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Many resource management systems and large-scale data processing frameworks use a reservation-based model for managing resources and scheduling tasks. We observe from the reported traces of Facebook and Google that this model leads to resource being wasted because the tasks do not use effectively the allocated resources. We confirm the problem with a trace of our production cluster. We propose an...
In this work we study the I/O performance of long, sequential workloads that mimic those of Big Data applications, to understand the implications of system virtualization on data-intensive frameworks such as Apache Hadoop and Spark, which are frequently run in clusters of Virtual Machines (VMs). We do so through an experimental measurement campaign that collects low-level traces and metrics, to show...
Virtualization is heavily used in modern private and public data centers. By enabling the consolidation of many virtual machines (VMs) in a physical server, virtualization blurs the frontier between networking and system. We have investigated in a previous work the various prices due to virtualization when a packet is moved from one VM to the physical NIC, by focusing on a pure UDP scenario and multiple...
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