The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...
Modern big data workflows, found in e.g., machine learning use cases, often involve iterations of cycles of batch analytics and interactive analytics on temporary data. Whereas batch analytics solutions for large volumes of raw data are well established (e ...
As various kinds of sensors penetrate our daily life (e.g., sensor networks for environmental monitoring, GPS for localization and navigation), the efficient management of massive amount of sensor data becomes increasingly important at present. Many sensor ...
We consider MapReduce workloads that are produced by analytics applications. In contrast to ad hoc query workloads, analytics applications are comprised of fixed data flows that are run over newly arriving data sets or on different portions of an existing ...
