Vertical partitioning algorithms for database design
ACM Transactions on Database Systems (TODS)
Vertical partitioning for database design: a graphical algorithm
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
The SDSS skyserver: public access to the sloan digital sky server data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
A heuristic approach to attribute partitioning
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Horizontal data partitioning in database design
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
A Transaction-Based Approach to Vertical Partitioning for Relational Database Systems
IEEE Transactions on Software Engineering
A Vertical Partitioning Algorithm for Relational Databases
Proceedings of the Third International Conference on Data Engineering
Applying genetic algorithms in database partitioning
Proceedings of the 2003 ACM symposium on Applied computing
AutoPart: Automating Schema Design for Large Scientific Databases Using Data Partitioning
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
An adaptable vertical partitioning method in distributed systems
Journal of Systems and Software
Research issues in automatic database clustering
ACM SIGMOD Record
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Vertical partitioning is an effective way of improving performance in the database systems where a significant percentage of query processing time is spent on the full scans of relational tables. Vertical partitioning provides even more compelling performance gains when it is combined with the controlled replication of data in the environments where the processing of queries dominates the data manipulations. This paper proposes a new algorithm that finds a suboptimal vertical partitioning of relational tables under a constraint that certain level of redundancies is acceptable in a database. The algorithm is based on a new cost model, which precisely estimates I/O throughput as the total number of physical read/write database operations required to implement a given workload. The solution described in the paper transforms a schema of relational database into a partitioned one and decides which components of the original schema should be replicated as the separate partitions. The experiments conducted in this research and reported in the paper confirm the correctness of the cost model used by the vertical partitioning algorithm and demonstrate the expected performance gains from the partitioning.