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X-WR-CALDESC:Events for Information Systems Group
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DTSTART;TZID=America/Los_Angeles:20190318T110000
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DTSTAMP:20261108T035144
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UID:1146-1552906800-1552910400@isg.ics.uci.edu
SUMMARY:Xiangyao Yu: Transaction Processing at Scale
DESCRIPTION:Abstract: \nOnline transaction processing (OLTP) is critical for applications including finance\, e-commerce\, social networks\, and healthcare. The increasing performance demands of these applications require OLTP to scale massively. Concurrency control is a major scalability bottleneck in such systems. \nThis talk presents three projects that identify and help resolve scalability challenges. First\, I present a scalability study of concurrency control on a simulated 1000-core processor and show the bottlenecks that constrain the scaling of classic algorithms. Then\, I present a new protocol called TicToc that removes the bottleneck of central timestamp allocation on multicore processors. The key technique is data-driven timestamp management that dynamically calculates each transaction’s timestamp based on its data access pattern. Finally\, I present Sundial\, a distributed concurrency control scheme that mitigates the bottleneck of long network latency through a lightweight caching protocol. The talk ends with a vision of transaction processing in the era of cloud computing and internet of things. \nBio: \nXiangyao Yu is a postdoctoral associate at Computer Science and Artificial Intelligence Lab (CSAIL) at Massachusetts Institute of Technology (MIT) under the supervision of Prof. Michael Stonebraker. He acquired his Ph.D. at MIT in 2017 and B.S. at Tsinghua University in 2012. His research interest centers on databases with additional expertise in computer architecture. He won the best Ph.D. thesis award in EECS at MIT and has three best paper awards or nominations. \nhttp://people.csail.mit.edu/yxy \nFor directions/parking information\, please visit: \nhttps://uci.edu/visit/maps.php and http://www.ics.uci.edu/about/visit/index.php
URL:https://isg.ics.uci.edu/event/xiangyao-yu-transaction-processing-at-scale/
LOCATION:DBH 3011
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DTSTART;TZID=America/Los_Angeles:20190321T140000
DTEND;TZID=America/Los_Angeles:20190321T150000
DTSTAMP:20261108T035144
CREATED:20190311T060555Z
LAST-MODIFIED:20190311T060555Z
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SUMMARY:Fatemeh Nargesian: Data Enrichment for Data Science
DESCRIPTION:Data Enrichment for Data Science\nFatemeh Nargesian\, University of Toronto\n\nMarch 21\, Thursday\, 2019\n\n2:00 – 3 pm\, DBH 3011\nRefreshments start at 1:30 pm\n\n\n\n\nData Science is built on the power of data processing and data preparation. In this talk\, I discuss the challenges of data preparation for end-to-end data science. Particularly\, I talk about data enrichment via discovery where the goal is to discover and integrate the right data to solve a given data science problem. I introduce two paradigms of data discovery. In the first paradigm\, the query is a dataset and a data scientist is interested in interactively finding datasets that can be integrated (e.g unioned) with the query. I introduce a probabilistic framework for searching for top-k unionable tables and discuss the need for distribution-aware techniques for data discovery. In the second paradigm\, search does not start with a query\, instead\, it is data-driven. I will talk about data lake organization problem where the goal is to build a directory structure that enables users to most efficiently navigate data lakes. I will present a navigation model of how users interact with a directory structure and introduce a scalable local search algorithm for optimizing data lake organizations.\n\n————————————–\n\nBio:\nFatemeh Nargesian is a PhD candidate in the Data Curation Group of the Department of Computer Science at University of Toronto. Her primary research interests are in the data management challenges of end-to-end data science. A paper she co-authored on data discovery was accorded the Best Demonstration Award at VLDB 2017. While at University of Toronto\, Fatemeh was a joint Research intern at IBM Research-NY. Prior to University of Toronto\, she worked on clinical data management at the Clinical Informatics Research Group at McGill University\, and received M.Sc. degrees in Computer Science at University of Ottawa and Artificial Intelligence at Sharif University of Technology.
URL:https://isg.ics.uci.edu/event/fatemeh-nargesian-data-enrichment-for-data-science/
LOCATION:DBH 3011
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