VizQL:用于查询、分析和可视化的语言

P. Hanrahan
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引用次数: 81

摘要

传统的查询语言(如SQL和MDX)具有有限的格式化和可视化功能。因此,虽然可以编写功能强大的查询,但还需要另一层软件以有用的形式向分析人员报告或呈现结果。VizQL™旨在填补这一空白。VizQL是从斯坦福大学的Polaris系统演变而来的,它将查询、分析和可视化结合到一个单一的框架中[1]。VizQL是一种描述表格、图表、图形、地图、时间序列和可视化表格的正式语言。这些不同类型的可视化表示被统一到一个框架中,使得从一种可视化表示切换到另一种可视化表示很容易(例如,从列表视图切换到交叉选项卡到图表)。与当前的图表包和类似查询语言不同,VizQL允许无限数量的图片表达式。因此,可视化可以很容易地定制和控制。VizQL是一种声明性语言。描述了期望的画面;检索结果、执行分析计算、将结果映射到可视化表示以及呈现图像所需的低级操作由查询分析器自动生成。查询分析器将VizQL表达式编译为SQL和MDX,因此VizQL可以与关系数据库和数据池一起使用。目前的实现支持Hyperion Essbase, Microsoft SQL Server, Microsoft Analysis Services, MySQL, Oracle,以及桌面数据源,如CSV和Excel文件。此分析阶段包括许多优化,这些优化允许以交互方式浏览大型数据库。VizQL提供了新一代的可视化分析工具,将查询、分析和可视化紧密结合在一起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VizQL: a language for query, analysis and visualization
Conventional query languages such as SQL and MDX have limited formatting and visualization capabilities. Thus, although powerful queries can be composed, another layer of software is needed to report or present the results in a useful form to the analyst. VizQL™ is designed to fill that gap. VizQL evolved from the Polaris system at Stanford, which combined query, analysis and visualization into a single framework [1].VizQL is a formal language for describing tables, charts, graphs, maps, time series and tables of visualizations. These different types of visual representations are unified into one framework, making it easy to switch from one visual representation to another (e.g. from a list view to a cross-tab to a chart). Unlike current charting packages and like query languages, VizQL permits an unlimited number of picture expressions. Visualizations can thus be easily customized and controlled. VizQL is a declarative language. The desired picture is described; the low-level operations needed to retrieve the results, to perform analytical calculations, to map the results to a visual representation, and to render the image are generated automatically by the query analyzer. The query analyzer compiles VizQL expressions to SQL and MDX and thus VizQL can be used with relational databases and datacubes. The current implementation supports Hyperion Essbase, Microsoft SQL Server, Microsoft Analysis Services, MySQL, Oracle, as well as desktop data sources such as CSV and Excel files. This analysis phase includes many optimizations that allow large databases to be browsed interactively. VizQL enables a new generation of visual analysis tools that closely couple query, analysis and visualization.
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