[Colloquium] Xi Liang Dissertation Defense/Mar 7, 2022

[Megan Woodward]

This is an announcement of Xi Liang's Dissertation Defense.
===============================================
Candidate: Xi Liang

Date: Monday, March 07, 2022

Time: 10 am CST

Remote Location: https://zoom.us/j/92237751551?pwd=VFh4bXVKQzVacXlSSU9QVHo3VTFuZz09   Passcode: 1XaqE8


Title: Synopses for Efficient and Reliable Approximate Query Processing

Abstract: Answering queries accurately at interactive speeds has become more challenging in modern data systems due to the massive growth of data. Such challenges lead to an increasing interest in Approximate Query Processing (AQP) techniques because they enable timely query execution in scenarios that can tolerate some degree of inaccuracy. While latency and accuracy have been the two main factors considered by many AQP systems, in our studies, we found other dimensions like applicability, reliability, robustness and data availability, etc. could also be the main considerations in certain scenarios and such demands call for the design of novel AQP techniques.

In this thesis, we propose novel AQP techniques of different characteristics for different scenarios where AQP can be useful. We first discuss PASS, a system that combines sampling and aggregation for better accuracy while keeping the latency and storage cost at a favorable level. As a follow-up of PASS, we present JanusAQP, a dynamic AQP system that extends the static partition tree proposed in PASS and addresses several challenges in a dynamic environment that make the system more practical. Thirdly, we propose PC, a novel missing-data analysis framework that not only enables a presentation of missing data but also the derivation of a tight hardbound for optimal reliability. Lastly, we discuss DQM, our effort in applying machine learning to manage materialized views in a robust manner.

Advisors: Sanjay Krishnan

Committee Members: Aaron Elmore, Sanjay Krishnan, and Raul Castro Fernandez




-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20220304/db54d093/attachment-0001.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: xiliang-thesis-draft-feb-compressed.pdf
Type: application/pdf
Size: 2423149 bytes
Desc: xiliang-thesis-draft-feb-compressed.pdf
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20220304/db54d093/attachment-0001.pdf>