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Abstract Virtual machine technologies oer,simple and practical mechanisms to address many manageability problems in database systems. For example, these technologies allow for server consolidation, easier deployment, and more exible provisioning. Therefore, database systems are increasingly being run on virtual machines. This oers,many unique oppor...
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Virtualization becomes a very common solution in enterprise and small systems. Therefore, virtualization decreases financial costs and decreases system administration efforts. Also virtualization has been proven to be one of the most efficient approaches to implementing highly available systems. One of the most common software systems deployed in v...
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... In the interest of space, we only present results for the ten queries whose run time in the Base system inTable 1 exceeds 2 seconds. The results for the other queries are similar, and can be found in [9]. In order to get an insight into the cause of the overhead, we use the mpstat tool to break down the overall run time of each query into user time and system time.Figure 1 shows the relative slowdown (defined similarly toTable 1) in user and system time for the ten selected queries.We can see that both the user time and the system time of almost all queries experience slowdown in Xen compared to Base. ...
... If we turn the Linux prefetching mechanism off in DomU, the amount of data read is very close to the actual data required by the queries and the queries no longer run faster inside Xen. More details are available in [9]. The point of this experiment is not to suggest using virtualization to implement prefetching. ...
Virtual machine technologies offer simple and practical mechanisms to address many manageability problems in database systems. For example, these technologies allow for server consolidation, easier deployment, and more flexible provisioning. Therefore, database systems are increasingly being run on virtual machines. This offers many opportunities for researchers in self-managing database systems, but it is also important to understand the cost of visualization. In this paper, we present an experimental study of the overhead of running a database workload on a virtual machine. We show that the average overhead is less than 10%, and we present details of the different causes of this overhead. Our study shows that the manageability benefits of virtualization come at an acceptable cost.
Key-value stores such as Cassandra and HBase have gained popularity as for their scalability and high availability in the face of heavy workloads and hardware failure. Many enterprises are deploying applications backed by key-value stores on to resources leased from Infrastructure as a Service (IaaS) providers. However, current key-value stores are unable to take full advantage of the resource elasticity provided by IaaS providers due to several challenges: i) high performance of data access in virtualised environments; ii) load-rebalancing as the system scales up and down; and iii) the lack of autoscaling controllers. In this paper I present my research efforts on addressing these issues to provide an elastic key-value store deployed in IaaS environments.
