报告题目：Coping with Big Data Volume and Variety
时间：2018年10月18日，下午3:00点
地点：光电学院楼1042会议室
报告人：陆嘉恒 芬兰赫尔辛基大学
邀请人：彭敦陆 教授
报告内容 In this talk, I will briefly introduce our two on-going research projects in the University of Helsinki: (1) Performance optimization on Hadoop and Spark platform: Nowadays open source data-intensive computing solutions, like Hadoop and Spark, are increasingly deployed as production systems for data scientists. However, the big data analytics systems such as Hadoop and Spark hold a high learning curve to the users, especially on system performance management to better utilize the system resources. I will discuss our work for an automatic toolkit for big data analytics job optimization. (2) Multi-model data management: Databases play an important role in our world today. But one of the greatest challenges in current database systems is the "Variety" of the big data. Multi-model databases have emerged to address this challenge by supporting multiple data models against a single, integrated backend. We will investigate the category theory for multi-model data management.
报告人简介: Jiaheng Lu is an Associate Professor at the University of Helsinki, Finland. His main research interests lie in the big data management and database systems, and specifically in the challenge of efficient data processing from real-life, massive data repository and Web. He got his bachelor degree in the University of Shanghai for Science and Technology, Master degree in Shanghai Jiao Tong University and Ph.D. degree in the National University of Singapore. He did two years the Postdoc research in the University of California, Irvine. He has published more than eighty papers in top database conference and journals. He has written several books, on XML, Hadoop and NoSQL databases. His book on Hadoop is one of the top-10 best-selling books in the category of computer software in China in 2013. His textbooks on XML and Hadoop has been used in different universities worldwide. He has frequently served as an organization chair and a PC member for database conferences including SIGMOD, VLDB, ICDE, EDBT, CIKM etc.