BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:IC Colloquium: Query Evaluation for Big Data
DTSTART:20210426T140000
DTEND:20210426T150000
DTSTAMP:20260408T003618Z
UID:0adf4116e778122447c96edf7982bcf26e3b54985c54a1860c00bfa9
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: Xiao Hu - Duke University\nIC Faculty candidate\n\nAbstrac
 t\nQuery evaluation has been one of the core problems in databases for mor
 e than 40 years\, while the need to process and analyze big data has invig
 orated this long-time research area with fresh challenges.  Massively par
 allel data systems\, such as MapReduce and Spark\, have become an effectiv
 e tool for handling large volumes of data\, while query evaluation algorit
 hms in these systems have to be designed so that they can scale to thousan
 ds of machines in parallel. In addition\, data is generated at very high s
 peeds\, which requires the query engine to deliver timely answers over dyn
 amic databases\, and ensure answers with robust qualities. Beyond the trad
 itional goal of efficiency\, my research has also aimed at equipping query
  evaluation algorithms in modern data analytical systems with new features
 \, such as scalability\, timeliness\, and veracity.\n\nIn this talk\, I wi
 ll focus on query evaluation for massively parallel systems for join queri
 es\, the most fundamental and practically important class of queries. I wi
 ll describe the intrinsic relationship between the join structure and its 
 parallel computational cost. In addition to a homogeneous parallel model\,
  I will also discuss some new challenges when the underlying communication
  model takes an arbitrary topology.  At last\, I will briefly discuss som
 e interesting open questions on query evaluation over dynamic databases\, 
 and conclude with exciting connections between query evaluation with other
  fields\, such as machine learning\, differential privacy\, and high-perfo
 rmance computing.  \n\nBio\nXiao Hu is a postdoctoral associate in the De
 partment of Computer Science at Duke University\, co-supervised by Prof. P
 ankaj Agarwal and Prof. Jun Yang. Prior to that\, she received her Ph.D. i
 n Computer Science and Engineering from HKUST\, and BE degree in Computer 
 Software from Tsinghua University.  Her research has focused on studying 
 fundamental problems in database theory and their implications to practica
 l systems. Her work on massively parallel join algorithms has been invited
  to ACM Transactions on Database Systems as a research paper\, as well as 
 a feature article in the Database Principles Column in SIGMOD Record.\n\nM
 ore information
LOCATION:https://epfl.zoom.us/j/89361796517?pwd=Z0UvOGJSRGxrOVZBZWpSR1hnU0
 ZIUT09
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR