Aggregate Queries Over Conditional Tables
Journal of Intelligent Information Systems
OLAP over uncertain and imprecise data
The VLDB Journal — The International Journal on Very Large Data Bases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
MCDB: a monte carlo approach to managing uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
An improvement on the complexity of factoring read-once Boolean functions
Discrete Applied Mathematics
Probabilistic top-k and ranking-aggregate queries
ACM Transactions on Database Systems (TODS)
Using OBDDs for Efficient Query Evaluation on Probabilistic Databases
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Conditioning probabilistic databases
Proceedings of the VLDB Endowment
Journal of Artificial Intelligence Research
The trichotomy of HAVING queries on a probabilistic database
The VLDB Journal — The International Journal on Very Large Data Bases
Aggregate queries for discrete and continuous probabilistic XML
Proceedings of the 13th International Conference on Database Theory
Incremental query evaluation in a ring of databases
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Provenance for aggregate queries
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Querying uncertain data with aggregate constraints
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Sensitivity analysis and explanations for robust query evaluation in probabilistic databases
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Making Aggregation Work in Uncertain and Probabilistic Databases
IEEE Transactions on Knowledge and Data Engineering
Probabilistic Databases
Anytime approximation in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
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This paper presents a query evaluation technique for positive relational algebra queries with aggregates on a representation system for probabilistic data based on the algebraic structures of semiring and semimodule. The core of our evaluation technique is a procedure that compiles semimodule and semiring expressions into so-called decomposition trees, for which the computation of the probability distribution can be done in time linear in the product of the sizes of the probability distributions represented by its nodes. We give syntactic characterisations of tractable queries with aggregates by exploiting the connection between query tractability and polynomial-time decomposition trees. A prototype of the technique is incorporated in the probabilistic database engine SPROUT. We report on performance experiments with custom datasets and TPC-H data.