Abstract ：

We present our ongoing work in the Cloudberry project to support visualization on large amounts of data to help users gain valuable insights quickly.? Existing approaches either need to modify data systems with new sampling operations, which limits their applicability when such changes are difficult, or rely on offline samples, which cannot provide statistical guarantees for queries with arbitrary conditions.? In the Cloudberry project we take a new approach in which we push visualization computation into the database engine as much as possible. Even though we view the database as a black box, we can still model its behaviors in query execution so that we can generate SQL queries to answer visualization requests efficiently to improve the user experience.? We will demonstrate a live system to visualize more than one billion social media records with the size of a few terabytes, where users can specify arbitrary temporal, spatial, and textual conditions to explore the data.

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Chen Li is a professor in the Department of Computer Science at UC Irvine. He received his Ph.D. degree in Computer Science from Stanford University, and his M.S. and B.S. in Computer Science from Tsinghua University, China, respectively.? His research interests are in the field of data management, including data-intensive computing, query processing and optimization, visualization, and text analytics.? His current focus is building open source systems for data management and analytics.? He was a recipient of an NSF CAREER Award, several test-of-time publication awards, and many grants and industry gifts. He was once a part-time Visiting Research Scientist at Google, and a founder of a startup to commercialize university research.

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