There is growing interest in visual data management systems that support queries with specialized operations ranging from resizing an image to running complex machine learning models. With a plethora of such operations, the basic need to receive query responses in minimal time takes a hit, especially when the client desires to run multiple such operations in a single query. Existing systems provide an ad-hoc approach where different solutions are clubbed together to provide an end-to-end visual data management system. Unlike such solutions, the Visual Data Management System (VDMS) natively executes queries with multiple operations, thus providing an end-to-end solution. However, a fixed subset of native operations and a synchronous threading architecture limit its generality and scalability. In this paper, we develop VDMS-Async that adds the capability to run user-defined operations with VDMS and execute operations within a query on a remote server. VDMS-Async utilizes an event-driven architecture to create an efficient pipeline for executing operations within a query. Our experiments have shown that VDMS-Async reduces the query execution time by 2-3X compared to existing state-of-the-art systems. Further, remote operations coupled with an event-driven architecture enables VDMS-Async to scale query execution time linearly with the addition of every new remote server. We demonstrate a 64X reduction in query execution time when adding 64 remote servers.

翻译：视觉数据管理系统日益受到关注，其支持从图像调整到复杂机器学习模型运行等专业化操作的查询。然而，大量此类操作的存在使得快速响应查询的基本需求受到挑战，尤其是当用户希望在单次查询中执行多个操作时。现有系统采用临时整合不同解决方案的零散方法构建端到端视觉数据管理系统。与此不同，视觉数据管理系统（VDMS）原生支持多操作查询，从而提供一体化解决方案。但固定原生操作子集与同步线程架构限制了其通用性与可扩展性。本文提出VDMS-Async，其扩展了VDMS运行用户自定义操作的能力，并支持在远程服务器上执行查询中的操作。VDMS-Async采用事件驱动架构构建高效操作执行流水线。实验表明，与现有最先进系统相比，VDMS-Async可将查询执行时间降低2-3倍。此外，远程操作结合事件驱动架构使得VDMS-Async的查询执行时间与每新增一台远程服务器呈线性扩展关系。实验证明，当添加64台远程服务器时，查询执行时间可降低64倍。