Coconut Palm: Static and Streaming Data Series Exploration Now in your Palm

TL;DR

Coconut Palm is an interactive exploration tool that leverages a new sortable data series format to enable efficient, sequential I/O based indexing and querying of massive data streams across scientific domains.

Contribution

The paper introduces Coconut Palm, a novel tool that combines multiple indexing techniques within the Coconut infrastructure for efficient static and streaming data series exploration.

Findings

Enables interactive exploration of data series from various scientific domains.

Supports both static and streaming data exploration scenarios.

Provides a recommender tool for navigating indexing options.

Abstract

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.