Most commercial database systems do (or should) exploit many sorting techniques that are
publicly known, but not readily available in the research literature. These techniques …

MapReduce is a programming model and an associated implementation for processing and
generating large datasets that is amenable to a broad variety of real-world tasks. Users …

MapReduce is a programming model and an associated implementation for processing and
generating large data sets. Users specify a _map_ function that processes a key/value pair …

Map-Reduce is a programming model that enables easy development of scalable parallel
applications to process a vast amount of data on large clusters of commodity machines …

In large federated and shared-nothing databases, resources can exhibit widely fluctuating
characteristics. Assumptions made at the time a query is submitted will rarely hold …

Data center-scale clusters are evolving towards heterogeneous hardware for power, cost,
differentiated price-performance, and other reasons. MapReduce is a well-known …

Recent high-performance processors employ sophisticated techniques to overlap and
simultaneously execute multiple computation and memory operations. Intuitively, these …

Several application and technology trends indicate that it might be both profitable and
feasible to move computation closer to the data that it processes. In this paper, we evaluate …

We present a novel external sorting algorithm using graphics processors (GPUs) on large
databases composed of billions of records and wide keys. Our algorithm uses the data …

The increasing performance and decreasing cost of processors and memory are causing
system intelligence to move into peripherals from the CPU. Storage system designers are …