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ares icon ares

Ares is a high performance and fault tolerant distributed stream processing system, which considers both both system performance and fault tolerant capability during task allocation and use a game-theoretic approach to obtain an optimal scheduler for task allocation. Ares greatly outperforms Storm in terms of system throughput and the average processing latency.

argus icon argus

Argus is a novel RDMA-assisted job scheduler which achieves high resource utilization by fully exploiting the structure feature of stage dependency. Comprehensive experiments using large-scale traces collected from real world show that Argus reduces job completion time and job makespan by 21% and 20%, respectively, compared to RDMA-Spark.

awesome-deeplearning icon awesome-deeplearning

深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI

ldcf icon ldcf

LDCF is a novel efficient approximate set representation structure for large-scale dynamic data sets. LDCF uses a novel multi-level tree structure and reduces the worst insertion and membership testing times from O(N) to O(1).

pstream icon pstream

PStream is a popularity-aware differentiated distributed stream processing system, which identifies the popularity of keys in the stream data and uses a differentiated partitioning scheme. PStream greatly outperforms Storm on skew distributed data in terms of throughput and processing latency.

simois icon simois

Simois is a scalable distributed stream join system, which supports efficient join operations in two streams with highly skewed data distribution. Simois can support the completeness of the join results, and greatly outperforms the existing stream join systems in terms of system throughput and the average processing latency.

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