BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Information Systems Group - ECPv6.4.0.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://isg.ics.uci.edu
X-WR-CALDESC:Events for Information Systems Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20220313T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20221106T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221014T123000
DTEND;TZID=America/Los_Angeles:20221014T140000
DTSTAMP:20260424T220413
CREATED:20220926T231206Z
LAST-MODIFIED:20221011T230328Z
UID:1469-1665750600-1665756000@isg.ics.uci.edu
SUMMARY:Qiushi Bai: QueryBooster-Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting + Demo
DESCRIPTION:Title: \nQueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting \nAbstract: \nQuery latency is critical in many database-backed applications where users need answers quickly to gain timely insights and make mission-critical decisions.  “Query rewriting” is one of the query optimization techniques which transforms SQL queries to more efficient formats based on pre-defined rewriting rules.  However\, with the emergence of different domain-specific applications such as visualization and business intelligence\, existing database optimizers lack support for developers to leverage their domain knowledge to rewrite queries. \nWe propose QueryBooster\, a middleware query rewriting service that sits between the application and the database.  It requires few or no modifications to the application or the database and allows developers to introduce their own rewriting rules to optimize their SQL queries.  We call this rewriting “human-centered.”  QueryBooster aims to provide a powerful interface for users to either compose rewriting rules using a rule language or show their rewriting intentions by providing examples.  Furthermore\, with the wisdom accumulated from the crowd\, QueryBooster can also automatically recommend rewritings for new queries to the user. \nIn this talk\, I will first show a demo where QueryBooster can accelerate Tableau queries on top of the PostgreSQL database up to 100 times faster.  I then discuss the research questions we are working on in QueryBooster\, such as how to develop a rule language\, how to generate rewriting rules automatically from user-given examples\, and how to leverage crowdsources to recommend rewriting rules. \nBio: \nQiushi Bai is a Ph.D. candidate in the Computer Science Department at UC Irvine. He received his Master’s and Bachelor’s degrees in CS from Northeastern University in China. His research interests have focused on improving query performance for big data analytics and visualizations.
URL:https://isg.ics.uci.edu/event/qiushi-bai-querybooster-improving-sql-performance-using-middleware-services-for-human-centered-query-rewriting-demo/
LOCATION:DBH 4011
END:VEVENT
END:VCALENDAR