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.

中文翻译：

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Coconut Palm：静态和流数据系列探索现在在您的掌中

许多现代应用程序生成大量数据系列流并将它们维护在索引中，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的操作成本很高，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，这是一种新的基础架构，可以根据新的可排序格式组织数据系列。通过这种方式，Coconut 能够利用最先进的索引技术，这些技术首次依赖排序，使用快速顺序 I/O 来构建、维护和查询数据系列索引。在这个演示中，我们展示了 Coconut Palm，这是一种新的探索工具，它允许交互地结合 Coconut 基础设施内的不同索引技术，从而无缝探索来自各个科学领域的数据系列。