Coconut：静态和流数据系列上可伸缩索引的可排序摘要
Coconut: sortable summarizations for scalable indexes over static and streaming data series
摘要：
许多现代应用程序产生需要分析的大量数据序列流，需要高效的相似性搜索操作。然而，用于此目的的最先进的数据系列索引在性能或存储成本方面不能很好地扩展大规模数据集。我们指出的问题，用于索引的数据系列的现有摘要不能排序，同时保持类似的数据系列接近彼此的排序顺序的事实。为了解决这个问题，我们提出了椰子，第一个数据系列索引的基础上可排序的摘要和第一个有效的解决方案，索引和查询流系列。Coconut的第一个创新是一个反向的、可排序的数据序列汇总，它基于z顺序曲线组织数据序列，使相似的序列在排序顺序中彼此接近。因此，椰子是能够使用批量加载和更新技术，依靠排序快速建立和维护一个连续的索引使用大型顺序磁盘I/O。然后，我们探索基于前缀和基于中位数的拆分策略自底向上批量加载，显示基于中位数的拆分优于最先进的，确保所有节点都密集填充。最后，我们探讨了可变大小的窗口查询的排序摘要的影响，表明它们可以通过有效的合并时间分区的更新的存在下支持。总的来说，我们通过分析和经验表明，Coconut在构建速度、查询速度和存储成本方面主导了最先进的数据系列索引。
英文摘要：
Many modern applications produce massive streams of data series that need to be analyzed, requiring efficient similarity search operations. However, the state-of-the-art data series indexes that are used for this purpose do not scale well for massive datasets in terms of performance, or storage costs. We pinpoint the problem to the fact that existing summarizations of data series used for indexing cannot be sorted while keeping similar data series close to each other in the sorted order. To address this problem, we present Coconut, the first data series index based on sortable summarizations and the first efficient solution for indexing and querying streaming series. The first innovation in Coconut is an inverted, sortable data series summarization that organizes data series based on a z-order curve, keeping similar series close to each other in the sorted order. As a result, Coconut is able to use bulk loading and updating techniques that rely on sorting to quickly build and maintain a contiguous index using large sequential disk I/Os. We then explore prefix-based and median-based splitting policies for bottom-up bulk loading, showing that median-based splitting outperforms the state of the art, ensuring that all nodes are densely populated. Finally, we explore the impact of sortable summarizations on variable-sized window queries, showing that they can be supported in the presence of updates through efficient merging of temporal partitions. Overall, we show analytically and empirically that Coconut dominates the state-of-the-art data series indexes in terms of construction speed, query speed, and storage costs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
