III: Small: Scalable Analytics for Data Bases and Data Streams--a Unified Approach

该项目的目标是支持大数据分析的开发，并促进在大数据软件生命周期中遇到的不同执行环境中部署此类应用程序。该项目通过以下方式实现其目标：（i）设计和实现可扩展分析语言（SAL），通过用户定义的聚合函数支持高级分析的定义;（ii）开发用于SAL的编译器，其优化在包含许多节点的分布式系统上的并行MapReduce导向的执行，以及（iii）开发早期精确结果库（EARL），其增强（ii）基于数据采样提供近似结果的能力。 使用EARL，分析师可以通过简单地指定目标精度来避免MapReduce应用程序的响应速度慢和设置时间长，而不需要修改原始程序。该项目的最终交付是SAL编译器，它通过支持在此环境中实现准实时响应所需的天气和减载原语，优化了对海量数据流的连续分析查询的并行执行。这些研究成果有望在领域科学、数字政府和电子商务等领域产生重大影响。该项目支持博士学位。研究大数据分析及其管理的学生。本研究的出版物、技术报告、软件和实验数据将通过项目网站（http：//yellowstone.cs.ucla.edu/nsf-projects/nsf1218471.html）传播。

The goal of this project is to support the development of big-data analytics and facilitate the deployment of such applications over the different execution environments encountered in the life-cycle of big-data software. The project achieves its goal by (i) designing and implementating a Scalable Analytics Language (SAL) that supports the definition of advanced analytics through user-defined aggregate functions; (ii) developing a compiler for SAL that optimizes parallel MapReduce-oriented executions over distributed systems containing many nodes, and (iii) developing an early accurate result library (EARL) that enhances (ii) with the ability of providing approximate results based on sampling of the data. Using EARL, the analyst can avoid the slow response and long set up-time of MapReduce applications by simply specifying a target accuracy, with no modification of the original program required. The final delivery of the project is a SAL compiler that optimizes parallel execution of continuous analytical queries on massive data streams, by supporting the synoptic and load-shedding primitives needed to achieve quasi real-time response in this environment. These research results are expected to have great impacts in several areas, including domain science, digital government and e-commerce. The project supports Ph.D. students pursuing research on big-data analytics and their management. Publications, technical reports, software, and experimental data from this research will be disseminated via the project web site (http://yellowstone.cs.ucla.edu/nsf-projects/nsf1218471.html).