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VERSION:2.0
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SUMMARY:Scalable Query Processing in Probabilistic Databases with SPROUT 
DTSTART:20090625T101500
DTSTAMP:20260408T145811Z
UID:10346bc49dee09f7c29e3380f5bd16b19f4a78065443273fbf38eea6
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Dan Olteanu\, Oxford University\, UK\nIn this talk I wil
 l address the problem of query evaluation on probabilistic databases and p
 resent the SPROUT query engine\, which is under development at Oxford. SPR
 OUT is publicly available as an extension of the PostgreSQL 8.3.3 query en
 gine. It is specifically tailored to tractable conjunctive queries with in
 equalities and to queries that are not tractable in general but become tra
 ctable on probabilistic databases restricted by functional dependencies.\n
 \nThe major components of SPROUT are an aggregation operator for exact con
 fidence computation\, which can be naturally integrated into existing rela
 tional query plans\, and optimizations that allow to push the aggregation 
 operator or parts thereof past joins. The operator is based on a fundament
 al connection between tractable queries and linear-size Ordered Binary Dec
 ision Diagrams (OBDDs) representing the uncertainty in the answers to such
  queries.\n\nI will then discuss the secondary-storage algorithm for the a
 ggregation operator. This algorithm can compute the probability of OBDDs f
 or tractable queries without materializing them\, with main memory require
 ments only dependent on the query size\, and in a few scans over the data.
  Experiments with GBs of TPC-H data show orders of magnitude improvements 
 of SPROUT over state-of-the-art exact and approximate techniques.\nProf. O
 lteanu's homepage
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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