论文标题
Vegafusion：交互式VEGA可视化的自动服务器端缩放
VegaFusion: Automatic Server-Side Scaling for Interactive Vega Visualizations
论文作者
论文摘要
VEGA语法已被基于浏览器的可视化工具的不断增长的生态系统广泛采用。但是，参考Vega渲染器不能很好地扩展到大型数据集（例如，数百万行或数百个兆字节），因为它要求将整个数据集加载到浏览器内存中。我们介绍了Vegafusion，将自动服务器端缩放带到Vega生态系统。 Vegafusion接受通用VEGA规格，并分区客户端与浏览器外部编译的服务器端过程之间所需的计算。可以处理大型数据集，以避免将它们加载到浏览器中，并利用多线程，更强大的服务器硬件和缓存。我们演示了如何将Vegafusion集成到现有的Vega生态系统中，并表明Vegafusion极大地超过了参考实现。我们通过与客户端以及远程计算机上的同一台机器上运行的Vegafusion来证明这些好处。
The Vega grammar has been broadly adopted by a growing ecosystem of browser-based visualization tools. However, the reference Vega renderer does not scale well to large datasets (e.g., millions of rows or hundreds of megabytes) because it requires the entire dataset to be loaded into browser memory. We introduce VegaFusion, which brings automatic server-side scaling to the Vega ecosystem. VegaFusion accepts generic Vega specifications and partitions the required computation between the client and an out-of-browser, natively-compiled server-side process. Large datasets can be processed server-side to avoid loading them into the browser and to take advantage of multi-threading, more powerful server hardware and caching. We demonstrate how VegaFusion can be integrated into the existing Vega ecosystem, and show that VegaFusion greatly outperforms the reference implementation. We demonstrate these benefits with VegaFusion running on the same machine as the client as well as on a remote machine.
