This paper presents Odyssey, a novel distributed data-series processing framework that efficiently addresses the critical challenges of exhibiting good speedup and ensuring high scalability in data series processing by taking advantage of the full computational capacity of modern clusters comprised of multi-core servers. Odyssey addresses a number of challenges in designing efficient and highly scalable distributed data series index, including efficient scheduling, and load-balancing without paying the prohibitive cost of moving data around. It also supports a flexible partial replication scheme, which enables Odyssey to navigate through a fundamental trade-off between data scalability and good performance during query answering. Through a wide range of configurations and using several real and synthetic datasets, our experimental analysis demonstrates that Odyssey achieves its challenging goals.
翻译:本文介绍了奥德赛,这是一个新颖的分发数据系列处理框架,它通过利用由多核心服务器组成的现代集群的全面计算能力,有效应对显示良好速度和确保数据序列处理的高度可扩缩性等重大挑战,奥德赛在设计高效和高度可扩缩的分布数据系列指数(包括高效的时间安排)和在不支付移动数据高昂费用的情况下平缓负荷方面应对了若干挑战,它还支持一个灵活的部分复制计划,使奥德赛能够在查询回答时通过数据可扩缩性和良好性能之间的根本平衡,通过多种配置和使用若干真实和合成数据集,我们的实验分析表明奥德赛实现了其具有挑战性的目标。