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DashQL -- Complete Analysis Workflows with SQL

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arxiv 2306.03714 v2 pith:5JZBIOUK submitted 2023-06-06 cs.HC cs.DB

classification cs.HCcs.DB
keywords analysisdashqlworkflowsgrammarlanguagecompleteoptimizationsadaptive
verification ladder T0 review T1 audit T2 compute T3 formal
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We present DashQL, a language that describes complete analysis workflows in self-contained scripts. DashQL combines SQL, the grammar of relational database systems, with a grammar of graphics in a grammar of analytics. It supports preparing and visualizing arbitrarily complex SQL statements in a single coherent language. The proximity to SQL facilitates holistic optimizations of analysis workflows covering data input, encoding, transformations, and visualizations. These optimizations use model and query metadata for visualization-driven aggregation, remote predicate pushdown, and adaptive materialization. We introduce the DashQL language as an extension of SQL and describe the efficient and interactive processing of text-based analysis workflows.

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  1. Mosaic Selections: Managing and Optimizing User Selections for Scalable Data Visualization Systems

    cs.HC 2025-07 conditional novelty 7.0 of 10

    User selections are modeled as filter predicates, and pre-aggregated materialized views are created and queried automatically, yielding sub-100 millisecond selection updates on datasets up to a billion rows.

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