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UID:114@lincs.fr
DTSTART;TZID=Europe/Paris:20150114T140000
DTEND;TZID=Europe/Paris:20150114T150000
DTSTAMP:20170313T171205Z
URL:https://www.lincs.fr/events/platforms-applications-big-fast-data-analy
 tics/
SUMMARY:Platforms and Applications for &quot\;Big and Fast&quot\; Data
 Analytics
DESCRIPTION:Recently there has been a significant interest in building big
 data systems that can handle not only "big data" but also "fast data" for
 analytics. Our work is strongly motivated by recent real-world case studies
 that point to the need for a general\, unified data processing framework to
 support analytical queries with different latency requirements. Towards
 this goal\, our project is designed to transform the popular MapReduce
 computation model\, originally proposed for batch processing\, into
 distributed (near) real-time processing. In this talk\, I start by
 examining the widely used Hadoop system and presenting a thorough analysis
 to understand the causes of high latency in Hadoop. I then present a number
 of necessary architectural changes\, as well as new resource configuration
 and optimization techniques to meet user-specified latency requirements
 while maximizing throughput. Experiments using typical workloads in click
 stream analysis and twitter feed analysis show that our techniques reduce
 the latency from tens or hundreds of seconds in Hadoop to sub-second in our
 system\, with 2x-7x increase in throughput. Our system also outperforms
 state-of-the-art distributed stream systems\, Twitter Storm and Spark
 Streaming\, by a wide margin. Finally\, I will show some initial results
 and challenges of supporting big and fast data analytics in the emerging
 domain of genomics.\n\nBiography: Yanlei Diao is Associate Professor of
 Computer Science at the University of Massachusetts Amherst. Her research
 interests are in information architectures and data management systems\,
 with a focus on big data analytics\, data streams\, uncertain data
 management\, and RFID and sensor data management. She received her PhD in
 Computer Science from the University of California\, Berkeley in 2005\, her
 M.S. in Computer Science from the Hong Kong University of Science and
 Technology in 2000\, and her B.S. in Computer Science from Fudan University
 in 1998. Yanlei Diao was a recipient of the 2013 CRA-W Borg Early Career
 Award (one female computer scientist selected each year)\, IBM Scalable
 Innovation Faculty Award\, and NSF Career Award\, and she was a finalist of
 the Microsoft Research New Faculty Award. She spoke at the Distinguished
 Faculty Lecture Series at the University of Texas at Austin. Her PhD
 dissertation "Query Processing for Large-Scale XML Message Brokering" won
 the 2006 ACM-SIGMOD Dissertation Award Honorable Mention. She is currently
 Editor-in-Chief of the ACM SIGMOD Record\, Associate Editor of ACM TODS\,
 Area Chair of SIGMOD 2015\, and member of the SIGMOD Executive Committee
 and SIGMOD Software Systems Award Committee. In the past\, she has served
 as Associate Editor of PVLDB\, organizing committee member of SIGMOD\,
 CIDR\, DMSN\, and the New England Database Summit\, as well as on the
 program committees of many international conferences and workshops. Her
 research has been strongly supported by industry with awards from Google\,
 IBM\, Cisco\, NEC labs\, and the Advanced Cybersecurity Center.
CATEGORIES:Seminars,Youtube
LOCATION:LINCS Meeting Room 40\, 23\, avenue d'Italie\, Paris\, 75013\,
 France
GEO:48.8283983;2.3568972000000485
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DTSTART:20141026T020000
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