7,193 research outputs found
Partout: A Distributed Engine for Efficient RDF Processing
The increasing interest in Semantic Web technologies has led not only to a
rapid growth of semantic data on the Web but also to an increasing number of
backend applications with already more than a trillion triples in some cases.
Confronted with such huge amounts of data and the future growth, existing
state-of-the-art systems for storing RDF and processing SPARQL queries are no
longer sufficient. In this paper, we introduce Partout, a distributed engine
for efficient RDF processing in a cluster of machines. We propose an effective
approach for fragmenting RDF data sets based on a query log, allocating the
fragments to nodes in a cluster, and finding the optimal configuration. Partout
can efficiently handle updates and its query optimizer produces efficient query
execution plans for ad-hoc SPARQL queries. Our experiments show the superiority
of our approach to state-of-the-art approaches for partitioning and distributed
SPARQL query processing
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
We introduce BriskStream, an in-memory data stream processing system (DSPSs)
specifically designed for modern shared-memory multicore architectures.
BriskStream's key contribution is an execution plan optimization paradigm,
namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair
of producer-consumer operators into consideration. We propose a branch and
bound based approach with three heuristics to resolve the resulting nontrivial
optimization problem. The experimental evaluations demonstrate that BriskStream
yields much higher throughput and better scalability than existing DSPSs on
multi-core architectures when processing different types of workloads.Comment: To appear in SIGMOD'1
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Valued Redundancy
Replicated objects increase distributed system performance and availability. An object is more valuable to the system if it contributes more to system performance (e.g. it is frequently accessed) and availability. Similarly, an object is less valuable if it is expensive to maintain (e.g. it is a large object). By replicating only the most valuable objects we use redundancy to maximize system performance and availability a t low cost. A simulation study of a distributed main-memory database shows substantial performance and availability gains with valued redundancy
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