CI-P: Planning for a Community Infrastructure to Enable Pocket-Scale Data Management Research

全球20亿部智能手机和400万个应用程序已成为大多数人通信和计算体验的重要组成部分。 大多数应用程序都需要存储结构化数据，例如联系人、地址簿条目，甚至是您在《糖果粉碎传奇》中的最高分数。 大多数智能手机都包含一个名为嵌入式数据库的软件，可以帮助应用程序保存和访问这些信息。 例如，Android手机和iPhone都包含一个名为SQLite的流行嵌入式数据库。 SQLite被大量使用--项目团队在实际使用中平均每天在Android手机上测量近18万个SQLite请求。 该团队还发现，许多此类请求使用SQLite的效率低下，导致电池寿命缩短，性能降低，并可能浪费计划数据。 为了做得更好，研究需要了解问题是什么。作为该项目的一部分，该团队正在收集真实世界的数据，并构建研究人员制作更好的嵌入式数据库所需的基础设施，从而实现更长的电池寿命，更灵敏的手机和更持久的计划数据。这是一个总体项目的规划阶段，旨在使研究人员更容易探索“口袋规模”数据的挑战。 虽然服务器级数据库系统经常进行测试和调整，以实现连续的高吞吐量查询处理，但嵌入式数据库会经历交互式使用产生的低容量但突发的工作负载。 这些工作负载的动态性要大得多，这使得它们更难重现，这反过来又使得在现实环境中评估新技术和系统变得困难。 这个社区基础设施（CI）项目的最终目标是建立一个由研究人员和工业合作伙伴组成的自我维持的社区，他们可以创建和共享工作负载跟踪、基准测试、仪器和可视化工具，从而更容易评估嵌入式数据库技术的创新。 在此CI规划阶段，项目团队通过接触来自多个领域的潜在合作伙伴来建立社区，包括数据库、移动的系统、编程语言和物联网。 作为该社区的中心，该团队正在开发一个用于对嵌入式数据库进行基准测试的工具链，以及一个托管在布法罗大学的社区网站（http：pocketdata.info）。 该项目还涉及外联工作，包括辅导、讲习班和系列研讨会。 在社区的关注和支持下，嵌入式数据库基准CI有望引发对袖珍数据管理的新一轮研究兴趣。

The world's 2 billion smartphones and 4 million apps have become a large part of most people's communication and computing experiences. Most apps need to store structured data like contacts, address book entries, or even your top scores in Candy Crush. Most smartphones include a piece of software called an embedded database that helps apps save and access this information. For example, both Android phones and iPhones include a popular embedded database called SQLite. SQLite is used a lot -- the project team measured nearly 180 thousand SQLite requests per day on an average Android phone in real-world use. The team also found that lots of these requests use SQLite inefficiently, resulting in shorter battery life, slower performance, and potentially wasted plan data. To do better, research is need to understand what is the problems are. As part of this project, the team is gathering the real-world data and building the infrastructure that researchers will need to make better embedded databases, leading to longer battery life, more responsive phones, and longer-lasting plan data.This is the planning stage of an overarching project that aims to make it easier for researchers to explore the challenges of "Pocket-Scale" data. While server-class database systems are frequently tested and tuned for continuous high-throughput query processing, embedded databases experience lower-volume but bursty workloads produced by interactive use. These workloads are far more dynamic, making them much harder to reproduce, which in turn make it hard to evaluate new techniques and systems in realistic settings. The ultimate goal for this community infrastructure (CI) project is to establish a self-sustaining community of researchers and industrial partners who create and share workload traces, benchmarks, instrumentation, and visualization tools, making it easier to evaluate innovations in embedded database technology. In this CI planning stage, the project team is building up the community by reaching out to potential partners from multiple areas including databases, mobile systems, programming languages, and internet-of-things. As a hub for this community, the team is developing a toolchain for benchmarking embedded database, as well as a community website hosted at the University at Buffalo (http://pocketdata.info). The project also involves outreach efforts including tutorials, workshops, and seminar series. With the interest and support from the community, the embedded database benchmark CI is expected to spark a new wave of research interest on pocket-scale data management.