Non first normal form relations: An algebra allowing data restructuring
Journal of Computer and System Sciences
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Incomplete object—a data model for design and planning applications
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Normalization and hierarchical dependencies in the relational data model
ACM Transactions on Database Systems (TODS)
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Database Management Systems
Remarks on the algebra of non first normal form relations
PODS '82 Proceedings of the 1st ACM SIGACT-SIGMOD symposium on Principles of database systems
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Eager Aggregation and Lazy Aggregation
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
On Line Processing of Compacted Relations
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
IBM Journal of Research and Development - Mathematics and computing
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Constraint solving via fractional edge covers
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
A consideration on normal form of not-necessarily-normalized relation in the relational data model
VLDB '77 Proceedings of the third international conference on Very large data bases - Volume 3
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
World-set decompositions: Expressiveness and efficient algorithms
Theoretical Computer Science
HYRISE: a main memory hybrid storage engine
Proceedings of the VLDB Endowment
Adapting microsoft SQL server for cloud computing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Probabilistic Databases
On minimal constraint networks
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Incrementally computing ordered answers of acyclic conjunctive queries
NGITS'06 Proceedings of the 6th international conference on Next Generation Information Technologies and Systems
Factorised representations of query results: size bounds and readability
Proceedings of the 15th International Conference on Database Theory
FDB: a query engine for factorised relational databases
Proceedings of the VLDB Endowment
On acyclic conjunctive queries and constant delay enumeration
CSL'07/EACSL'07 Proceedings of the 21st international conference, and Proceedings of the 16th annuall conference on Computer Science Logic
Scaling factorization machines to relational data
Proceedings of the VLDB Endowment
F1: a distributed SQL database that scales
Proceedings of the VLDB Endowment
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A common approach to data analysis involves understanding and manipulating succinct representations of data. In earlier work, we put forward a succinct representation system for relational data called factorised databases and reported on the main-memory query engine FDB for select-project-join queries on such databases. In this paper, we extend FDB to support a larger class of practical queries with aggregates and ordering. This requires novel optimisation and evaluation techniques. We show how factorisation coupled with partial aggregation can effectively reduce the number of operations needed for query evaluation. We also show how factorisations of query results can support enumeration of tuples in desired orders as efficiently as listing them from the unfactorised, sorted results. We experimentally observe that FDB can outperform off-the-shelf relational engines by orders of magnitude.