ISTC Researchers to Present Papers at VLDB 2017 Conference

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ISTC for Big Data principal Investigators, researchers, and their students will present a number of papers at the 2017 International Conference on Very Large Databases (VLDB 2017) in Munich, Germany, August 28-September 1, 2017.  (To read any of the papers, click on the links provided below.)

Some highlights:

  • Professor Andy Pavlo and his students at Carnegie Mellon are working to make sure database management systems (DBMSs) can take advantage of new and evolutionary hardware. PhD candidate Joy Arulraj will present the paper “Write-Behind Logging”: how to change a DBMS’s logging and recovery algorithms to use emerging non-volatile memory (NVM). Their new protocol enables the DBMS to recover nearly instantaneously from system failures and reduces the wear-down on NVM devices. This work is in collaboration with Intel Labs and is part of CMU’s extensive work on non-volatile memory databases. Read their blog post about Write-Behind Logging here.
  • Analytics require visual data exploration tools that can quickly gather and display insights from datasets at “human speed.” Techniques such as Approximate Query Processing (AQP) are increasingly important in meeting the interactivity guarantees promised by these tools—but even these techniques are straining as datasets get ever larger and more complex. Researchers in Brown University’s Data Management Research Group will present “Revisiting Reuse for Approximate Query Processing” by Alex Galakatos, Andrew Crotty, Emanuel Zgraggen, Carsten Binnig and ISTC PI Tim Kraska. They’ve developed a formulation for Approximate Query Processing that maximizes result reuse in order to improve interactivity for visual data exploration tasks. Their AQP formulation can provide low-error approximate results at interactive speeds, even for queries over rare subpopulations.

Other work being presented from ISTC researchers and participating universities includes:

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