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
Efficient mining of association rules using closed itemset lattices
Information Systems
Automating physical database design in a parallel database
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Fundamentals of Computer Alori
Fundamentals of Computer Alori
A Transaction-Based Approach to Vertical Partitioning for Relational Database Systems
IEEE Transactions on Software Engineering
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Automatic physical design tuning: workload as a sequence
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Constrained physical design tuning
Proceedings of the VLDB Endowment
On-Line Index Selection for Shifting Workloads
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Tuning database configuration parameters with iTuned
Proceedings of the VLDB Endowment
Schism: a workload-driven approach to database replication and partitioning
Proceedings of the VLDB Endowment
Semi-automatic index tuning: keeping DBAs in the loop
Proceedings of the VLDB Endowment
Autonomous database partitioning using data mining on single computers and cluster computers
Proceedings of the 16th International Database Engineering & Applications Sysmposium
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A key factor of measuring database performance is query response time, which is dominated by I/O time. Database partitioning is among techniques that can help users reduce the I/O time significantly. However, how to efficiently partition tables in a database is not an easy problem, especially when we want to have this partitioning task done automatically by the system itself. This paper introduces an algorithm called Self-Managing Online Partitioner for Databases (SMOPD) in vertical partitioning based on closed item sets mining from a query set and system statistic information mined from system statistic views. This algorithm can dynamically monitor the database performance using user-configured parameters and automatically detect the performance trend so that it can decide when to perform a re-partitioning action without feedback from DBAs. This algorithm can free DBAs from the heavy tasks of keeping monitoring the system and struggling against the large statistic tables. The paper also presents the experimental results evaluating the performance of the algorithm using the TPC-H benchmark.