Plywood

Plywood is a JavaScript library that simplifies building interactive visualizations and applications for large data sets. Plywood acts as a middle-layer between data visualizations and data stores.

Plywood is architected around the principles of nested Split-Apply-Combine, a powerful divide-and-conquer algorithm that can be used to construct all types of data visualizations. Plywood comes with its own expression language where a single Plywood expression can translate to multiple database queries, and where results are returned in a nested data structure so they can be easily consumed by visualization libraries such as D3.js.

You can use Plywood in the browser and/or in node.js to easily create your own visualizations and applications.

Plywood also acts as a very advanced query planner for Druid, and Plywood will determine the most optimal way to execute Druid queries.

Installation

To use Plywood from npm simply run: npm install plywood.

Plywood can also be used by the browser.

Documentation

To learn more, see http://plywood.imply.io

项目文档结构

• docs/ - 项目文档目录
  • docs/features/ - 功能特性文档
    • subtotalsSpec 优化详细文档
    • subtotalsSpec 优化使用指南
  • docs/examples/ - 示例代码
• tests/ - 测试文件目录
  • tests/subtotals/ - subtotalsSpec 优化测试

新功能特性

subtotalsSpec 查询优化

利用 Apache Druid 的 subtotalsSpec 特性，将多次查询合并为一次查询，大幅提升多维度分析的查询性能。

快速开始:

const result = await expression.compute(context, {
  customOptions: {
    useSubtotalsSpec: true    // 启用 subtotalsSpec 优化
  }
});

性能提升: 60-90% 的查询时间减少

详细信息请参考：subtotalsSpec 优化文档

Also see

• Pivot - a data exploration GUI built using Plywood.
• PlyQL - a SQL-like interface to plywood
• Vadim Ogievetsky talks about the inspiration behind Plywood

Development

To run all the Plywood unit tests you will need to set up the data sources in the DataZoo.

Questions & Support

For updates about new and upcoming features follow @implydata on Twitter.

Please file bugs and feature requests by opening and issue on GitHub and direct all questions to our user groups.