across different loads and consistency levels. The average performance errors of the model compared to the real results are between 6% and 10%. We also demonstrate the applicability of our model to other NoSQL databases and other possible utilisation of it.

Apache Cassandra has emerged as one of the most widely adopted NoSQL databases. However, there is still a limited understanding on how to optimally operate Cassandra in the cloud using autoscaling methods, by which resources can be scaled up or down to reduce operational costs and meet servicelevel objectives (SLOs). To address this limitation, we present PAX, a partition-aware elastic resource management system for Apache Cassandra. PAX uses low-overhead query sampling and knowledge of the datapartitioning across the nodes to automatically adapt capacity in Cassandra clusters. Differently from existing autoscaling methods for Cassandra, which incur large acquisition times for new nodes, PAX exploits Cassandra's hinted handoff mechanism and a shared hints storage to minimize the time needed to acquire a node into the cluster. We propose a reactive and a proactive implementation of PAX and compare their performance against different workloads with varying intensities and item popularity distributions, finding that the proactive version significantly reduces SLO violations.

Estimating performance models parameters of cloud systems presents several challenges due to the distributed nature of the applications, the chains of interactions of requests with architectural nodes, and the parallelism and coordination mechanisms implemented within these systems. In this work, we present a new inference algorithm for model parameters, called state divergence (SD) algorithm, to accurately estimate resource demands in a complex cloud application. Differently from existing approaches, SD attempts to minimize the divergence between observed and modeled marginal state probabilities for individual nodes within an application, therefore requiring the availability of probabilistic measures from both the system and the underpinning model. Validation against a case study using the Apache Cassandra NoSQL database and random experiments show that SD can accurately predict demands and improve system behavior modeling and prediction.

Introduction: Intestinal invagination is a common pathology amongst children, while it is a rare entity in adults. Invagination is responsible for only 1-3% of adult-onset intestinal obstruction. Meckel’s diverticulum, on the other hand, is the most common congenital anomaly of the gastrointestinal tract. Most of them are asymptomatic; they are recognized when they complicate, and can present with diverticulitis, gastrointestinal bleeding, intestinal obstruction, perforation, or invagination. Invagination with the Meckel’s diverticulum (MD) is a rare cause of chronic abdominal pain in the adults. We wish to present this first case of intestinal invagination and Meckel ‘s diverticulum invaginated. Presentation of case: We report the case of a 17-year-old man who was admitted to the emergency room due to a diffuse abdominal pain. Abdominal CT scan showed intestinal invagination and intestinal obstruction. The exploratory laparoscopy revealed the presence of intestinal invagination and segmental resection of the small intestine was performed. The patient was discharged on the sixteen post-operative day. Discussion: The prevalence of MD is 1 to 4%. Diagnosis is often difficult and delayed because clinical symptoms are not specific and the diagnosis is performed mainly by imaging studies. Intestinal obstruction is a more common complication in adults, whereas in children, bleeding is the more common complication. In our case, the patient had a diffuse abdominal pain with small bowel obstruction. Laparoscopy may be useful for confirming the presence of intestinal invagination, and demonstrating the underlying organic lesion serving as the lead point. Only with the laparotomy we have been able to notice the combination of intestinal invagination and MD invaginated. Conclusion: we aimed to present the role of Meckel’s diverticulum as an initiating factor of illegible invagination, with inversion into the ileum and specifically in our clinical case can cause invagination of itself.

No abstract