Coconut Palm：掌上型静态和流数据系列探索
Coconut Palm: Static and Streaming Data Series Exploration Now in your Palm
摘要：
许多现代应用程序产生大量的数据序列流，并将它们保存在索引中，以便能够通过最近邻搜索来探索它们。然而，现有的数据系列索引操作起来很昂贵，因为它们向存储发出许多随机I/O。为了解决这个问题，我们最近提出了Coconut，这是一种新的基础设施，它基于一种新的可排序格式来组织数据序列。通过这种方式，Coconut能够利用最先进的索引技术，首次依靠排序来使用快速顺序I/O构建、维护和查询数据系列索引。在此演示中，我们展示了Coconut Palm，一种新的探索工具，允许交互式地结合Coconut基础设施中的不同索引技术，从而无缝地探索来自各种科学领域的数据系列。域.我们强调了Coconut提供的丰富的索引设计选择，并提出了一个新的推荐工具，允许用户智能地导航静态和流数据探索场景。
英文摘要：
Many modern applications produce massive streams of data series and maintain them in indexes to be able to explore them through nearest neighbor search. Existing data series indexes, however, are expensive to operate as they issue many random I/Os to storage. To address this problem, we recently proposed Coconut, a new infrastructure that organizes data series based on a new sortable format. In this way, Coconut is able to leverage state-of-the-art indexing techniques that rely on sorting for the first time to build, maintain and query data series indexes using fast sequential I/Os. In this demonstration, we present Coconut Palm, a new exploration tool that allows to interactively combine different indexing techniques from within the Coconut infrastructure and to thereby seamlessly explore data series from across various scientific domains. We highlight the rich indexing design choices that Coconut opens up, and we present a new recommender tool that allows users to intelligently navigate them for both static and streaming data exploration scenarios.
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。
